You searched for subject:(Human face recognition Computer science ).
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Rutgers University
1.
Pham, Hai, 1985-.
Learning human facial performance: analysis and synthesis.
Degree: PhD, Computer Science, 2019, Rutgers University
URL: https://rucore.libraries.rutgers.edu/rutgers-lib/60045/ 
► Human faces convey a large range of semantic meaning through facial expressions, which reflect both actions and affective states. More importantly, in the coming age…
(more)
▼ Human faces convey a large range of semantic meaning through facial expressions, which reflect both actions and affective states. More importantly, in the coming age of artificial intelligence and virtual persona, facial expressions can serve as a two-way communicative interface between human and machine. In this dissertation, we study two aspects of face and facial expression modeling: the analysis and reconstruction of human facial expressions via interpretable 3D blendshape representation from different input modalities, and the reversed problem in which we train a model to hallucinate coherent facial expressions directly given any arbitrary portrait and facial action parameters.
First, we present a real-time robust 3D face tracking framework from RGBD videos, driven by an efficient and flexible 3D shape regressor, capable of tracking head pose, facial actions and on-the-fly identity adaptation in extreme instances. Second, we introduce a series of recurrent neural networks to predict facial action intensities from speech for real-time animation. Finally, we present a novel deep generative neural network that can directly manipulate image pixels of a portrait to make the unseen subject express various emotions controlled by continuous facial action unit coefficients, while maintaining her personal characteristics. Our model enables flexible, effortless facial expression editing.
Advisors/Committee Members: Pavlovic, Vladimir (chair), Metaxas, Dimitris (internal member), Elgammal, Ahmed (internal member), Luo, Jiebo (outside member), School of Graduate Studies.
Subjects/Keywords: Human face recognition (Computer science)
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APA (6th Edition):
Pham, Hai, 1. (2019). Learning human facial performance: analysis and synthesis. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/60045/
Chicago Manual of Style (16th Edition):
Pham, Hai, 1985-. “Learning human facial performance: analysis and synthesis.” 2019. Doctoral Dissertation, Rutgers University. Accessed March 09, 2021.
https://rucore.libraries.rutgers.edu/rutgers-lib/60045/.
MLA Handbook (7th Edition):
Pham, Hai, 1985-. “Learning human facial performance: analysis and synthesis.” 2019. Web. 09 Mar 2021.
Vancouver:
Pham, Hai 1. Learning human facial performance: analysis and synthesis. [Internet] [Doctoral dissertation]. Rutgers University; 2019. [cited 2021 Mar 09].
Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/60045/.
Council of Science Editors:
Pham, Hai 1. Learning human facial performance: analysis and synthesis. [Doctoral Dissertation]. Rutgers University; 2019. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/60045/
Michigan State University
2.
Best-Rowden, Lacey.
Face recognition : role of aging and quality covariates.
Degree: 2016, Michigan State University
URL: http://etd.lib.msu.edu/islandora/object/etd:4719
► Thesis Ph. D. Michigan State University. Computer Science 2016
A technology once seen only in television dramas, automatic face recognition systems are now deployed in…
(more)
▼ Thesis Ph. D. Michigan State University. Computer Science 2016
A technology once seen only in television dramas, automatic face recognition systems are now deployed in many important applications. Recognition of individuals from facial images is used for de-duplication of identification cards (e.g., driver's licenses and passports), verification of prisoner identities, and tag suggestions for personal photo collections. Face images acquired in such applications are conducive to the current capabilities of face recognition algorithms; state-of-the-art systems are able to recognize constrained face images with close to 99% accuracy. However, the performance of automatic face recognition degrades when processing unconstrained face images (i.e., image acquisition is uncontrolled and subjects may be uncooperative). In such scenarios, a face image may simultaneously contain multiple confounding factors, or covariates, such as variations in facial pose, illumination, expression, occlusion, resolution, and facial aging.The first contribution of this dissertation is a framework for matching a collection of unconstrained face media (images, videos, 3D model, demographics, facial sketch) when multiple instances of a subject's face are available. This is particularly relevant to forensicinvestigations where the goal is to identify a \person of interest" based on low quality face images and videos (e.g., captured by surveillance cameras or mobile phones of bystanders) and other information compiled during the investigation (e.g., gender, race, age, facial sketch). While traditional face matching methods generally take a single media (i.e., a still face image, video track, or face sketch) as input, this work considers using the entire gamut of media as a probe to generate a single candidate list for the person of interest. We show that the proposed approach boosts the likelihood of correctly identifying the person of interest through the use of different fusion schemes, 3D face models, and incorporation of quality measures for fusion and video frame selection.Secondly, this dissertation proposes an automatic measure of the quality of an unconstrained face image, where quality is defined as a measure of the utility of a face image to automatic face recognition. A large database of unconstrained face images is first annotated with target quality labels using two methods: (i) human assessments of face image quality, and (ii) quality values computed from similarity scores. A support vector regression model trained on image features automatically extracted using a deep convolutional neural network is then used to predict the quality of an unseen face image. Results demonstrate that target quality values from human assessments and similarity scores are not highly correlated with each other, but both are useful for applications of face image quality, such as to reject low-quality face images prior to matching and to rank a collection of face images based on quality.Finally, this dissertation addresses the important problem of facial…
Advisors/Committee Members: Jain, Anil K, Liu, Xiaoming, Ross, Arun, Aviyente, Selin.
Subjects/Keywords: Human face recognition (Computer science); Human face recognition (Computer science) – Mathematical models; Computer science
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APA (6th Edition):
Best-Rowden, L. (2016). Face recognition : role of aging and quality covariates. (Thesis). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:4719
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Best-Rowden, Lacey. “Face recognition : role of aging and quality covariates.” 2016. Thesis, Michigan State University. Accessed March 09, 2021.
http://etd.lib.msu.edu/islandora/object/etd:4719.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Best-Rowden, Lacey. “Face recognition : role of aging and quality covariates.” 2016. Web. 09 Mar 2021.
Vancouver:
Best-Rowden L. Face recognition : role of aging and quality covariates. [Internet] [Thesis]. Michigan State University; 2016. [cited 2021 Mar 09].
Available from: http://etd.lib.msu.edu/islandora/object/etd:4719.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Best-Rowden L. Face recognition : role of aging and quality covariates. [Thesis]. Michigan State University; 2016. Available from: http://etd.lib.msu.edu/islandora/object/etd:4719
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Rutgers University
3.
Dhingra, Atul.
Face identification and clustering.
Degree: MS, Computer Science, 2017, Rutgers University
URL: https://rucore.libraries.rutgers.edu/rutgers-lib/53585/
► In this thesis, we study two problems based on clustering algorithms. In the first problem, we study the role of visual attributes using an agglomerative…
(more)
▼ In this thesis, we study two problems based on clustering algorithms. In the first problem, we study the role of visual attributes using an agglomerative clustering algorithm to whittle down the search area where the number of classes is high to improve the performance of clustering. We observe that as we add more attributes, the clustering performance increases overall. In the second problem, we study the role of clustering in aggregating templates in a 1:N open set protocol using multi-shot video as a probe. We observe that by increasing the number of clusters, the performance increases with respect to the baseline and reaches a peak, after which increasing the number of clusters causes the performance to degrade. Experiments are conducted using recently introduced unconstrained IARPA Janus IJB-A, CS2, and CS3
face recognition datasets.
Advisors/Committee Members: Elgammal, Ahmed (chair), Kapadia, Mubbasir (internal member), Boularias, Abdeslam (internal member), Patel, Vishal (outside member).
Subjects/Keywords: Human face recognition (Computer science); Cluster analysis
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APA (6th Edition):
Dhingra, A. (2017). Face identification and clustering. (Masters Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/53585/
Chicago Manual of Style (16th Edition):
Dhingra, Atul. “Face identification and clustering.” 2017. Masters Thesis, Rutgers University. Accessed March 09, 2021.
https://rucore.libraries.rutgers.edu/rutgers-lib/53585/.
MLA Handbook (7th Edition):
Dhingra, Atul. “Face identification and clustering.” 2017. Web. 09 Mar 2021.
Vancouver:
Dhingra A. Face identification and clustering. [Internet] [Masters thesis]. Rutgers University; 2017. [cited 2021 Mar 09].
Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/53585/.
Council of Science Editors:
Dhingra A. Face identification and clustering. [Masters Thesis]. Rutgers University; 2017. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/53585/
University of Texas – Austin
4.
Jahanbin, Sina.
New approaches to automatic 3-D and 2-D 3-D face recognition.
Degree: PhD, Electrical and Computer Engineering, 2011, University of Texas – Austin
URL: http://hdl.handle.net/2152/ETD-UT-2011-05-2990
► Automatic face recognition has attracted the attention of many research institutes, commercial industries, and government agencies in the past few years mainly due to the…
(more)
▼ Automatic
face recognition has attracted the attention of many research institutes, commercial industries, and government agencies in the past few years
mainly due to the emergence of numerous applications, such as surveillance, access control to secure facilities, and airport screening. Almost all of the research on the early days of
face recognition was focused on using 2-D (intensity/portrait) images
of the
face. While several sophisticated 2-D solutions have been proposed, unbiased evaluation studies show that their collective performance remains unsatisfactory, and degrades significantly with variations in lighting condition,
face position,
makeup, or existence of non-neutral facial expressions. Recent developments in
3-D imaging technology has made cheaper, quicker and more reliable acquisition of 3-D facial models a reality. These 3-D facial models contain information about
the anatomical structure of the
face that remains constant under variable lighting conditions, facial makeup, and pose variations. Thus, researchers are considering to utilize 3-D structure of the
face alone or in combination with 2-D information to
alleviate inherent limitations of 2-D images and attain better performance.
Published 3-D
face recognition algorithms have demonstrated promising results confirming the effectiveness of 3-D facial models in dealing with the above mentioned factors contributing to the failure of 2-D
face recognition systems. However,
the majority of these 3-D algorithms are extensions of conventional 2-D approaches,
where intensity images are simply replaced by 3-D models rendered as
range images. These algorithms are not specifically tailored to exploit abundant geometric and anthropometric clues available in 3-D facial models.
In this dissertation we introduce innovative 3-D and 2-D+3-D facial measurements (features) that effectively describe the geometric characteristics of the corresponding faces. Some of the features described in this dissertation, as well as
many features proposed in the literature are defined around or between meaningful facial landmarks (fiducial points). In order to reach our goal of designing an accurate
automatic
face recognition system, we also propose a novel algorithm combining 3-D (range) and 2-D (portrait) Gabor clues to pinpoint a number of points with meaningful anthropometric definitions with significantly better accuracies than those achievable using a single modality alone.
This dissertation is organized as follows. In Chapter 1, various biometric modalities are introduced and the advantages of the facial biometrics over other
modalities are discussed. The discussion in Chapter 1 is continued with introduction
of the
face recognition’s modes of operation followed by some current and potential future applications. The problem statement of this dissertation is also included in this chapter. In Chapter 2, an extensive review of the successful 2-D, 3-D, and 2-D+3-D
face recognition algorithms are provided. Chapter 3 presents the details of our…
Advisors/Committee Members: Bovik, Alan C. (Alan Conrad), 1958- (advisor), Castleman, Kenneth (committee member), Markey, Mia K. (committee member), Vishwanath, Sriram (committee member), Grauman, Kristen (committee member), Fussell, Donald S. (committee member).
