subject:(Object tracking)

Linköping University

1. Nyström, Axel. Evaluation of Multiple Object Tracking in Surveillance Video.

Degree: Computer Vision, 2019, Linköping University

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157666

► Multiple object tracking is the process of assigning unique and consistent identities to objects throughout a video sequence. A popular approach to multiple object… (more)

Subjects/Keywords: Multiple Object Tracking; Tracking-by-Detection; Object Detection; Object Tracking; Deep Learning; Signal Processing; Signalbehandling

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APA (6^th Edition):

Nyström, A. (2019). Evaluation of Multiple Object Tracking in Surveillance Video. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157666

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Nyström, Axel. “Evaluation of Multiple Object Tracking in Surveillance Video.” 2019. Thesis, Linköping University. Accessed December 09, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157666.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Nyström, Axel. “Evaluation of Multiple Object Tracking in Surveillance Video.” 2019. Web. 09 Dec 2019.

Vancouver:

Nyström A. Evaluation of Multiple Object Tracking in Surveillance Video. [Internet] [Thesis]. Linköping University; 2019. [cited 2019 Dec 09]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157666.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Nyström A. Evaluation of Multiple Object Tracking in Surveillance Video. [Thesis]. Linköping University; 2019. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157666

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Rochester Institute of Technology

2. Buck, Ashley. Multiple Identity Tracking and Motion Extrapolation.

Degree: MS, Psychology (CLA), 2019, Rochester Institute of Technology

URL: https://scholarworks.rit.edu/theses/10145

► Multiple Identity Tracking (MIT) is a paradigm in which individuals track the location and identity of moving objects in the environment. The first goal… (more)

Subjects/Keywords: Motion extrapolation; Multiple identity tracking; Multiple object tracking; Object displacement; Object tracking

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APA (6^th Edition):

Buck, A. (2019). Multiple Identity Tracking and Motion Extrapolation. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/10145

Chicago Manual of Style (16^th Edition):

Buck, Ashley. “Multiple Identity Tracking and Motion Extrapolation.” 2019. Masters Thesis, Rochester Institute of Technology. Accessed December 09, 2019. https://scholarworks.rit.edu/theses/10145.

MLA Handbook (7^th Edition):

Buck, Ashley. “Multiple Identity Tracking and Motion Extrapolation.” 2019. Web. 09 Dec 2019.

Vancouver:

Buck A. Multiple Identity Tracking and Motion Extrapolation. [Internet] [Masters thesis]. Rochester Institute of Technology; 2019. [cited 2019 Dec 09]. Available from: https://scholarworks.rit.edu/theses/10145.

Council of Science Editors:

Buck A. Multiple Identity Tracking and Motion Extrapolation. [Masters Thesis]. Rochester Institute of Technology; 2019. Available from: https://scholarworks.rit.edu/theses/10145

Australian National University

3. Zhu, Gao. An Exploration into Model-Free Online Visual Object Tracking .

Degree: 2016, Australian National University

URL: http://hdl.handle.net/1885/112128

► This thesis presents a thorough investigation of model-free visual object tracking, a fundamental computer vision task that is essential for practical video analytics applications. Given… (more)

▼ This thesis presents a thorough investigation of model-free visual object tracking, a fundamental computer vision task that is essential for practical video analytics applications. Given the states of the object in the rst frame, e.g., the position and size of the target, the computational methods developed and advanced in this thesis aim at determining target states in consecutive video frames automatically. In contrast to the tracking schemes that depend strictly on specic object detectors, model-free tracking provides conveniently flexible and competently general solutions where object representations are initiated in the first frame and adapted in an online manner at each frame. We first articulate our motivations and intuitions in Chapter 1, formulate model-free online visual tracking, illustrate outcomes on two representative object tracking applications; drone control and sports video broadcasting analysis, and elaborate other relevant problems. In Chapter 2, we review various tracking methodologies employed by state-ofthe-art trackers and further review related background knowledge, including several important dataset benchmarks and workshop challenges, which are widely used for evaluating the performance of trackers, as well as commonly applied evaluation protocols in this chapter. In Chapter 3 through Chapter 6, we then explore the model-free online visual tracking problem in four different dimensions: 1) learning a more discriminative classier with a two-layer classication hierarchy and background contextual clusters; 2) overcoming the limit of conventionally used local-search scheme with a global object tracking framework based on instance-specic object proposals; 3) tracking object affine motion with a Structured Support Vector Machine (SSVM) framework incorporated with motion manifold structure; 4) an efficient multiple object model-free online tracking approach based on a shared pool of object proposals. Lastly, as a conclusion and future work outlook, we highlight and summarize the contribution of this thesis and discuss several promising research directions in Chapter 7, based on latest work and their drawbacks of current state-of-the-art trackers.