Subjects/Keywords: Biometrics; Face recognition; Facial recognition; Human face recognition (Computer science); 3-D imaging; Gabor clues
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APA (6th Edition):
Jahanbin, S. (2011). New approaches to automatic 3-D and 2-D 3-D face recognition. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-05-2990
Chicago Manual of Style (16th Edition):
Jahanbin, Sina. “New approaches to automatic 3-D and 2-D 3-D face recognition.” 2011. Doctoral Dissertation, University of Texas – Austin. Accessed March 09, 2021.
http://hdl.handle.net/2152/ETD-UT-2011-05-2990.
MLA Handbook (7th Edition):
Jahanbin, Sina. “New approaches to automatic 3-D and 2-D 3-D face recognition.” 2011. Web. 09 Mar 2021.
Vancouver:
Jahanbin S. New approaches to automatic 3-D and 2-D 3-D face recognition. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2011. [cited 2021 Mar 09].
Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-2990.
Council of Science Editors:
Jahanbin S. New approaches to automatic 3-D and 2-D 3-D face recognition. [Doctoral Dissertation]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-2990
Michigan State University
5.
Yin, Xi.
Representation learning and image synthesis for deep face recognition.
Degree: 2018, Michigan State University
URL: http://etd.lib.msu.edu/islandora/object/etd:19404
► Thesis Ph. D. Michigan State University. Computer Science 2018
"Face recognition has been advanced a lot in recent years thanks to the development of deep…
(more)
▼ Thesis Ph. D. Michigan State University. Computer Science 2018
"Face recognition has been advanced a lot in recent years thanks to the development of deep neural networks. The large intra-class variations in pose, illumination, and expression are the long-standing challenges. Learning a discriminative representation that is robust to these variations is the key. In the scenarios of profile pose or long-tail training data, image or feature-level data augmentation is needed. This dissertation presents three different methods to solve these problems. First, we explore a multi-task Convolutional Neural Network (CNN) that aims to leverage side tasks to improve representation learning. A pose-directed multi-task CNN is introduced to better handle pose variation. The proposed framework is effective in pose-invariant face recognition. Second, we propose a Face Frontalization-Generative Adversarial Network (FF-GAN) that can generate a frontal face even from an input image with extreme profile pose. FF-GAN handles pose variation from the perspective of image-level data augmentation. Multiple loss functions are proposed to achieve large-pose face frontalization. The proposed approach is evaluated on various tasks including face reconstruction, landmark detection, face frontalization, and face recognition. Third, a feature transfer learning method is presented to solve the problem of insufficient intra-class variation via feature-level data augmentation. A Gaussian prior is assumed across all the regular classes and the variance are transferred from regular classes to long-tail classes. Further, an alternating training regimen is proposed to simultaneously achieve less biased decision boundaries and more discriminative representations. Extensive experiments have demonstrated the effectiveness of the proposed feature transfer framework." – Abstract.
Online resource;
Advisors/Committee Members: Liu, Xiaoming, Jain, Anil K., Ross, Arun, Morris, Daniel D..
Subjects/Keywords: Human face recognition (Computer science); Neural networks (Computer science); Computer science
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APA (6th Edition):
Yin, X. (2018). Representation learning and image synthesis for deep face recognition. (Thesis). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:19404
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Yin, Xi. “Representation learning and image synthesis for deep face recognition.” 2018. Thesis, Michigan State University. Accessed March 09, 2021.
http://etd.lib.msu.edu/islandora/object/etd:19404.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Yin, Xi. “Representation learning and image synthesis for deep face recognition.” 2018. Web. 09 Mar 2021.
Vancouver:
Yin X. Representation learning and image synthesis for deep face recognition. [Internet] [Thesis]. Michigan State University; 2018. [cited 2021 Mar 09].
Available from: http://etd.lib.msu.edu/islandora/object/etd:19404.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Yin X. Representation learning and image synthesis for deep face recognition. [Thesis]. Michigan State University; 2018. Available from: http://etd.lib.msu.edu/islandora/object/etd:19404
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Zambia
6.
Kalunga, Joseph.
Integrating fingerprint biometrics system into the Military Police database: The case of Zambia Army
.
Degree: 2015, University of Zambia
URL: http://dspace.unza.zm:8080/xmlui/handle/123456789/4913
► This research was conducted so as to investigate the design and development of security applications that integrate fingerprint biometrics system into the military police database…
(more)
▼ This research was conducted so as to investigate the design and development of security applications that integrate fingerprint biometrics system into the military police database for the purpose of improving security in Military organisation. The research opposes manual procedures and modernises military police operations in that fingerprint biometrics authentication systems is incorporated into military police database. Biometric system for human identity authentication is more secure and accuracy as compared to the traditional token based system (access control or Identity Card) method of identification. The study was conducted at Zambia Army Headquarters Military Police Unit in Lusaka Zambia. Prior to the system development, data was collected through unstructured interviews, record inspection and observation. Additionally, other requirements were collected through relevant literature review. After data collection, software requirements were specified; analysed, designed and application was developed using visual studio 2010 on DotNet framework 4.0 with C# object oriented programming language. The backend database used was MySQL relational database management system (RDMBS). The research produced a number of key results including the development of biometric security layer that is able to identify and verify the identity of an individual using enrolled fingerprint template. Other results include the ability to capture service personel data, storage, retrieval and dissemination of information. The developed application performance was evaluated by enrolled ten fingerprints and captured related individual personal information. In each three experiments of enrolled ten fingerprints, the biometric module verified all the thirty fingerprints. Therefore, a biometric error allowance rate of 0.001 percent False Acceptance Rate (FAR) and 0.001 percent False Rejection Rate (FRR) was given. In conclusion, we can describe security as layered and can be improved by introducing biometric human identity authentication. Biometric security layer enhances human identity recognition. Human identity recognition is an essential component of security provision in any organisation. Furthermore, the study shows an integration of fingerprint biometric system into traditional database application is possible and can alleviate problems associated with the manual security procedures.
Subjects/Keywords: Biometric Identification;
Pattern Recognition Systems;
Human Face Recognition(Computer Science)
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APA (6th Edition):
Kalunga, J. (2015). Integrating fingerprint biometrics system into the Military Police database: The case of Zambia Army
. (Thesis). University of Zambia. Retrieved from http://dspace.unza.zm:8080/xmlui/handle/123456789/4913
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Kalunga, Joseph. “Integrating fingerprint biometrics system into the Military Police database: The case of Zambia Army
.” 2015. Thesis, University of Zambia. Accessed March 09, 2021.
http://dspace.unza.zm:8080/xmlui/handle/123456789/4913.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Kalunga, Joseph. “Integrating fingerprint biometrics system into the Military Police database: The case of Zambia Army
.” 2015. Web. 09 Mar 2021.
Vancouver:
Kalunga J. Integrating fingerprint biometrics system into the Military Police database: The case of Zambia Army
. [Internet] [Thesis]. University of Zambia; 2015. [cited 2021 Mar 09].
Available from: http://dspace.unza.zm:8080/xmlui/handle/123456789/4913.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Kalunga J. Integrating fingerprint biometrics system into the Military Police database: The case of Zambia Army
. [Thesis]. University of Zambia; 2015. Available from: http://dspace.unza.zm:8080/xmlui/handle/123456789/4913
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Michigan State University
7.
Yin, Bangjie.
Towards interpretable face recognition.
Degree: 2019, Michigan State University
URL: http://etd.lib.msu.edu/islandora/object/etd:47916
► Thesis M.S. Michigan State University. Computer Science 2019
Deep CNNs have been pushing the frontier of visual recognition over past years. Besides recognition accuracy, strong…
(more)
▼ Thesis M.S. Michigan State University. Computer Science 2019
Deep CNNs have been pushing the frontier of visual recognition over past years. Besides recognition accuracy, strong demands in understanding deep CNNs in the research community motivate developments of tools to dissect pre-trained models to visualize how they make predictions. Recent works further push the interpretability in the network learning stage to learn more meaningful representations. In this work, focusing on a specific area of visual recognition, we report our efforts towards interpretable face recognition. We propose a spatial activation diversity loss to learn more structured face representations. By leveraging the structure, we further design a feature activation diversity loss to push the interpretable representations to be discriminative and robust to occlusions. We demonstrate on three face recognition benchmarks that our proposed method is able to achieve the state-of-art face recognition accuracy with easily interpretable face representations.
Description based on online resource;
Advisors/Committee Members: Liu, Xiaoming, Ross, Arun Abraham, Chai, Joyce Yue.
Subjects/Keywords: Human face recognition (Computer science); Computer science; Convolutional neural networks
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APA ·
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APA (6th Edition):
Yin, B. (2019). Towards interpretable face recognition. (Thesis). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:47916
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Yin, Bangjie. “Towards interpretable face recognition.” 2019. Thesis, Michigan State University. Accessed March 09, 2021.
http://etd.lib.msu.edu/islandora/object/etd:47916.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Yin, Bangjie. “Towards interpretable face recognition.” 2019. Web. 09 Mar 2021.
Vancouver:
Yin B. Towards interpretable face recognition. [Internet] [Thesis]. Michigan State University; 2019. [cited 2021 Mar 09].
Available from: http://etd.lib.msu.edu/islandora/object/etd:47916.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Yin B. Towards interpretable face recognition. [Thesis]. Michigan State University; 2019. Available from: http://etd.lib.msu.edu/islandora/object/etd:47916
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Michigan State University
8.
Otto, Charles.
Face search and clustering at scale.
Degree: 2016, Michigan State University
URL: http://etd.lib.msu.edu/islandora/object/etd:4367
► Thesis Ph. D. Michigan State University. Computer Science 2016
There has been a great deal of progress on the problem of unconstrained face recognition in…
(more)
▼ Thesis Ph. D. Michigan State University. Computer Science 2016
There has been a great deal of progress on the problem of unconstrained face recognition in recent years, particularly with the emergence of deep learning methods for generating face representations. Developing robust face representations is not only of great practical interest for classic biometric problems like face verification, but also for emerging large scale face search problems. In both social media, and law-enforcement applications, an extremely large volume of face data is becoming commonplace. One emerging problem related to this high volume of data is to devise methods to search for persons of interest among the billions of shared photos on these websites. Another challenge is to group or cluster large collections of unlabeled face images by identity, for example as a prelude to manual examination of a collection of images in law-enforcement applications.Regarding the face search problem, we propose a face search system which combines a fast search procedure, coupled with a state-of-the-art commercial off the shelf (COTS) matcher, in a cascaded framework. Given a probe face, we first filter the large gallery of photos to find the top-k most similar faces using features learned by a convolutional neural network. The k retrieved candidates are re-ranked by combining similarities based on deep features and those output by the COTS matcher. We evaluate the proposed face search system on a gallery containing 80 million web-downloaded face images. Experimental results demonstrate that while the deep features perform worse than the COTS matcher on a mugshot dataset (93.7% vs. 98.6% [email protected] of 0.01%), fusing the deep features with the COTS matcher improves the overall performance (99.5% [email protected] of 0.01%). This shows that the learned deep features provide complementary information over representations used in state-of-the-art face matchers. On the unconstrained face image benchmarks, the performance of the learned deep features is competitive with reported accuracies. LFW database: 98.20% accuracy under the standard protocol and 88.03% [email protected] of 0.1% under the BLUFR protocol; IJB-A benchmark: 51.0% [email protected] of 0.1% (verification), rank 1 retrieval of 82.2% (closed-set search), 61.5% [email protected] of 1% (open-set search). The proposed face search system offers an excellent trade-off between accuracy and scalability on galleries with millions of images. Additionally, in a face search experiment involving photos of the Tsarnaev brothers, convicted of the Boston Marathon bombing, the proposed cascade face search system could find the younger brother's (Dzhokhar Tsarnaev) photo at rank 1 in 1 second on a 5M gallery and at rank 8 in 7 seconds on an 80M gallery, using a Intel Xeon processor clocked at 3.1 GHz.In terms of clustering, in social media, law enforcement, and other applications the number of unlabeled faces can be of the order of hundreds of million, while the number of identities (clusters) can range from a few thousand to millions. To address the…
Advisors/Committee Members: Jain, Anil K, Ross, Arun, Liu, Xiaoming, Aviyente, Selin.
Subjects/Keywords: Human face recognition (Computer science); Biometry – Data processing; Computer science
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APA (6th Edition):
Otto, C. (2016). Face search and clustering at scale. (Thesis). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:4367
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Otto, Charles. “Face search and clustering at scale.” 2016. Thesis, Michigan State University. Accessed March 09, 2021.
http://etd.lib.msu.edu/islandora/object/etd:4367.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Otto, Charles. “Face search and clustering at scale.” 2016. Web. 09 Mar 2021.
Vancouver:
Otto C. Face search and clustering at scale. [Internet] [Thesis]. Michigan State University; 2016. [cited 2021 Mar 09].
Available from: http://etd.lib.msu.edu/islandora/object/etd:4367.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Otto C. Face search and clustering at scale. [Thesis]. Michigan State University; 2016. Available from: http://etd.lib.msu.edu/islandora/object/etd:4367
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Johannesburg
9.
Jacobs, Divan.
FRAnC : a system for digital facial recognition.
Degree: 2012, University of Johannesburg
URL: http://hdl.handle.net/10210/4798
► M. Comm.
Malicious acts such as fraud and terrorisms are continually becoming a more pressing threat. The need is growing daily for a cheap, non-intrusive…
(more)
▼ M. Comm.
Malicious acts such as fraud and terrorisms are continually becoming a more pressing threat. The need is growing daily for a cheap, non-intrusive technology, that does not make use of specialized equipment, which can identify individuals with or without their knowledge or permission, over the internet or in the public domain. The answer to this problem might be digital facial recognition, the authentication of a person according to the measurements and shape of his facial patterns (nodal points). Thus far the technology has primarily been used by law enforcement. The great strength of facial recognition is that it can scan multiple people in an area quickly, with or without their interaction with the system. The purpose of facial recognition surveillance is to implement it anywhere possible, for example shopping centres, street corners, hotel lobbies or train stations, and to be able to identify any individual finding himself in any of these areas. Also, if a larger system can be implemented, we would be able to track any individual wherever he goes. Through this, any suspicious character can be monitored and tracked if the need arises, ensuring that people can live in a much safer world.
Subjects/Keywords: FRAnC; Facial expression - Computer simulation; Human face recognition (Computer science)
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APA (6th Edition):
Jacobs, D. (2012). FRAnC : a system for digital facial recognition. (Thesis). University of Johannesburg. Retrieved from http://hdl.handle.net/10210/4798
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Jacobs, Divan. “FRAnC : a system for digital facial recognition.” 2012. Thesis, University of Johannesburg. Accessed March 09, 2021.
http://hdl.handle.net/10210/4798.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Jacobs, Divan. “FRAnC : a system for digital facial recognition.” 2012. Web. 09 Mar 2021.
Vancouver:
Jacobs D. FRAnC : a system for digital facial recognition. [Internet] [Thesis]. University of Johannesburg; 2012. [cited 2021 Mar 09].
Available from: http://hdl.handle.net/10210/4798.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Jacobs D. FRAnC : a system for digital facial recognition. [Thesis]. University of Johannesburg; 2012. Available from: http://hdl.handle.net/10210/4798
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Michigan State University
10.
Klum, Scott Jeffrey.
FaceSketchID : a system for facial sketch to mugshot matching.
Degree: 2014, Michigan State University
URL: http://etd.lib.msu.edu/islandora/object/etd:3340
► Thesis M.S. Michigan State University. Computer Science 2014.
Facial composites are widely used by law enforcement agencies to assist in the identification and apprehension of…
(more)
▼ Thesis M.S. Michigan State University. Computer Science 2014.
Facial composites are widely used by law enforcement agencies to assist in the identification and apprehension of suspects involved in criminal activities. These composites, generated from witness descriptions, are posted in public places and in the media with the hope that some viewers will provide tips about the identity of the suspect. This legacy method of identifying suspects is slow, tedious, and may not even lead to the timely apprehension of the suspect. Hence, there is a need for a method that can automatically and efficiently match facial composites to large police mugshot databases. As a result of this requirement, facial composite recognition is an important topic for biometrics researchers. While substantial progress has been made in non-forensic facial composite (or viewed composite) recognition over the past decade, very little work has been done using operational composites relevant to law enforcement agencies. Furthermore, to our knowledge, no facial composite to mugshot matching system has been documented that is readily deployable. The contributions of this thesis include: (i) an exploration of composite recognition use cases involving multiple forms of facial composites, (ii) the FaceSketchID System, a scalable and operationally deployable software system that achieves state-of-the-art matching accuracy on facial composites using two complementary algorithms (holistic and component-based), and (iii) a study of the effects of training data on algorithm performance. Experimental results are presented using a large mugshot gallery that is representative of a law enforcement agency's mugshot database. All results are compared against three state-of-the-art commercial-off-the-shelf (COTS) face recognition systems.
Description based on online resource; title from PDF t.p. (viewed on Sept. 3, 2014)
Advisors/Committee Members: Jain, Anil K, Ross, Arun, Liu, Xiaoming.
Subjects/Keywords: Human face recognition (Computer science); Biometric identification; Identification photographs; Computer science; Facial composite recognition
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APA (6th Edition):
Klum, S. J. (2014). FaceSketchID : a system for facial sketch to mugshot matching. (Thesis). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:3340
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Klum, Scott Jeffrey. “FaceSketchID : a system for facial sketch to mugshot matching.” 2014. Thesis, Michigan State University. Accessed March 09, 2021.
http://etd.lib.msu.edu/islandora/object/etd:3340.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Klum, Scott Jeffrey. “FaceSketchID : a system for facial sketch to mugshot matching.” 2014. Web. 09 Mar 2021.
Vancouver:
Klum SJ. FaceSketchID : a system for facial sketch to mugshot matching. [Internet] [Thesis]. Michigan State University; 2014. [cited 2021 Mar 09].
Available from: http://etd.lib.msu.edu/islandora/object/etd:3340.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Klum SJ. FaceSketchID : a system for facial sketch to mugshot matching. [Thesis]. Michigan State University; 2014. Available from: http://etd.lib.msu.edu/islandora/object/etd:3340
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Ryerson University
11.
Gao, Jun.
Human Face Detection in Color Images.
Degree: 2004, Ryerson University
URL: https://digital.library.ryerson.ca/islandora/object/RULA%3A2339
► Detection of human face has many realistic and important applications such as human and computer interface, face recognition, face image database management, security access control…
(more)
▼ Detection of
human face has many realistic and important applications such as
human and
computer interface,
face recognition,
face image database management, security access control systems and content-based indexing video retrieval systems. In this report a
face detection scheme will be presented. The scheme is designed to operate on color images. In the first stage of algorithm, the skin color regions are detected based on the chrominance information. A color segmentation stage is then employed to make skin color regions to be divided into smaller regions which have homogenous color. Then, we use the iterative luminance segmentation to further separate the detected skin region from other skin-colored objects such as hair, clothes, and wood, based on the high variance of the luminance component in the neighborhood of edges of objects. Post-processing is applied to determine whether skin color regions fit the
face constrains on density of skin, size, shape and symmetry and contain the facial features such as eyes and mouths. Experimental results show that the algorithm is robust and is capable of detecting multiple faces in the presence of a complex background which contains the color similar to the skin tone.
Advisors/Committee Members: Ma, Bobby Ngok-Wah (Thesis advisor), Ryerson University (Degree grantor).
Subjects/Keywords: Human face recognition (Computer science)
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APA (6th Edition):
Gao, J. (2004). Human Face Detection in Color Images. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A2339
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Gao, Jun. “Human Face Detection in Color Images.” 2004. Thesis, Ryerson University. Accessed March 09, 2021.
https://digital.library.ryerson.ca/islandora/object/RULA%3A2339.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Gao, Jun. “Human Face Detection in Color Images.” 2004. Web. 09 Mar 2021.
Vancouver:
Gao J. Human Face Detection in Color Images. [Internet] [Thesis]. Ryerson University; 2004. [cited 2021 Mar 09].
Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A2339.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Gao J. Human Face Detection in Color Images. [Thesis]. Ryerson University; 2004. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A2339
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Hong Kong
12.
贾旭辉.
Face alignment and face
mask reasoning for the images in the wild.
Degree: 2016, University of Hong Kong
URL: http://hdl.handle.net/10722/239963
► Over the past decades, face alignment, a process of localising semantic facial landmarks such as eyebrows and nose tip, has been intensively studied as it…
(more)
▼ Over the past decades, face alignment, a
process of localising semantic facial landmarks such as eyebrows
and nose tip, has been intensively studied as it is an essential
prerequisite for many face analysis tasks, e.g., face animation, 3D
face modelling and face recognition. In recent years, remarkable
progress has been made and some of them even reported
close-to-human accuracy on academic benchmack '300W'. However,
these methods are prone to break down when confronting partial
facial occlusions or large head pose, which occur frequently in
realistic scenarios. In this thesis, we aim to advance face
alignment performance under above mentioned challenges. We also
conduct an empirical study of recent face alignment methods.
First, we will focus on exploring solution for face occlusion
handling. We address the face mask reasoning and facial landmarks
localization in an unified Structured Decision Forests framework.
We first assign a portion of the face dataset with face masks,
i.e., for each face image we give each pixel a label to indicate
whether it belongs to the face or not. Then we incorporate such
additional information of dense pixel labelling into training the
Structured Classification-Regression Decision Forest. The
classification nodes aim at decreasing the variance of the pixel
labels of the patches by using our proposed structured criterion
while the regression nodes aim at decreasing the variance of the
displacements between the patches and the facial landmarks. The
proposed framework allows us to predict the face mask and facial
landmarks locations jointly.
In the second part of the thesis,
we present a novel reflective method to estimate 2D-3D face shape
across large pose. We include the knowledge that a face is a 3D
object into the learning pipeline, and formulate face alignment as
a 3D Morphable Model (3DMM) fitting problem, where the camera
projection matrix and 3D shape parameters are learned by an
extended cascaded pose regression framework. In order to improve
algorithm robustness in difficult poses, we introduce a reflective
invariant metric for failure alert. We investigate the relation
between reflective variance and face misalignment error, and find
there is strong correlation between them. This finding is exploited
to provide feedback to our algorithm. For samples predicted as
failure, we restart the algorithm with better initialisations based
on explicit head pose estimation, which enhances the possibility of
convergence.