Subjects/Keywords: object tracking; model-free; online

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APA (6^th Edition):

Zhu, G. (2016). An Exploration into Model-Free Online Visual Object Tracking . (Thesis). Australian National University. Retrieved from http://hdl.handle.net/1885/112128

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Zhu, Gao. “An Exploration into Model-Free Online Visual Object Tracking .” 2016. Thesis, Australian National University. Accessed December 09, 2019. http://hdl.handle.net/1885/112128.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Zhu, Gao. “An Exploration into Model-Free Online Visual Object Tracking .” 2016. Web. 09 Dec 2019.

Vancouver:

Zhu G. An Exploration into Model-Free Online Visual Object Tracking . [Internet] [Thesis]. Australian National University; 2016. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/1885/112128.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zhu G. An Exploration into Model-Free Online Visual Object Tracking . [Thesis]. Australian National University; 2016. Available from: http://hdl.handle.net/1885/112128

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Southern California

4. Dinh, Thang Ba. Persistent object tracking in unconstrained environments.

Degree: PhD, Computer Science, 2011, University of Southern California

URL: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/673435/rec/5000

► Visual tracking has been an active and fruitful topic in computer vision these days since it is a very important component for a wide range… (more)

▼ Visual tracking has been an active and fruitful topic in computer vision these days since it is a very important component for a wide range of practical systems such as surveillance, robotics, multimedia information retrieval, human-computer interaction. In this dissertation, our goal is to track an object of interest persistently with respect to the appearance changes caused by illumination variations, viewpoint changes, and out-of-plane rotation. An object also may leave the field of view then reappear. In order to track and reacquire an unknown object with limited labeling data, we propose to learn these changes online and build a model that encodes all appearance variations while tracking. To address visual object tracking as a semi-supervised problem, we propose a co-trained cascade particle filter framework to label incoming data continuously and online update hybrid models generatively and discriminatively. Each of the layers in the cascade contains one or more either generative or discriminative appearance models. The cascade manner of organizing the particle filter enables the efficient evaluation of multiple appearance models with different computational costs, thus, improve the speed of the tracker. This proposed framework provides not only the ability to adapt to object appearance changes but also an object-specific detection capability which allows to reacquire an object after total occlusion. ❧ One of the vital issues of visual tracking is drifting where partial occlusion is a critical factor. We propose to use the co-training framework of generative and discriminative models to detect where the occlusion occurs. Precise occlusion segmentation is then performed using Meanshift. After that, the occluded parts are recovered using the learned information from the models. We also propose to use local feature movement voting scheme to serve as a referee when there is a strong disagreement between the two models. Finally, each of the models will be updated using the new non-occluded information. ❧ Another major factor causing tracking failure is the emergence of regions having similar appearance as the target. It is even more challenging when the target leaves the field of view (FoV) leading the tracker to follow another similar object, and not reacquire the right target when it reappears. We propose a method to address this problem by exploiting the context on-the-fly in two terms: Distracters and Supporters. Both of them are automatically explored using a sequential randomized forest, an online template-based appearance model, and local features. Distracters are regions, which have similar appearance as the target and consistently co-occur with a high confidence score. The tracker must keep tracking these distracters to avoid drifting. Supporters, on the other hand, are local key-points around the target with consistent co-occurrence and motion correlation in a short time. They play an important role in verifying the genuine target. ❧ To demonstrate the feasibility of our proposed framework, we apply it… Advisors/Committee Members: Medioni, Gerard (Committee Chair), Morency, Louis-Philippe (Committee Member), Narayanan, Shrikanth S. (Committee Member).

Subjects/Keywords: object tracking; visual tracking; object detection; PTZ tracking; pan-tilt-zoom camera; face tracking; real-time tracking; surveillance; active tracking

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APA (6^th Edition):

Dinh, T. B. (2011). Persistent object tracking in unconstrained environments. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/673435/rec/5000

Chicago Manual of Style (16^th Edition):

Dinh, Thang Ba. “Persistent object tracking in unconstrained environments.” 2011. Doctoral Dissertation, University of Southern California. Accessed December 09, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/673435/rec/5000.