Finally, we carry out a rigorous evaluation of
recent face alignment methods: 1) we proposes a new evaluation
metric for face alignment on a set of images, i.e., area under
error distribution curve within a threshold, AUCa, as the
traditional evaluation measure (mean error) is very sensitive to
big alignment error. 2) we extend the 300W database with more
practical face detections to make fair comparison possible. 3) we
carry out face alignment sensitivity analysis w.r.t. face detection
on both synthetic and real data, using both off-the-shelf and
re-retrained…
Subjects/Keywords: Human
face recognition (Computer science)
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Manager
APA (6th Edition):
贾旭辉. (2016). Face alignment and face
mask reasoning for the images in the wild. (Thesis). University of Hong Kong. Retrieved from http://hdl.handle.net/10722/239963
Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
贾旭辉. “Face alignment and face
mask reasoning for the images in the wild.” 2016. Thesis, University of Hong Kong. Accessed March 09, 2021.
http://hdl.handle.net/10722/239963.
Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
贾旭辉. “Face alignment and face
mask reasoning for the images in the wild.” 2016. Web. 09 Mar 2021.
Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Vancouver:
贾旭辉. Face alignment and face
mask reasoning for the images in the wild. [Internet] [Thesis]. University of Hong Kong; 2016. [cited 2021 Mar 09].
Available from: http://hdl.handle.net/10722/239963.
Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
贾旭辉. Face alignment and face
mask reasoning for the images in the wild. [Thesis]. University of Hong Kong; 2016. Available from: http://hdl.handle.net/10722/239963
Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation
Macquarie University
13.
Damavandinejadmonfared, Sepehr.
Improved PCA-based techniques for face and finger-vein recognition systems.
Degree: 2017, Macquarie University
URL: http://hdl.handle.net/1959.14/1261382
► Theoretical thesis.
Bibliography: pages 285-295.
1 Introduction – 2 Background – 3 Databases – 4 Kernel Principal Component Analysis – 5 Kernel Entropy Component Analysis…
(more)
▼ Theoretical thesis.
Bibliography: pages 285-295.
1 Introduction – 2 Background – 3 Databases – 4 Kernel Principal Component Analysis – 5 Kernel Entropy Component Analysis in Face Recognition – 6 Kernel Entropy Component Analysis in Finger-Vein Recognition – 7 Proposed New Dimensionality-Reduction Method – 8 New Image Transformation Method (FDGDA) – 9 Feature Dependent Kernel Entropy Component Analysis – 10 Finger-Vein Extraction – 11 Overall Conclusion and Future Work.
Biometrics refers to metrics related to human characteristics and biometric technologies use physical or behavioural characteristics of people to identify and recognize an individual. With the ever increasing growth in cybercrimes, biometric technologies have become increasingly important in this digital information age. The focus of this thesisis on the design ans application of new techniques for image based biometrics recognition systems using faces and finger veins. Principal Component Analysis (PCA) is a way of identifying patterns in data, and expressing the data in such a way as to highlight their similarities and differences. The PCA technique plays an important role in feature extraction and dimensionality reduction. In this thesis, we propose a variety of extensions of PCA technique using kernel and entropy based extensions. We have proposed new algorithms to face and finger vein recognition systems and show that these extensions can yield better results in terms of accuracy and performance.
1 online resource (xxvi, 295 pages) illustrations (some colour)
Advisors/Committee Members: Macquarie University. Department of Computing.
Subjects/Keywords: Biometrics; Principal components analysis; Human face recognition (Computer science)
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APA (6th Edition):
Damavandinejadmonfared, S. (2017). Improved PCA-based techniques for face and finger-vein recognition systems. (Doctoral Dissertation). Macquarie University. Retrieved from http://hdl.handle.net/1959.14/1261382
Chicago Manual of Style (16th Edition):
Damavandinejadmonfared, Sepehr. “Improved PCA-based techniques for face and finger-vein recognition systems.” 2017. Doctoral Dissertation, Macquarie University. Accessed March 09, 2021.
http://hdl.handle.net/1959.14/1261382.
MLA Handbook (7th Edition):
Damavandinejadmonfared, Sepehr. “Improved PCA-based techniques for face and finger-vein recognition systems.” 2017. Web. 09 Mar 2021.
Vancouver:
Damavandinejadmonfared S. Improved PCA-based techniques for face and finger-vein recognition systems. [Internet] [Doctoral dissertation]. Macquarie University; 2017. [cited 2021 Mar 09].
Available from: http://hdl.handle.net/1959.14/1261382.
Council of Science Editors:
Damavandinejadmonfared S. Improved PCA-based techniques for face and finger-vein recognition systems. [Doctoral Dissertation]. Macquarie University; 2017. Available from: http://hdl.handle.net/1959.14/1261382
Rutgers University
14.
Zhong, Lin, 1985-.
Single image deblurring with or without face prior and its applications.
Degree: PhD, Computer Science, 2015, Rutgers University
URL: https://rucore.libraries.rutgers.edu/rutgers-lib/47622/
► The motion blur is one of the most difficult challenges in photography, which is generated from the relative motion between the sensor and the scene…
(more)
▼ The motion blur is one of the most difficult challenges in photography, which is generated from the relative motion between the sensor and the scene during exposure time. These blur artifacts degrade the visual experience, and the performance of various applications, such as, object detection, facial analysis. Therefore, it is significant to remove the blur and restore sharp and clean images. Our work focuses on the general single image deblurring, and face image deblurring with face prior. State-of-the-art single image deblurring techniques are sensitive to image noise. Even a small amount of noise, which is inevitable in low-light conditions, can degrade the quality of blur kernel estimation dramatically. We propose a new method for handling noise in blind image deconvolution based on new theoretical and practical insights. Based on the observations on directional filter, our method applies a series of directional filters at different orientations to the input image, and estimates an accurate Radon transform of the blur kernel from each filtered image. Finally, we reconstruct the blur kernel using inverse Radon transform. Experimental results on synthetic and real data show that our algorithm achieves higher quality results than previous approaches on blurry and noisy images. The human face is one of the most essential focuses in numerous applications. Although significant progress has been made in the image deblurring area, few of them can obtain promising results on blurry face images. Many state-of-the-art single image deblurring approaches estimate the blur kernel based on analyzing the edge profiles of the input image. However, the detection of strong edges is very difficult on human faces, since the human faces do not contain as much texture as natural images. We propose to utilize the global face structure information to help with the strong or salient edge detection. Our method outperforms the existing methods in extensive evaluations on synthetic and real face images. Facial expression is a significant application on sharp and restored face images. To improve the general facial expression recognition performance, we present a new idea to analyze facial expression by exploring the common and specific information among different expressions.
Advisors/Committee Members: Metaxas, Dimitris N. (chair), Elgammal, Ahmed (internal member), Bekris, Kostas (internal member), Samaras, Dimitris (outside member).
Subjects/Keywords: Image processing – Digital techniques; Human face recognition (Computer science)
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APA (6th Edition):
Zhong, Lin, 1. (2015). Single image deblurring with or without face prior and its applications. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/47622/
Chicago Manual of Style (16th Edition):
Zhong, Lin, 1985-. “Single image deblurring with or without face prior and its applications.” 2015. Doctoral Dissertation, Rutgers University. Accessed March 09, 2021.
https://rucore.libraries.rutgers.edu/rutgers-lib/47622/.
MLA Handbook (7th Edition):
Zhong, Lin, 1985-. “Single image deblurring with or without face prior and its applications.” 2015. Web. 09 Mar 2021.
Vancouver:
Zhong, Lin 1. Single image deblurring with or without face prior and its applications. [Internet] [Doctoral dissertation]. Rutgers University; 2015. [cited 2021 Mar 09].
Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/47622/.
Council of Science Editors:
Zhong, Lin 1. Single image deblurring with or without face prior and its applications. [Doctoral Dissertation]. Rutgers University; 2015. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/47622/
Drexel University
15.
Zhang, Zhongchuan.
3D Pedestrian Tracking and Virtual Reconstruction of Ceramic Vessels Using Geometric and Color Cues.
Degree: 2016, Drexel University
URL: http://hdl.handle.net/1860/idea:6720
► Object tracking using cameras has many applications ranging from monitoring children and the elderly, to behavior analysis, entertainment, and homeland security. This thesis concentrates on…
(more)
▼ Object tracking using cameras has many applications ranging from monitoring children and the elderly, to behavior analysis, entertainment, and homeland security. This thesis concentrates on the problem of tracking person(s) of interest in crowded scenes (e.g., airports, train stations, malls, etc.), rendering their locations in time and space along with high quality close-up images of the person for recognition. The tracking is achieved using a combination of overhead cameras for 3D tracking and a network of pan-tilt-zoom (PTZ) cameras to obtain close-up frontal face images. Based on projective geometry, the overhead cameras track people using salient and easily computable feature points such as head points. When the obtained head point is not accurate enough, the color information of the head tops across subsequent frames is integrated to detect and track people. To capture the best frontal face images of a target across time, a PTZ camera scheduling is proposed, where the 'best' PTZ camera is selected based on the capture quality (as close as possible to frontal view) and handoff success (response time needed by the newly selected camera to move from current to desired state) probabilities. The experiments show the 3D tracking errors are very small (less than 5 cm with 14 people crowding an area of around 4 m2) and the frontal face images are captured effectively with most of them centering in the frames. Computational archaeology is becoming a success story of applying computational tools in the reconstruction of vessels obtained from digs, freeing the expert from hours of intensive labor in manually stitching shards into meaningful vessels. In this thesis, we concentrate on the use of geometric and color information of the fragments for 3D virtual reconstruction of broken ceramic vessels. Generic models generated by the experts as a rendition of what the original vessel may have looked like are also utilized. The generic models need not to be identical to the original vessel, but are within a geometric transformation of it in most of its parts. The markings on the 3D surfaces of fragments and generic models are extracted based on their color cues. Ceramic fragments are then aligned against the corresponding generic models based on the geometric relation between the extracted markings. The alignments yield sub-scanner resolution fitting errors.
Ph.D., Electrical Engineering – Drexel University, 2016
Advisors/Committee Members: Cohen, Fernand S., College of Engineering.
Subjects/Keywords: Electrical engineering; Human face recognition (Computer science); Image processing; Optical pattern recognition; Face perception – Computer simulation
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APA (6th Edition):
Zhang, Z. (2016). 3D Pedestrian Tracking and Virtual Reconstruction of Ceramic Vessels Using Geometric and Color Cues. (Thesis). Drexel University. Retrieved from http://hdl.handle.net/1860/idea:6720
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Zhang, Zhongchuan. “3D Pedestrian Tracking and Virtual Reconstruction of Ceramic Vessels Using Geometric and Color Cues.” 2016. Thesis, Drexel University. Accessed March 09, 2021.
http://hdl.handle.net/1860/idea:6720.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Zhang, Zhongchuan. “3D Pedestrian Tracking and Virtual Reconstruction of Ceramic Vessels Using Geometric and Color Cues.” 2016. Web. 09 Mar 2021.