MLA Handbook (7^th Edition):

Dinh, Thang Ba. “Persistent object tracking in unconstrained environments.” 2011. Web. 09 Dec 2019.

Vancouver:

Dinh TB. Persistent object tracking in unconstrained environments. [Internet] [Doctoral dissertation]. University of Southern California; 2011. [cited 2019 Dec 09]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/673435/rec/5000.

Council of Science Editors:

Dinh TB. Persistent object tracking in unconstrained environments. [Doctoral Dissertation]. University of Southern California; 2011. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/673435/rec/5000

Queens University

5. Bentley, Ian. Track Persistence in Wireless Sensor Networks .

Degree: Computing, 2010, Queens University

URL: http://hdl.handle.net/1974/6033

► In this thesis we directly consider an object tracking problem for wireless sensor networks (WSNs), called track persistence. Track persistence temporally extends the problem of… (more)

Subjects/Keywords: WSN; Wireless Sensor Networks; Target Tracking; Object Tracking; Track Persistence; Single object tracking; Track; Persistence

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APA (6^th Edition):

Bentley, I. (2010). Track Persistence in Wireless Sensor Networks . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/6033

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Bentley, Ian. “Track Persistence in Wireless Sensor Networks .” 2010. Thesis, Queens University. Accessed December 09, 2019. http://hdl.handle.net/1974/6033.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Bentley, Ian. “Track Persistence in Wireless Sensor Networks .” 2010. Web. 09 Dec 2019.

Vancouver:

Bentley I. Track Persistence in Wireless Sensor Networks . [Internet] [Thesis]. Queens University; 2010. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/1974/6033.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bentley I. Track Persistence in Wireless Sensor Networks . [Thesis]. Queens University; 2010. Available from: http://hdl.handle.net/1974/6033

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Universiteit Utrecht

6. Deiman, J. Automatic Tracking, Segmentation, Removal and Replay of Traffic in Panoramic 360-Degree Videos for Virtual Reality.

Degree: 2016, Universiteit Utrecht

URL: http://dspace.library.uu.nl:8080/handle/1874/334268

► The Netherlands Aerospace Centre (NLR) has a virtual reality setup which allows users to experience an airplane fly-over with realistically simulated sound. They want to… (more)

Subjects/Keywords: object detection; object tracking; object segmentation; inpainting; virtual reality; panoramic video

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Deiman, J. (2016). Automatic Tracking, Segmentation, Removal and Replay of Traffic in Panoramic 360-Degree Videos for Virtual Reality. (Masters Thesis). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/334268

Chicago Manual of Style (16^th Edition):

Deiman, J. “Automatic Tracking, Segmentation, Removal and Replay of Traffic in Panoramic 360-Degree Videos for Virtual Reality.” 2016. Masters Thesis, Universiteit Utrecht. Accessed December 09, 2019. http://dspace.library.uu.nl:8080/handle/1874/334268.

MLA Handbook (7^th Edition):

Deiman, J. “Automatic Tracking, Segmentation, Removal and Replay of Traffic in Panoramic 360-Degree Videos for Virtual Reality.” 2016. Web. 09 Dec 2019.

Vancouver:

Deiman J. Automatic Tracking, Segmentation, Removal and Replay of Traffic in Panoramic 360-Degree Videos for Virtual Reality. [Internet] [Masters thesis]. Universiteit Utrecht; 2016. [cited 2019 Dec 09]. Available from: http://dspace.library.uu.nl:8080/handle/1874/334268.

Council of Science Editors:

Deiman J. Automatic Tracking, Segmentation, Removal and Replay of Traffic in Panoramic 360-Degree Videos for Virtual Reality. [Masters Thesis]. Universiteit Utrecht; 2016. Available from: http://dspace.library.uu.nl:8080/handle/1874/334268

University of Washington

7. Huang, Tsung-Wei. Automatic Video Analysis for Electronic Monitoring of Fishery Activities.

Degree: PhD, 2019, University of Washington

URL: http://hdl.handle.net/1773/44796

► Recently, automated imagery analysis techniques have drawn increasing attention in fishery science and industry. Compared to traditional human observing and monitoring, automated imagery analysis techniques… (more)