Vancouver:
Zhang Z. 3D Pedestrian Tracking and Virtual Reconstruction of Ceramic Vessels Using Geometric and Color Cues. [Internet] [Thesis]. Drexel University; 2016. [cited 2021 Mar 09].
Available from: http://hdl.handle.net/1860/idea:6720.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Zhang Z. 3D Pedestrian Tracking and Virtual Reconstruction of Ceramic Vessels Using Geometric and Color Cues. [Thesis]. Drexel University; 2016. Available from: http://hdl.handle.net/1860/idea:6720
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Johannesburg
16.
Van der Schyff, Marco.
Bandwidth efficient virtual classroom.
Degree: 2009, University of Johannesburg
URL: http://hdl.handle.net/10210/2186
► M.Ing.
Virtual classrooms and online-learning are growing in popularity, but there are still some factors limiting the potential. Limited bandwidth for audio and video, the…
(more)
▼ M.Ing.
Virtual classrooms and online-learning are growing in popularity, but there are still some factors limiting the potential. Limited bandwidth for audio and video, the resultant transmission quality and limited feedback during virtual classroom sessions are some of the problems that need to be addressed. This thesis presents information on the design and implementation of various components of a virtual classroom system for researching methods of student feedback with a focus on bandwidth conservation. A facial feature technique is implemented and used within the system to determine the viability of using facial feature extraction to provide and prioritise feedback from students to teacher while conserving bandwidth. This allows a teacher to estimate the comprehension level of the class and individual students based on student images. A server determines which student terminal transmits its images to the teacher using data obtained from the facial feature extraction process. Feedback is improved as teachers adapt to class circumstances using experience gained in traditional classrooms. Feedback is also less reliant on intentional student participation. New page-turner, page suggestion and class activity components are presented as possible methods for improving student feedback. In particular, the effect of virtual classroom system parameters on feedback delays and bandwidth usage is investigated. In general, delays are increased as bandwidth requirements decrease. The system shows promise for future use in research on facial feature extraction, student feedback and bandwidth conservation in virtual classrooms.
Subjects/Keywords: Image processing; Human face recognition (Computer science); Distance education; Computer-assisted instruction
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APA (6th Edition):
Van der Schyff, M. (2009). Bandwidth efficient virtual classroom. (Thesis). University of Johannesburg. Retrieved from http://hdl.handle.net/10210/2186
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Van der Schyff, Marco. “Bandwidth efficient virtual classroom.” 2009. Thesis, University of Johannesburg. Accessed March 09, 2021.
http://hdl.handle.net/10210/2186.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Van der Schyff, Marco. “Bandwidth efficient virtual classroom.” 2009. Web. 09 Mar 2021.
Vancouver:
Van der Schyff M. Bandwidth efficient virtual classroom. [Internet] [Thesis]. University of Johannesburg; 2009. [cited 2021 Mar 09].
Available from: http://hdl.handle.net/10210/2186.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Van der Schyff M. Bandwidth efficient virtual classroom. [Thesis]. University of Johannesburg; 2009. Available from: http://hdl.handle.net/10210/2186
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of North Texas
17.
Toure, Zikra.
Human-Machine Interface Using Facial Gesture Recognition.
Degree: 2017, University of North Texas
URL: https://digital.library.unt.edu/ark:/67531/metadc1062841/
► This Master thesis proposes a human-computer interface for individual with limited hand movements that incorporate the use of facial gesture as a means of communication.…
(more)
▼ This Master thesis proposes a
human-
computer interface for individual with limited hand movements that incorporate the use of facial gesture as a means of communication. The system recognizes faces and extracts facial gestures to map them into Morse code that would be translated in English in real time. The system is implemented on a MACBOOK
computer using Python software, OpenCV library, and Dlib library. The system is tested by 6 students. Five of the testers were not familiar with Morse code. They performed the experiments in an average of 90 seconds. One of the tester was familiar with Morse code and performed the experiment in 53 seconds. It is concluded that errors occurred due to variations in features of the testers, lighting conditions, and unfamiliarity with the system. Implementing an auto correction and auto prediction system will decrease typing time considerably and make the system more robust.
Advisors/Committee Members: Namuduri, Kamesh, Li, Xinrong, Varanasi, Murali.
Subjects/Keywords: Facial; Gestures; Recognition; Human face recognition (Computer science); Gesture.; Communication devices for people with disabilities.; Human-computer interaction.
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Hong Kong University of Science and Technology
18.
Jiang, Feijun.
Hierarchical integration of stereo analysis, face detection and head pose estimation.
Degree: 2012, Hong Kong University of Science and Technology
URL: http://repository.ust.hk/ir/Record/1783.1-7740
;
https://doi.org/10.14711/thesis-b1197970
;
http://repository.ust.hk/ir/bitstream/1783.1-7740/1/th_redirect.html
► In building computer vision systems, the most popular architecture is a flat parallel structure where tasks are considered independently and each task is solved by…
(more)
▼ In building computer vision systems, the most popular architecture is a flat parallel structure where tasks are considered independently and each task is solved by cascading a feature extraction stage with a machine learning classifier. In this work, we propose an efficient hierarchical multi-task vision system that integrates stereo and texture cues to accomplish automatic multi-view face detection and head pose estimation. This hierarchical structure is inspired by the hierarchical signal processing in the primate visual cortex, where different perceptual tasks share the same early visual representations and more complex features are extracted from simpler features. It appears that the visual cortex of different kinds of animals use normalized Gabor features as early visual representations. We demonstrate that the same bank of normalized four-orientation Gabor features, improves face detection, disparity detection and head pose estimation. The multi-view face detector based on discrete normalized Gabor features has state-of-the-art performance. Integrating disparity detectors based on disparity energy features extracted from the normalized Gabor features improves both the efficiency and the accuracy of the face detector. Disparity information enables us to filter out 90% of image locations as being less likely to contain faces. Performance is improved because the filtering rejects 32% of the false detections made by a similar monocular detector with the same recall rate. The same normalized Gabor features are also a robust representation for pose estimation. In particular, in the normalized Gabor feature space faces with similar poses are closer than in other feature spaces. Pose estimation with these features using nonlinear regression based on the Weighted K Nearest-Neighbor (WKNN) performs better than previously reported approaches on the same database under more complex illumination conditions. Combining multi-view face detector and pose estimator, we build up an efficient automatic head pose estimator. We further improve the efficiency of pose estimation using local linear regression method. This method combines multi-class classification with linear regression. This method generates similar estimation accuracy as WKNN estimator, but the computation time is just 5% of that of WKNN estimator. This system is very efficient. Our implementation on a PC equipped with an i5 2.66GHz CPU and a Nvidia GTX 465 graphic card takes only 42.0ms to detect faces on a 640 x 480 stereo image pair, and only an additional 0.13ms to estimate the pose of each detected face.
Subjects/Keywords: Stereoscopic views – Data processing
; Human face recognition (Computer science)
; Computer vision
; Optical pattern recognition
; Image processing – Digital techniques
; Computer graphics
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APA (6th Edition):
Jiang, F. (2012). Hierarchical integration of stereo analysis, face detection and head pose estimation. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-7740 ; https://doi.org/10.14711/thesis-b1197970 ; http://repository.ust.hk/ir/bitstream/1783.1-7740/1/th_redirect.html
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Jiang, Feijun. “Hierarchical integration of stereo analysis, face detection and head pose estimation.” 2012. Thesis, Hong Kong University of Science and Technology. Accessed March 09, 2021.
http://repository.ust.hk/ir/Record/1783.1-7740 ; https://doi.org/10.14711/thesis-b1197970 ; http://repository.ust.hk/ir/bitstream/1783.1-7740/1/th_redirect.html.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Jiang, Feijun. “Hierarchical integration of stereo analysis, face detection and head pose estimation.” 2012. Web. 09 Mar 2021.
Vancouver:
Jiang F. Hierarchical integration of stereo analysis, face detection and head pose estimation. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2012. [cited 2021 Mar 09].
Available from: http://repository.ust.hk/ir/Record/1783.1-7740 ; https://doi.org/10.14711/thesis-b1197970 ; http://repository.ust.hk/ir/bitstream/1783.1-7740/1/th_redirect.html.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Jiang F. Hierarchical integration of stereo analysis, face detection and head pose estimation. [Thesis]. Hong Kong University of Science and Technology; 2012. Available from: http://repository.ust.hk/ir/Record/1783.1-7740 ; https://doi.org/10.14711/thesis-b1197970 ; http://repository.ust.hk/ir/bitstream/1783.1-7740/1/th_redirect.html
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Michigan State University
19.
Hsu, Rein-Lien.
Face detection and modeling for recognition.
Degree: PhD, Department of Computer Science & Engineering, 2002, Michigan State University
URL: http://etd.lib.msu.edu/islandora/object/etd:31342
Subjects/Keywords: Human face recognition (Computer science); Biometry
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APA ·
Chicago ·
MLA ·
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APA (6th Edition):
Hsu, R. (2002). Face detection and modeling for recognition. (Doctoral Dissertation). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:31342
Chicago Manual of Style (16th Edition):
Hsu, Rein-Lien. “Face detection and modeling for recognition.” 2002. Doctoral Dissertation, Michigan State University. Accessed March 09, 2021.
http://etd.lib.msu.edu/islandora/object/etd:31342.
MLA Handbook (7th Edition):
Hsu, Rein-Lien. “Face detection and modeling for recognition.” 2002. Web. 09 Mar 2021.
Vancouver:
Hsu R. Face detection and modeling for recognition. [Internet] [Doctoral dissertation]. Michigan State University; 2002. [cited 2021 Mar 09].
Available from: http://etd.lib.msu.edu/islandora/object/etd:31342.
Council of Science Editors:
Hsu R. Face detection and modeling for recognition. [Doctoral Dissertation]. Michigan State University; 2002. Available from: http://etd.lib.msu.edu/islandora/object/etd:31342
20.
Tello-Sánchez, Fernando-Antonio.
Adaptación y comparación de dos metodologías de reconocimiento facial aplicados a la detección de somnolencia en conductores.
Degree: Ingeniero de sistemas, Ingeniería de sistemas, 2018, Universidad de Lima
URL: http://doi.org/10.26439/ulima.tesis/10242
► Esta tesis busca realizar una comparación entre dos metodologías de reconocimiento de expresiones faciales: Viola-Jones y Regression Based Facial Landmark Detection, los cuales han sido…
(more)
▼ Esta tesis busca realizar una comparación entre dos metodologías de reconocimiento de
expresiones faciales: Viola-Jones y Regression Based Facial Landmark Detection, los
cuales han sido adaptados para la detección de somnolencia, para conocer cuál de ellas
es la óptima y se adecua mejor a las condiciones variables de: oclusión, rotación de
rostro e iluminación.
Advisors/Committee Members: Gutiérrez-Cárdenas, Juan (advisor).
Subjects/Keywords: Reconocimiento facial (informática); Conductores de automóviles; Human face recognition (Computer science); Automobile drivers; Pendiente / Pendiente
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APA ·
Chicago ·
MLA ·
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CSE |
Export
to Zotero / EndNote / Reference
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APA (6th Edition):
Tello-Sánchez, F. (2018). Adaptación y comparación de dos metodologías de reconocimiento facial aplicados a la detección de somnolencia en conductores. (Thesis). Universidad de Lima. Retrieved from http://doi.org/10.26439/ulima.tesis/10242
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Tello-Sánchez, Fernando-Antonio. “Adaptación y comparación de dos metodologías de reconocimiento facial aplicados a la detección de somnolencia en conductores.” 2018. Thesis, Universidad de Lima. Accessed March 09, 2021.
http://doi.org/10.26439/ulima.tesis/10242.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Tello-Sánchez, Fernando-Antonio. “Adaptación y comparación de dos metodologías de reconocimiento facial aplicados a la detección de somnolencia en conductores.” 2018. Web. 09 Mar 2021.