▼ Recently, automated imagery analysis techniques have drawn increasing attention in fishery science and industry. Compared to traditional human observing and monitoring, automated imagery analysis techniques are more scalable and deployable, and thus have been widely used in recent years for numerous fishery survey tasks, such as abundance estimation, species identification or length measurement. One of the emerging fishery survey tasks which can effectively take advantage of the automated imagery analysis is the electronic monitoring (EM) for fishery activities. The goal of EM is to monitor the fish catching on fishing vessels, either for scientific survey or legal purpose. For example, a fishing vessel may not retain fish catching if the length is below some threshold or exceeding the quota of the vessel for certain species. Therefore, accurate tracking, counting, measurement and species classification is required in the EM systems. There are, however, challenges from the inspected subjects and operation environments. Deformable objects, noise from the wild sea surface, and dynamic background, make conventional tracking, segmentation and classification methods unreliable. To overcome the challenges encountered in the electronic monitoring, this dissertation presents an online 3D tracking and segmentation system for stereo video based monitoring of rail fish catching on wild sea surface. Based on the result of a pre-trained image object (fish) detector, a Kalman filtering-based tracking system overcomes the issues of low detection scores of deformed objects and unreliable bounding boxes by rescoring multiple object proposals using spatial information in 3D. A clustering-and-scoring strategy is then applied on the depth map, so that a plane classification method can effectively segment the objects from the dynamic background without any prior modeling. The object segmentation is further refined using fully connected conditional random fields based on color and geometric features. With the segmentation results, we can measure the 3D lengths of objects and update the positions of bounding boxes to help tracking. Experimental results show that a reliable tracking and measurement performance under noisy and dynamic sea surface environment is achieved. Once fish are tracked and measured, one of the primary tasks in the electronic monitoring is to identify the species of fish. In the work of object classification, one challenge is that the feature generation needs to be robust with fish in any orientations and poses, which yield diverse visual features and large within-class variation. Other challenges include the high visual similarity among fish species. Therefore, in this dissertation, we utilize the deep metric learning to learn a feature representation which can separate visually similar species in the feature space. By adding more constraints based on the temporal order of image sequences, we can make the model to learn a more structured and compact feature space. Besides, by exploiting the clustering properties and… Advisors/Committee Members: Hwang, Jenq-Neng (advisor).

Subjects/Keywords: object classification; object segmentation; object tracking; Electrical engineering; Electrical engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Huang, T. (2019). Automatic Video Analysis for Electronic Monitoring of Fishery Activities. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/44796

Chicago Manual of Style (16^th Edition):

Huang, Tsung-Wei. “Automatic Video Analysis for Electronic Monitoring of Fishery Activities.” 2019. Doctoral Dissertation, University of Washington. Accessed December 09, 2019. http://hdl.handle.net/1773/44796.

MLA Handbook (7^th Edition):

Huang, Tsung-Wei. “Automatic Video Analysis for Electronic Monitoring of Fishery Activities.” 2019. Web. 09 Dec 2019.

Vancouver:

Huang T. Automatic Video Analysis for Electronic Monitoring of Fishery Activities. [Internet] [Doctoral dissertation]. University of Washington; 2019. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/1773/44796.

Council of Science Editors:

Huang T. Automatic Video Analysis for Electronic Monitoring of Fishery Activities. [Doctoral Dissertation]. University of Washington; 2019. Available from: http://hdl.handle.net/1773/44796

University of Toledo

8. Ahmadi, Kaveh, ahmadi. Dim Object Tracking in Cluttered Image Sequences.

Degree: PhD, Engineering, 2016, University of Toledo

URL: http://rave.ohiolink.edu/etdc/view?acc_num=toledo1470147209

► This research is aimed at developing efficient dim object tracking techniques in cluttered image sequences. In this dissertation, a number of new techniques are presented… (more)

▼ This research is aimed at developing efficient dim object tracking techniques in cluttered image sequences. In this dissertation, a number of new techniques are presented for image enhancement, super resolution (SR), dim object tracking, and multi-sensor object tracking. Cluttered images are impaired by noise. To deal with a mixed Gaussian and impulse noise in the image, a novel sparse coding super resolution is developed. The sparse coding has recently become a widely used tool in signal and image processing. The sparse linear combination of elements from an appropriately chosen over-complete dictionary can represent many signal patches. The proposed SR is composed of a Genetic Algorithm (GA) search step to find the optimum match from low resolution dictionary. By using GA, the proposed SR is capable of efficiently up-sampling the low resolution images while preserving the image details.Dim object tracking in a heavy clutter environment is a theoretical and technological challenge in the field of image processing. For a small dim object, conventional tracking methods fail for the lack of geometrical information. Multiple Hypotheses Testing (MHT) is one of the generally accepted methods in target tracking systems. However, processing a tree structure with a significant number of branches in MHT has been a challenging issue. Tracking high-speed objects with traditional MHT requires some presumptions which limit the capabilities of these methods. In this dissertation, a hierarchal tracking system in two levels is presented to solve this problem. For each point in the lower-level, a Multi Objective Particle Swarm Optimization (MOPSO) technique is applied to a group of consecutive frames in order to reduce the number of branches in each tracking tree. Thus, an optimum track for each moving object is obtained in a group of frames. In the upper-level, an iterative process is used to connect the matching optimum tracks of the consecutive frames based on the spatial information and fitness values. Another problem of dim object tracking is background subtraction which is difficult due to noisy environment. This dissertation presents a novel algorithm for detecting and tracking small dim targets in Infrared (IR) image sequences with low Signal to Noise Ratio (SNR) based on the frequency and spatial domain information. Using a Dual-Tree Complex Wavelet Transform (DT-CWT), a Constant False Alarm Rate (CFAR) detector is applied in the frequency domain to find potential positions of objects in a frame. Following this step, a Support Vector Machine (SVM) classification is applied to accept or reject each potential point based on the spatial domain information of the frame. The combination of the frequency and spatial domain information demonstrates the high efficiency and accuracy of the proposed method which is supported by the experimental results.One of the important tools applied in this dissertation is Particle Filter (PF). The PF, a nonparametric implementation of the Bayes filter, is commonly used to estimate the state of a… Advisors/Committee Members: Salari, Ezzatollah (Committee Chair).

Subjects/Keywords: Computer Engineering; Computer Science; Dim Object Tracking; Particle Filter; Particle Swarm Optimization; Multiple Object Tracking; Multi Sensor Object Tracking; Super Resolution

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APA (6^th Edition):

Ahmadi, Kaveh, a. (2016). Dim Object Tracking in Cluttered Image Sequences. (Doctoral Dissertation). University of Toledo. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=toledo1470147209

Chicago Manual of Style (16^th Edition):

Ahmadi, Kaveh, ahmadi. “Dim Object Tracking in Cluttered Image Sequences.” 2016. Doctoral Dissertation, University of Toledo. Accessed December 09, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1470147209.

MLA Handbook (7^th Edition):

Ahmadi, Kaveh, ahmadi. “Dim Object Tracking in Cluttered Image Sequences.” 2016. Web. 09 Dec 2019.

Vancouver:

Ahmadi, Kaveh a. Dim Object Tracking in Cluttered Image Sequences. [Internet] [Doctoral dissertation]. University of Toledo; 2016. [cited 2019 Dec 09]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=toledo1470147209.

Council of Science Editors:

Ahmadi, Kaveh a. Dim Object Tracking in Cluttered Image Sequences. [Doctoral Dissertation]. University of Toledo; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=toledo1470147209

9. Lopes, Nuno Vieira. Fuzzy logic based approach for object feature tracking.

Degree: 2012, Instituto Politécnico de Leiria

URL: https://www.rcaap.pt/detail.jsp?id=oai:iconline.ipleiria.pt:10400.8/3259

►

This thesis introduces a novel technique for feature tracking in sequences of greyscale images based on fuzzy logic. A versatile and modular methodology for feature… (more)

▼

This thesis introduces a novel technique for feature tracking in sequences of greyscale images based on fuzzy logic. A versatile and modular methodology for feature tracking using fuzzy sets and inference engines is presented. Moreover, an extension of this methodology to perform the correct tracking of multiple features is also presented. To perform feature tracking three membership functions are initially defined. A membership function related to the distinctive property of the feature to be tracked. A membership function is related to the fact of considering that the feature has smooth movement between each image sequence and a membership function concerns its expected future location. Applying these functions to the image pixels, the corresponding fuzzy sets are obtained and then mathematically manipulated to serve as input to an inference engine. Situations such as occlusion or detection failure of features are overcome using estimated positions calculated using a motion model and a state vector of the feature. This methodology was previously applied to track a single feature identified by the user. Several performance tests were conducted on sequences of both synthetic and real images. Experimental results are presented, analysed and discussed. Although this methodology could be applied directly to multiple feature tracking, an extension of this methodology has been developed within that purpose. In this new method, the processing sequence of each feature is dynamic and hierarchical. Dynamic because this sequence can change over time and hierarchical because features with higher priority will be processed first. Thus, the process gives preference to features whose location are easier to predict compared with features whose knowledge of their behavior is less predictable. When this priority value becomes too low, the feature will no longer tracked by the algorithm. To access the performance of this new approach, sequences of images where several features specified by the user are to be tracked were used. In the final part of this work, conclusions drawn from this work as well as the definition of some guidelines for future research are presented.