Vancouver:
Tello-Sánchez F. Adaptación y comparación de dos metodologías de reconocimiento facial aplicados a la detección de somnolencia en conductores. [Internet] [Thesis]. Universidad de Lima; 2018. [cited 2021 Mar 09].
Available from: http://doi.org/10.26439/ulima.tesis/10242.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Tello-Sánchez F. Adaptación y comparación de dos metodologías de reconocimiento facial aplicados a la detección de somnolencia en conductores. [Thesis]. Universidad de Lima; 2018. Available from: http://doi.org/10.26439/ulima.tesis/10242
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Michigan State University
21.
Jourabloo, Amin.
Designing convolutional neural networks for face alignment and anti-spoofing.
Degree: 2019, Michigan State University
URL: http://etd.lib.msu.edu/islandora/object/etd:47821
► Thesis Ph. D. Michigan State University. Computer Science 2019
"Face alignment is the process of detecting a set of fiducial points on a face image,…
(more)
▼ Thesis Ph. D. Michigan State University. Computer Science 2019
"Face alignment is the process of detecting a set of fiducial points on a face image, such as mouth corners, nose tip, etc. Face alignment is a key module in the pipeline of most facial analysis tasks, normally after face detection and before subsequent feature extraction and classification. As a result, improving the face alignment accuracy is helpful for numerous facial analysis tasks. Recently, face alignment works are popular in top vision venues and achieve a lot of attention. In spite of the fruitful prior work and ongoing progress of face alignment, pose-invariant face alignment is still challenging. To address the inherent challenges associated with this problem, we propose pose-invariant face alignment by fitting a dense 3DMM, and integrating estimation of 3D shape and 2D facial landmarks from a single face image in a single CNN. We introduce a new layer, called visualization layer, which is differentiable and allows backpropagation of an error from a later block to an earlier one. Another application of facial analysis is the face anti-spoofing, which has recently achieved a lot of attention. While face recognition systems serve as a verification portal for various devices (i.e., phone unlock, access control, and transportation security), attackers present face spoofs (i.e., presentation attacks, PA) to the system and attempt to be authenticated as the genuine user. We present our proposed deep models for face anti-spoofing that use the supervision from both the spatial and temporal auxiliary information, for the purpose of robustly detecting face PA from a face video." – Page ii.
Description based on online resource;
Advisors/Committee Members: Liu, Xiaoming, Ross, Arun, Morris, Daniel, Boddeti, Vishnu.
Subjects/Keywords: Human face recognition (Computer science); False personation – Prevention – Technological innovations; Neural networks (Computer science); Computer science
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APA ·
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Export
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APA (6th Edition):
Jourabloo, A. (2019). Designing convolutional neural networks for face alignment and anti-spoofing. (Thesis). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:47821
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Jourabloo, Amin. “Designing convolutional neural networks for face alignment and anti-spoofing.” 2019. Thesis, Michigan State University. Accessed March 09, 2021.
http://etd.lib.msu.edu/islandora/object/etd:47821.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Jourabloo, Amin. “Designing convolutional neural networks for face alignment and anti-spoofing.” 2019. Web. 09 Mar 2021.
Vancouver:
Jourabloo A. Designing convolutional neural networks for face alignment and anti-spoofing. [Internet] [Thesis]. Michigan State University; 2019. [cited 2021 Mar 09].
Available from: http://etd.lib.msu.edu/islandora/object/etd:47821.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Jourabloo A. Designing convolutional neural networks for face alignment and anti-spoofing. [Thesis]. Michigan State University; 2019. Available from: http://etd.lib.msu.edu/islandora/object/etd:47821
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Florida Atlantic University
22.
James, Jhanon.
Face Processing Using Mobile Devices.
Degree: MS, 2016, Florida Atlantic University
URL: http://purl.flvc.org/fau/fd/FA00004770
;
(URL)
http://purl.flvc.org/fau/fd/FA00004770
► Summary: Image Processing and Computer Vision solutions have become commodities for software developers, thanks to the growing availability of Application Program- ming Interfaces (APIs) that…
(more)
▼ Summary: Image Processing and Computer Vision solutions have become commodities
for software developers, thanks to the growing availability of Application Program-
ming Interfaces (APIs) that encapsulate rich functionality, powered by advanced al-
gorithms. To understand and create an e cient method to process faces in images
by computers, one must understand how the human visual system processes them.
Face processing by computers has been an active research area for about 50
years now. Face detection has become a commodity and is now incorporated into
simple devices such as digital cameras and smartphones.
An iOS app was implemented in Objective-C using Microsoft Cognitive Ser-
vices APIs, as a tool for human vision and face processing research. Experimental
work on image compression, upside-down orientation, the Thatcher e ect, negative
inversion, high frequency, facial artifacts, caricatures and image degradation were
completed on the Radboud and 10k US Adult Faces Databases along with other
images.
2016
Degree granted:
Collection: FAU
Advisors/Committee Members: Marques, Oge (Thesis advisor), Florida Atlantic University (Degree grantor), College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science.
Subjects/Keywords: Image processing – Digital techniques.; Mobile communication systems.; Mobile computing.; Artificial intelligence.; Human face recognition (Computer science); Computer vision.; Optical pattern recognition.
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APA ·
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MLA ·
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Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
James, J. (2016). Face Processing Using Mobile Devices. (Masters Thesis). Florida Atlantic University. Retrieved from http://purl.flvc.org/fau/fd/FA00004770 ; (URL) http://purl.flvc.org/fau/fd/FA00004770
Chicago Manual of Style (16th Edition):
James, Jhanon. “Face Processing Using Mobile Devices.” 2016. Masters Thesis, Florida Atlantic University. Accessed March 09, 2021.
http://purl.flvc.org/fau/fd/FA00004770 ; (URL) http://purl.flvc.org/fau/fd/FA00004770.
MLA Handbook (7th Edition):
James, Jhanon. “Face Processing Using Mobile Devices.” 2016. Web. 09 Mar 2021.
Vancouver:
James J. Face Processing Using Mobile Devices. [Internet] [Masters thesis]. Florida Atlantic University; 2016. [cited 2021 Mar 09].
Available from: http://purl.flvc.org/fau/fd/FA00004770 ; (URL) http://purl.flvc.org/fau/fd/FA00004770.
Council of Science Editors:
James J. Face Processing Using Mobile Devices. [Masters Thesis]. Florida Atlantic University; 2016. Available from: http://purl.flvc.org/fau/fd/FA00004770 ; (URL) http://purl.flvc.org/fau/fd/FA00004770
Ryerson University
23.
Tie, Yun.
Human emotional state recognition using 3D facial expression features.
Degree: 2011, Ryerson University
URL: https://digital.library.ryerson.ca/islandora/object/RULA%3A1011
► In recent years there has been a growing interest in improving all aspects of the interaction between human and computers. Emotion recognition is a new…
(more)
▼ In recent years there has been a growing interest in improving all aspects of the interaction between
human and computers. Emotion
recognition is a new research direction in
human-
computer interaction (HCI) which is based on affective computing that is expected to significantly improve the quality of HCI system and communications. Most existing works address this problem using 2D features, but they are sensitive to head pose, clutter, and variations in lighting conditions. In light of such problems, two 3D visual feature based approaches are presented in this dissertation. First, we present a
recognition method based on the Gabor library for real 3D visual features extraction and an improved kernel canonical correlation analysis (IKCCA) algorithm for emotion classification. Second, to reduce the computation cost and provide a more general approach, we propose using a fiducial points' controlled 3D
face model to recognize
human emotion from video sequences. An Elastic body spine (EBS) technique is applied for deformation feature extraction and a discriminative Isomap (D-Isomap) based classification is used for the final decision. The most significant contributions of this work are detecting and tracking fiducial points automatically from video sequences to construct a generic 3D
face model, and the introduction of EBS deformation features for emotion
recognition. The experimental results show the robustness and effectiveness of the proposed methods.
Advisors/Committee Members: Guan, Ling (Thesis advisor), Ryerson University (Degree grantor).
Subjects/Keywords: Face perception – Data processing; Emotions – Data processing; Human face recognition (Computer science); Three-dimensional display systems; Image processing – Digital techniques
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APA (6th Edition):
Tie, Y. (2011). Human emotional state recognition using 3D facial expression features. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A1011
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Tie, Yun. “Human emotional state recognition using 3D facial expression features.” 2011. Thesis, Ryerson University. Accessed March 09, 2021.
https://digital.library.ryerson.ca/islandora/object/RULA%3A1011.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Tie, Yun. “Human emotional state recognition using 3D facial expression features.” 2011. Web. 09 Mar 2021.
Vancouver:
Tie Y. Human emotional state recognition using 3D facial expression features. [Internet] [Thesis]. Ryerson University; 2011. [cited 2021 Mar 09].
Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A1011.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Tie Y. Human emotional state recognition using 3D facial expression features. [Thesis]. Ryerson University; 2011. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A1011
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Texas State University – San Marcos
24.
Haque, Md Inzamam Ul.
A Facial Expression Recognition Application Development Using Deep Convolutional Neural Network For Children With Autism Spectrum Disorder To Help Identify Human Emotions.
Degree: MS, Engineering, 2019, Texas State University – San Marcos
URL: https://digital.library.txstate.edu/handle/10877/8457
► In this thesis, a novel idea is presented, which is to teach young children with Autism Spectrum Disorder (ASD) to recognize human facial expressions through…
(more)
▼ In this thesis, a novel idea is presented, which is to teach young children with Autism Spectrum Disorder (ASD) to recognize
human facial expressions through the help of
computer vision and image processing. Universally, there are seven facial expressions categories: angry, disgust, happy, sad, fear, surprised and neutral. To recognize all these facial expressions and to predict the current mood of a person is a difficult task for a child. For a child with ASD, this problem presents itself in a more complex manner due to the nature of the disorder. The main goal of the thesis was to develop a deep Convolutional Neural Network (DCNN) for facial expression
recognition, which can help young children with ASD to recognize facial expressions, using mobile devices. Previously, different neural network models and classifiers have been presented to achieve state of the art accuracy in this sector. Separately, different studies have been performed in studying the ability and performance of children with ASD for recognizing facial expressions. In this thesis, additional features have been added to the DCNN model such that it can correctly classify facial expressions in different lighting conditions and from different viewpoints as the model is trained to do so. Upon developing the DCNN model, an iOS app has been developed implementing this deep learning model as a byproduct and as a medium to use this model in clinical trials for children with autism as a medium of enhancing their communication abilities. The implementation of this proposed idea started with finding datasets containing images of faces with different expressions from different angles. Further datasets were produced from the original dataset with images of different contrast and brightness with the help of image processing. The performance of the DCNN model was evaluated using these datasets. Once an optimal accuracy is achieved with good generalizability, an app suitable for iOS platform was developed for running both the DCNN model and image processing algorithms. The function of the app is to open the camera of the device, detect a
face, classify the facial expression, and show the expression with an emoticon on the screen. As a product of this work, the app can be used by speech-language pathologies, teacher, care-takers, and parents as a technological tool when working with children with ASD. The design of the model and application is targeted to children with ASD to recognize and identify facial expressions in real-time to practice social skills during everyday social interaction.