Nesta tese é introduzida uma nova técnica de seguimento de pontos característicos de objectos em sequências de imagens em escala de cinzentos baseada em lógica difusa. É apresentada uma metodologia versátil e modular para o seguimento de objectos utilizando conjuntos difusos e motores de inferência. É também apresentada uma extensão desta metodologia para o correcto seguimento de múltiplos pontos característicos. Para se realizar o seguimento são definidas inicialmente três funções de pertença. Uma função de pertença está relacionada com a propriedade distintiva do objecto que desejamos seguir, outra está relacionada com o facto de se considerar que o objecto tem uma movimentação suave entre cada imagem da sequência e outra função de pertença referente à sua previsível localização futura. Aplicando estas funções de pertença aos píxeis da…

Advisors/Committee Members: Melo-Pinto, Pedro, Couto, Pedro M..

Subjects/Keywords: Fuzzy Logic; Object tracking; Lógica difusa

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APA (6^th Edition):

Lopes, N. V. (2012). Fuzzy logic based approach for object feature tracking. (Thesis). Instituto Politécnico de Leiria. Retrieved from https://www.rcaap.pt/detail.jsp?id=oai:iconline.ipleiria.pt:10400.8/3259

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Lopes, Nuno Vieira. “Fuzzy logic based approach for object feature tracking.” 2012. Thesis, Instituto Politécnico de Leiria. Accessed December 09, 2019. https://www.rcaap.pt/detail.jsp?id=oai:iconline.ipleiria.pt:10400.8/3259.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Lopes, Nuno Vieira. “Fuzzy logic based approach for object feature tracking.” 2012. Web. 09 Dec 2019.

Vancouver:

Lopes NV. Fuzzy logic based approach for object feature tracking. [Internet] [Thesis]. Instituto Politécnico de Leiria; 2012. [cited 2019 Dec 09]. Available from: https://www.rcaap.pt/detail.jsp?id=oai:iconline.ipleiria.pt:10400.8/3259.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lopes NV. Fuzzy logic based approach for object feature tracking. [Thesis]. Instituto Politécnico de Leiria; 2012. Available from: https://www.rcaap.pt/detail.jsp?id=oai:iconline.ipleiria.pt:10400.8/3259

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

California State University – Sacramento

10. Wadhwani, Hitesh. A tool for tracking objects through V1KU, a neural network system.

Degree: MS, Computer Science, 2011, California State University – Sacramento

URL: http://hdl.handle.net/10211.9/924

► The intent of this project is to explore the tracking capabilities of V1KU a neural network system. V1KU is a product by General Vision Company… (more)

Subjects/Keywords: Image recognition; Artificial intelligence; Object tracking

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APA (6^th Edition):

Wadhwani, H. (2011). A tool for tracking objects through V1KU, a neural network system. (Masters Thesis). California State University – Sacramento. Retrieved from http://hdl.handle.net/10211.9/924

Chicago Manual of Style (16^th Edition):

Wadhwani, Hitesh. “A tool for tracking objects through V1KU, a neural network system.” 2011. Masters Thesis, California State University – Sacramento. Accessed December 09, 2019. http://hdl.handle.net/10211.9/924.

MLA Handbook (7^th Edition):

Wadhwani, Hitesh. “A tool for tracking objects through V1KU, a neural network system.” 2011. Web. 09 Dec 2019.

Vancouver:

Wadhwani H. A tool for tracking objects through V1KU, a neural network system. [Internet] [Masters thesis]. California State University – Sacramento; 2011. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/10211.9/924.

Council of Science Editors:

Wadhwani H. A tool for tracking objects through V1KU, a neural network system. [Masters Thesis]. California State University – Sacramento; 2011. Available from: http://hdl.handle.net/10211.9/924

NSYSU

11. Hsu, Chiang-Hao. Application of an Omnidirectional Camera to Detection of Moving Objects in 3D Space.

Degree: Master, Mechanical and Electro-Mechanical Engineering, 2011, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0829111-231710

► Conventional cameras are usually small in their field of view (FOV) and make the observable region limited. Applications by such a vision system may also… (more)

Subjects/Keywords: Omnidirectional image; Object tracking; CAMShift; Optical flow

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APA (6^th Edition):

Hsu, C. (2011). Application of an Omnidirectional Camera to Detection of Moving Objects in 3D Space. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0829111-231710

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Hsu, Chiang-Hao. “Application of an Omnidirectional Camera to Detection of Moving Objects in 3D Space.” 2011. Thesis, NSYSU. Accessed December 09, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0829111-231710.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Hsu, Chiang-Hao. “Application of an Omnidirectional Camera to Detection of Moving Objects in 3D Space.” 2011. Web. 09 Dec 2019.

Vancouver:

Hsu C. Application of an Omnidirectional Camera to Detection of Moving Objects in 3D Space. [Internet] [Thesis]. NSYSU; 2011. [cited 2019 Dec 09]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0829111-231710.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hsu C. Application of an Omnidirectional Camera to Detection of Moving Objects in 3D Space. [Thesis]. NSYSU; 2011. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0829111-231710

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

King Abdullah University of Science and Technology

12. Alharbi, Yazeed. Marker Detection in Aerial Images.

Degree: 2017, King Abdullah University of Science and Technology

URL: http://hdl.handle.net/10754/623123

► The problem that the thesis is trying to solve is the detection of small markers in high-resolution aerial images. Given a high-resolution image, the goal… (more)

Subjects/Keywords: vision; computer; detection; tracking; object; description

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APA (6^th Edition):

Alharbi, Y. (2017). Marker Detection in Aerial Images. (Thesis). King Abdullah University of Science and Technology. Retrieved from http://hdl.handle.net/10754/623123

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Alharbi, Yazeed. “Marker Detection in Aerial Images.” 2017. Thesis, King Abdullah University of Science and Technology. Accessed December 09, 2019. http://hdl.handle.net/10754/623123.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Alharbi, Yazeed. “Marker Detection in Aerial Images.” 2017. Web. 09 Dec 2019.

Vancouver:

Alharbi Y. Marker Detection in Aerial Images. [Internet] [Thesis]. King Abdullah University of Science and Technology; 2017. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/10754/623123.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Alharbi Y. Marker Detection in Aerial Images. [Thesis]. King Abdullah University of Science and Technology; 2017. Available from: http://hdl.handle.net/10754/623123

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Cornell University

13. Wyffels, Kevin. Precision Tracking Of Extended Objects Via Non-Traditional Sensor Models .

Degree: 2016, Cornell University

URL: http://hdl.handle.net/1813/43659

► Inspired by human perception, novel research into the sub-domain of robotic perception, known as extended object tracking, is presented. This research is motivated by the… (more)

▼ Inspired by human perception, novel research into the sub-domain of robotic perception, known as extended object tracking, is presented. This research is motivated by the practical challenges of deploying robot driven cars (aka robocars, self-driving cars, autonomous road vehicles, etc.) into the existing transportation infrastructure alongside human-controlled vehicles. In this vein, arbitrary, uncooperative extended objects maneuvering in close proximity to the ego vehicle are considered, without a priori knowledge of the environment (e.g. road structure, traffic laws, etc.) or the objects to be tracked (e.g. controls, intent, shape, size, type, etc.). The novel approaches presented here are primarily aimed at improving the precision and accuracy of extended object tracking by mitigating the inherent information loss associated with interpreting sensor data returned from arbitrary extended objects. Specifically, a rigorous probabilistic occlusion model is derived for identifying and fusing negative information inherently present in sensor data; information that is heavily leveraged by humans, but largely ignored by robots. Further, a rigorous estimation framework is proposed for estimating the detailed shape of extended objects jointly with their kinematics; detailed object shape estimates enable explicit sensor models, which, in turn, engender improved tracking precision. Additionally, a hierarchical tracking framework is proposed for dynamically allocating computational resources in proportion to an objects continuously changing relevance to the ego robot task, as defined by novel probabilistic object relevancy metrics. As a result, at any given time, objects considered to be of central importance to the ego robot task are tracked with relatively complex, high-precision methods, while objects deemed merely peripheral to the ego robot task are tracked with relatively low complexity, low precision methods; a direct analog to the human concepts of attention and focus in allocating finite cognitive resources. The proposed work is evaluated via simulation and experiments involving Cornell University's autonomous Chevy Tahoe, Skynet, demonstrating that non-traditional sensor models are necessary for high precision tracking of arbitrary extended objects, and that humans are worth emulating en route to this goal. Advisors/Committee Members: Kress Gazit,Hadas (committeeMember), Snavely,Keith Noah (committeeMember).