Advisors/Committee Members: Valles, Damian (advisor), Resendiz, Maria (committee member), Koutitas, George (committee member).
Subjects/Keywords: Deep convolutional neural network; Autism spectrum disorder; Deep learning; Human face recognition (Computer science); Face – Identification; Autism
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APA ·
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MLA ·
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Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Haque, M. I. U. (2019). A Facial Expression Recognition Application Development Using Deep Convolutional Neural Network For Children With Autism Spectrum Disorder To Help Identify Human Emotions. (Masters Thesis). Texas State University – San Marcos. Retrieved from https://digital.library.txstate.edu/handle/10877/8457
Chicago Manual of Style (16th Edition):
Haque, Md Inzamam Ul. “A Facial Expression Recognition Application Development Using Deep Convolutional Neural Network For Children With Autism Spectrum Disorder To Help Identify Human Emotions.” 2019. Masters Thesis, Texas State University – San Marcos. Accessed March 09, 2021.
https://digital.library.txstate.edu/handle/10877/8457.
MLA Handbook (7th Edition):
Haque, Md Inzamam Ul. “A Facial Expression Recognition Application Development Using Deep Convolutional Neural Network For Children With Autism Spectrum Disorder To Help Identify Human Emotions.” 2019. Web. 09 Mar 2021.
Vancouver:
Haque MIU. A Facial Expression Recognition Application Development Using Deep Convolutional Neural Network For Children With Autism Spectrum Disorder To Help Identify Human Emotions. [Internet] [Masters thesis]. Texas State University – San Marcos; 2019. [cited 2021 Mar 09].
Available from: https://digital.library.txstate.edu/handle/10877/8457.
Council of Science Editors:
Haque MIU. A Facial Expression Recognition Application Development Using Deep Convolutional Neural Network For Children With Autism Spectrum Disorder To Help Identify Human Emotions. [Masters Thesis]. Texas State University – San Marcos; 2019. Available from: https://digital.library.txstate.edu/handle/10877/8457
University of Johannesburg
25.
Van der Haar, Dustin Terence.
Face recognition-based authentication and monitoring in video telecommunication systems.
Degree: 2012, University of Johannesburg
URL: http://hdl.handle.net/10210/5024
► M.Sc. (Computer Science)
A video conference is an interactive meeting between two or more locations, facilitated by simultaneous two-way video and audio transmissions. People in…
(more)
▼ M.Sc. (Computer Science)
A video conference is an interactive meeting between two or more locations, facilitated by simultaneous two-way video and audio transmissions. People in a video conference, also known as participants, join these video conferences for business and recreational purposes. In a typical video conference, we should properly identify and authenticate every participant in the video conference, if information discussed during the video conference is confidential. This prevents unauthorized and unwanted people from being part of the conference and exposing any confidential information during the video conference. Present existing video conferencing systems however, have problems in this area, resulting in some risks. These risks relate precisely to the lack of facilities to properly identify and authenticate participants, making it possible for unwanted/unauthorised participants to join the conference or masquerade as another participant. It is especially a problem, when facilitators or organisers are the only participants that know the authorised participants, or participants allowed in a video conference. In this dissertation, we review the risks that are present in video conferencing, and create a security system, (called BioVid) that mitigates the identification and authentication risks in video conferences. BioVid uses a Speeded-Up Robust Features or SURF-based face recognition approach, to identify and authenticate any participant in a video conference. BioVid continuously monitors the participants to check if masquerading has occurred and when it does detect an unauthorised participant, it informs the Service Provider. The Service Provider can then deal with the problem by either kicking the participant or asking the other participants to vote the unauthorised participant out of the video conference.
Subjects/Keywords: Video telecommunication systems; Information security; Human face rocognition (Computer science); Videoconferencing security; Speeded-Up Robust Features face recognition; SURF-based face recognition; BioVid security system
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APA (6th Edition):
Van der Haar, D. T. (2012). Face recognition-based authentication and monitoring in video telecommunication systems. (Thesis). University of Johannesburg. Retrieved from http://hdl.handle.net/10210/5024
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Van der Haar, Dustin Terence. “Face recognition-based authentication and monitoring in video telecommunication systems.” 2012. Thesis, University of Johannesburg. Accessed March 09, 2021.
http://hdl.handle.net/10210/5024.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Van der Haar, Dustin Terence. “Face recognition-based authentication and monitoring in video telecommunication systems.” 2012. Web. 09 Mar 2021.
Vancouver:
Van der Haar DT. Face recognition-based authentication and monitoring in video telecommunication systems. [Internet] [Thesis]. University of Johannesburg; 2012. [cited 2021 Mar 09].
Available from: http://hdl.handle.net/10210/5024.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Van der Haar DT. Face recognition-based authentication and monitoring in video telecommunication systems. [Thesis]. University of Johannesburg; 2012. Available from: http://hdl.handle.net/10210/5024
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of California – Riverside
26.
Malur Srinivasan, Ramya.
Investigating the Role of Saliency for Face Recognition.
Degree: Electrical Engineering, 2015, University of California – Riverside
URL: http://www.escholarship.org/uc/item/9xz4d9fp
► There has been enormous interest in developing automatic face recognition techniques. Be it for government use such as law enforcement, voter identification, surveillance and immigration,…
(more)
▼ There has been enormous interest in developing automatic face recognition techniques. Be it for government use such as law enforcement, voter identification, surveillance and immigration, or for commercial use such as gaming industry, face tagging on internet, e-commerce, healthcare and banking, a large number of real world applications utilize face recognition. A variety of challenges are associated with a face recognition system. While modeling variations in facial expressions, age, pose and illumination is necessary in many applications, certain specific applications may also involve comparing face images taken over different media such as a facial sketch to a photo.Selecting visually salient, i.e., highly informative and discriminative features, is critical to every face recognition task. Often, such features are selected based on expert knowledge and/or learned from training data. The choice of these features is largely governed by the application. While there has been extensive work on saliency-based feature selection strategies for object/activity recognition in general, the role of saliency in the context of face recognition is relatively unexplored. The primary focus of this work is to investigate the role of saliency for face recognition. We discuss three face recognition applications illustrating the role of saliency in each of these problem domains. In the first, we propose a framework for identifying subjects (sitters) in ancient portraits belonging to the Renaissance era. Apart from the typical face recognition challenges, recognition in art works come with the additional challenges of having to deal with limited training data and the need to model variability in artistic renditions. In this direction, we propose a framework that is capable of learning salient characteristics of individual artists and subsequently perform identification based on statistical hypothesis testing.We next discuss a related face recognition application of comparing an artistic sketch with a photograph. Here, we propose an unsupervised face recognition scheme based on computing saliency maps constructed from region covariance matrices of low level visual features. We also discuss the utility of such features for face recognition in unconstrained environments (often referred to as `recognition in the wild') and subject to artificial distortions such as Gaussian blur and white noise. We conduct experiments on the Chinese University of Hong Kong Photo-Sketch database and the Quality Labeled Faces in the Wild (QLFW) to demonstrate the advantages of the proposed method. Taking cue from the scenario of face recognition in art works wherein we have limited authenticated portraits, we next investigate the general problem of face recognition from very limited training data. This problem is relevant to many forensic science applications. We show that by learning salient features characteristic of a style such as a facial expression, pose, etc., one can obtain better recognition accuracies between face image pairs than with the case…
Subjects/Keywords: Electrical engineering; Computer science; Face Recognition; Saliency
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APA (6th Edition):
Malur Srinivasan, R. (2015). Investigating the Role of Saliency for Face Recognition. (Thesis). University of California – Riverside. Retrieved from http://www.escholarship.org/uc/item/9xz4d9fp
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Malur Srinivasan, Ramya. “Investigating the Role of Saliency for Face Recognition.” 2015. Thesis, University of California – Riverside. Accessed March 09, 2021.
http://www.escholarship.org/uc/item/9xz4d9fp.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Malur Srinivasan, Ramya. “Investigating the Role of Saliency for Face Recognition.” 2015. Web. 09 Mar 2021.
Vancouver:
Malur Srinivasan R. Investigating the Role of Saliency for Face Recognition. [Internet] [Thesis]. University of California – Riverside; 2015. [cited 2021 Mar 09].
Available from: http://www.escholarship.org/uc/item/9xz4d9fp.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Malur Srinivasan R. Investigating the Role of Saliency for Face Recognition. [Thesis]. University of California – Riverside; 2015. Available from: http://www.escholarship.org/uc/item/9xz4d9fp
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Indian Institute of Science
27.
Anoop, K R.
Multiview Face Detection And Free Form Face Recognition For Surveillance.
Degree: MSc Engg, Faculty of Engineering, 2014, Indian Institute of Science
URL: http://etd.iisc.ac.in/handle/2005/2401
► The problem of face detection and recognition within a given database has become one of the important problems in computer vision. A simple approach for…
(more)
▼ The problem of
face detection and
recognition within a given database has become one of the important problems in
computer vision. A simple approach for
Face Detection in video is to run a learning based
face detector every frame. But such an approach is computationally expensive and completely ignores the temporal continuity present in videos. Moreover the search space can be reduced by utilizing visual cues extracted based on the relevant task at hand(top down approach). Once detection is done next step is to perform a
face recognition based on the available database. But the faces detected from
face detect or output is neither aligned nor well cropped and is prone to scale change. We call such faces as free form faces. But the current existing algorithms on
face recognition assume faces to be properly aligned and cropped, and having the same scale as the faces in the database, which is highly constrained.
In this thesis, we propose an integrated detect-track framework for Multiview
face detection in videos. We overcome the limitations of the frame based approaches, by utilizing the temporal continuity present in videos and also incorporating the top down information of the task. We model the problem based on the concept from Experiential sampling [2]. This consists of determining certain key positions which are relevant to the task(
face detection). These key positions are referred to as attention samples and Multiview
face detection is performed only at these locations. These statistical samples are estimated based on the visual cues, past experience and the temporal continuity and is modeled as a Bayesian filtering problem, which is solved using Particle Filters. In order to detect all views we use a tracker integrated with the detector and come out with a novel track termination algorithm using the concepts from Track Before Detect(TBD)[26].
Such an approach is computationally efficient and also results in lower false positive rate. We provide experiments showing the efficiency of the integrated detect-track approach over the multiview
face detector approach without a tracker.
For free form
face recognition we propose to use the concept of Principal Geodesic Analysis(PGA) of the Covariance descriptors obtained from Gabor filters. This is similar to Principal Component Analysis in Euclidean spaces (Covariance descriptors lie on a Riemannian manifold). Such a descriptor is robust to alignment and scaling problems and also are of lower dimensions. We also employ sparse modeling technique for
Face recognition task using these Covariance descriptor which are dimensionally reduced by transforming them on to a tangent space, which we call PGA feature. Further, we improve upon the
recognition results of linear sparse modeling, by non-linear mapping of the PGA features by employing “Kernel Trick” for these sparse models. We show that the Kernelized sparse models using the PGA features are indeed very efficient for free form
face recognition by testing on two standard databases namely AR and YaleB database.
Advisors/Committee Members: Ramakrishnan, K R (advisor).
Subjects/Keywords: Multiview Face Detection; Face Recognition; Multiview Face Detection - Detect-Track; Free Form Face Recognition; Video Surveillance; Video - Face Detection; Face Perception; Video - Face Recognition; Computer Science
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APA (6th Edition):
Anoop, K. R. (2014). Multiview Face Detection And Free Form Face Recognition For Surveillance. (Masters Thesis). Indian Institute of Science. Retrieved from http://etd.iisc.ac.in/handle/2005/2401
Chicago Manual of Style (16th Edition):
Anoop, K R. “Multiview Face Detection And Free Form Face Recognition For Surveillance.” 2014. Masters Thesis, Indian Institute of Science. Accessed March 09, 2021.
http://etd.iisc.ac.in/handle/2005/2401.
MLA Handbook (7th Edition):
Anoop, K R. “Multiview Face Detection And Free Form Face Recognition For Surveillance.” 2014. Web. 09 Mar 2021.
Vancouver:
Anoop KR. Multiview Face Detection And Free Form Face Recognition For Surveillance. [Internet] [Masters thesis]. Indian Institute of Science; 2014. [cited 2021 Mar 09].
Available from: http://etd.iisc.ac.in/handle/2005/2401.
Council of Science Editors:
Anoop KR. Multiview Face Detection And Free Form Face Recognition For Surveillance. [Masters Thesis]. Indian Institute of Science; 2014. Available from: http://etd.iisc.ac.in/handle/2005/2401
Ryerson University
28.
Tang, Kevin.
Protected multimodal emotion recognition.
Degree: 2015, Ryerson University
URL: https://digital.library.ryerson.ca/islandora/object/RULA%3A3765
► In this thesis, we propose Protected Multimodal Emotion recognition (PMM-ER), an emotion recognition approach that includes security features against the growing rate of cyber-attacks on…
(more)
▼ In this thesis, we propose Protected Multimodal Emotion
recognition (PMM-ER), an emotion
recognition approach that includes security features against the growing rate of cyber-attacks on various databases, including emotion databases. The analysis on the frequently used encryption algorithms has led to the modified encryption algorithm proposed in this work. The system is able to recognize 7 different emotions, i.e. happiness, sadness, surprise, fear, disgust and anger, as well as a neutral emotion state, based on 2D video frames, 3D vertices, and audio wave information. Several well-known features are employed, including the HSV colour feature, iterative closest point (ICP) and Mel-frequency cepstral coefficients (MFCCs). We also propose a novel approach to feature fusion including both decision- and feature-level fusion, and some well-known classification and feature extraction algorithms such as principle component analysis (PCA), linear discernment analysis (LDA) and canonical correlation analysis (CCA) are compared in this study.
Advisors/Committee Members: Ryerson University (Degree grantor).
Subjects/Keywords: Emotions – Mathematical models; Emotions – Measurement – Computer programs; Emotions – Data processing; Human face recognition (Computer science); Pattern recognition systems; Human-computer interaction; Biometric identification – Technological innovations; Three-dimensional imaging; Computer security
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APA ·
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to Zotero / EndNote / Reference
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APA (6th Edition):
Tang, K. (2015). Protected multimodal emotion recognition. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A3765
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Tang, Kevin. “Protected multimodal emotion recognition.” 2015. Thesis, Ryerson University. Accessed March 09, 2021.
https://digital.library.ryerson.ca/islandora/object/RULA%3A3765.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Tang, Kevin. “Protected multimodal emotion recognition.” 2015. Web. 09 Mar 2021.
Vancouver:
Tang K. Protected multimodal emotion recognition. [Internet] [Thesis]. Ryerson University; 2015. [cited 2021 Mar 09].
Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A3765.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Tang K. Protected multimodal emotion recognition. [Thesis]. Ryerson University; 2015. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A3765
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Technology, Sydney
29.
Du, R.
Single and multiple instance learning for visual categorisation.
Degree: 2013, University of Technology, Sydney
URL: http://hdl.handle.net/10453/23495
► Nowadays, huge amounts of visual data, e.g., videos and images, have become widely accessible. Therefore, intelligently categorizing the large and growing collections of data for…
(more)
▼ Nowadays, huge amounts of visual data, e.g., videos and images, have become widely accessible. Therefore, intelligently categorizing the large and growing collections of data for access convenience has been a central goal for modern computer vision research. In this thesis, we describe several newly-developed approaches for visual categorization upon the single and multiple instance learning cases.
In single-instance learning (SIL), each of the training instances has been labeled. Here, we focus on a challenging task of facial expressions recognition where manually labeling each training instance, i.e., face video, is handy. To get the distinct features of expressions, we propose a novel feature representation, Histogram Variances Face (HVF), which integrates dynamic expression information into a static image being invariant to illumination and in-plane rotation. Through HVFs, the facial expression recognition can be cast as a facial recognition problem. We have applied our approach on the well-known Cohn-Kanade AU-Coded Facial Expression database, and then those extracted HVFs are classified by using facial recognition technology, i.e., Eigenfaces and Support Vector Machines (SVMs). The recognition accuracy is very encouraging. We further propose an extension of HVFs, Hexagonal Histogram Variance Faces (HHVFs), which applies HVFs on a hexagonal structure. Comparing to HVFs, HHVFs not only greatly reduce the computation costs but also improve the recognition accuracy.
In multiple-instance learning (MIL), the training instances are divided into groups and the instances in the same group share only one label. MIL arises from many applications where individually labeling training instances is expensive. In this case, we propose a novel algorithm, multiple-instance learning with a supervised kernel density estimation (MIL-SKDE), to tackle the labeling ambiguity. Our algorithm extends the twin technologies, kernel density estimation (SKDE) and mean shift, to their supervised versions in which the labels of data points will affect the mode seeking. We apply MIL-SKDE in several applications of visual categorization, e.g., image and object categorization, and our algorithm performs superiorly comparing to other state-of-the-art methods. Furthermore, to address the complexity issue of MIL-SKDE, we propose MIL-SS (MIL with speed-up SKDE) to speed up the training process. Experiments shows that it has comparable performances to MIL-SKDE but is much more efficient in training stage.
Finally, we apply MIL-SS in a “bag-of-words” (BoW) system to learn the visual codebook for object categorization on a more comprehensive dataset. Our system consists of four steps: codebook generation, feature coding, feature pooling and classification. Unlike conventional BoW methods that learn codebook from the whole image areas, our method can learn codebook just from the areas of target objects, which significantly improves classification accuracy.
Subjects/Keywords: Human face recognition.; Facial pattern recognition.; Computer vision research.
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APA ·
Chicago ·
MLA ·
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CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Du, R. (2013). Single and multiple instance learning for visual categorisation. (Thesis). University of Technology, Sydney. Retrieved from http://hdl.handle.net/10453/23495
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Du, R. “Single and multiple instance learning for visual categorisation.” 2013. Thesis, University of Technology, Sydney. Accessed March 09, 2021.
http://hdl.handle.net/10453/23495.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Du, R. “Single and multiple instance learning for visual categorisation.” 2013. Web. 09 Mar 2021.
Vancouver:
Du R. Single and multiple instance learning for visual categorisation. [Internet] [Thesis]. University of Technology, Sydney; 2013. [cited 2021 Mar 09].
Available from: http://hdl.handle.net/10453/23495.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Du R. Single and multiple instance learning for visual categorisation. [Thesis]. University of Technology, Sydney; 2013. Available from: http://hdl.handle.net/10453/23495
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
30.
Bozed, Kenz Amhmed.
Detection of facial expressions based on time dependent morphological features.
Degree: PhD, 2011, University of Bedfordshire
URL: http://hdl.handle.net/10547/145618
► Facial expression detection by a machine is a valuable topic for Human Computer Interaction and has been a study issue in the behavioural science for…
(more)
▼ Facial expression detection by a machine is a valuable topic for Human Computer Interaction and has been a study issue in the behavioural science for some time. Recently, significant progress has been achieved in machine analysis of facial expressions but there are still some interestes to study the area in order to extend its applications. This work investigates the theoretical concepts behind facial expressions and leads to the proposal of new algorithms in face detection and facial feature localisation, design and construction of a prototype system to test these algorithms. The overall goals and motivation of this work is to introduce vision based techniques able to detect and recognise the facial expressions. In this context, a facial expression prototype system is developed that accomplishes facial segmentation (i.e. face detection, facial features localisation), facial features extraction and features classification. To detect a face, a new simplified algorithm is developed to detect and locate its presence from the fackground by exploiting skin colour properties which are then used to distinguish between face and non-face regions. This allows facial parts to be extracted from a face using elliptical and box regions whose geometrical relationships are then utilised to determine the positions of the eyes and mouth through morphological operations. The mean and standard deviations of segmented facial parts are then computed and used as features for the face. For images belonging to the same class, thses features are applied to the K-mean algorithm to compute the controid point of each class expression. This is repeated for images in the same expression class. The Euclidean distance is computed between each feature point and its cluster centre in the same expression class. This determines how close a facial expression is to a particular class and can be used as observation vectors for a Hidden Markov Model (HMM) classifier. Thus, an HMM is built to evaluate an expression of a subject as belonging to one of the six expression classes, which are Joy, Anger, Surprise, Sadness, Fear and Disgust by an HMM using distance features. To evaluate the proposed classifier, experiments are conducted on new subjects using 100 video clips that contained a mixture of expressions. The average successful detection rate of 95.6% is measured from a total of 9142 frames contained in the video clips. The proposed prototype system processes facial features parts and presents improved results of facial expressions detection rather than using whole facial features as proposed by previous authors. This work has resulted in four contributions: the Ellipse Box Face Detection Algorithm (EBFDA), Facial Features Distance Algorithm (FFDA), Facial features extraction process, and Facial features classification. These were tested and verified using the prototype system.
Subjects/Keywords: 006.4; facial features recognition; facial expressions; human-computer interaction; face recognition
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APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Bozed, K. A. (2011). Detection of facial expressions based on time dependent morphological features. (Doctoral Dissertation). University of Bedfordshire. Retrieved from http://hdl.handle.net/10547/145618
Chicago Manual of Style (16th Edition):
Bozed, Kenz Amhmed. “Detection of facial expressions based on time dependent morphological features.” 2011. Doctoral Dissertation, University of Bedfordshire. Accessed March 09, 2021.
http://hdl.handle.net/10547/145618.
MLA Handbook (7th Edition):
Bozed, Kenz Amhmed. “Detection of facial expressions based on time dependent morphological features.” 2011. Web. 09 Mar 2021.
Vancouver:
Bozed KA. Detection of facial expressions based on time dependent morphological features. [Internet] [Doctoral dissertation]. University of Bedfordshire; 2011. [cited 2021 Mar 09].
Available from: http://hdl.handle.net/10547/145618.
Council of Science Editors:
Bozed KA. Detection of facial expressions based on time dependent morphological features. [Doctoral Dissertation]. University of Bedfordshire; 2011. Available from: http://hdl.handle.net/10547/145618
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Open Access Theses and Dissertations