Subjects/Keywords: Autonomous Vehicles; Extended Object Tracking; Probabilistic Inference

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APA (6^th Edition):

Wyffels, K. (2016). Precision Tracking Of Extended Objects Via Non-Traditional Sensor Models . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/43659

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Wyffels, Kevin. “Precision Tracking Of Extended Objects Via Non-Traditional Sensor Models .” 2016. Thesis, Cornell University. Accessed December 09, 2019. http://hdl.handle.net/1813/43659.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Wyffels, Kevin. “Precision Tracking Of Extended Objects Via Non-Traditional Sensor Models .” 2016. Web. 09 Dec 2019.

Vancouver:

Wyffels K. Precision Tracking Of Extended Objects Via Non-Traditional Sensor Models . [Internet] [Thesis]. Cornell University; 2016. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/1813/43659.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wyffels K. Precision Tracking Of Extended Objects Via Non-Traditional Sensor Models . [Thesis]. Cornell University; 2016. Available from: http://hdl.handle.net/1813/43659

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Ottawa

14. Stolle, Jacob. Experimental Modelling of Debris Dynamics in Tsunami-Like Flow Conditions .

Degree: 2016, University of Ottawa

URL: http://hdl.handle.net/10393/34959

► Tsunamis are among the most devastating and complex natural disasters, affecting coastal regions worldwide. Tsunami waves are generated through many natural phenomena, such as earthquakes,… (more)

▼ Tsunamis are among the most devastating and complex natural disasters, affecting coastal regions worldwide. Tsunami waves are generated through many natural phenomena, such as earthquakes, landslides, and volcanic eruptions. The waves travel at high speeds away from the source, potentially affecting multiple countries with very little warning. Over the past several decades, tsunamis such as the 2004 Indian Ocean, the 2010 Chilean, and the 2011 Tohoku Tsunami served as reminders of the potential devastation of these natural disasters, resulting in tragic loss of life and billions of dollars in damages. Forensic engineering field investigations and subsequent analysis of these events have demonstrated that infrastructure in these tsunami-prone regions was not adequately prepared for the extreme forces associated with a tsunami. As a result, there has been an increased research emphasis worldwide on the planning and design of infrastructure located in tsunami-prone areas to be better prepared for such future events. The present study aims to experimentally investigate and analyze the motion of debris carried by an inundating tsunami flood. One of the previous challenges involved in the evaluation of debris motion during such events was a lack of experimental methods that could non-invasively, quickly and accurately track the motion of debris at high velocities. This study introduces two innovative methods of tracking the debris. The first one used a novel camera-based tracking algorithm, while the second used Bluetooth and Inertial Measurement Unit sensors to track the debris within the inundating tsunami flood. The study outlines, for the first time, the technology and methods involved in the two tracking methods as it used both dry-test and wet-test experiments to evaluate the applicability of these methods in coastal and hydraulic engineering. This study used these two methods to evaluate the motion of debris from experiments conducted in a new Tsunami Wave Basin commissioned recently at Waseda University (Tokyo, Japan). The study examined the effect of the initial positioning of the debris, particularly focusing on the spreading area of the debris (determining thus their maximum displacement and the spreading angle of the debris). The results showed that an increase in the number of the debris resulted in an increase in the spreading angle of the debris and a decrease in the displacement of the debris. The increased number of debris also added significantly more variation in the final resting position of the debris due to the increased debris-debris collisions. The initial orientation of the debris also affected debris motion, particularly influencing the peak velocity of the debris and the distance from the initial debris resting position to where the peak velocity was observed.

Subjects/Keywords: tsunami; coastal engineering; debris; object tracking

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APA (6^th Edition):

Stolle, J. (2016). Experimental Modelling of Debris Dynamics in Tsunami-Like Flow Conditions . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/34959

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Stolle, Jacob. “Experimental Modelling of Debris Dynamics in Tsunami-Like Flow Conditions .” 2016. Thesis, University of Ottawa. Accessed December 09, 2019. http://hdl.handle.net/10393/34959.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Stolle, Jacob. “Experimental Modelling of Debris Dynamics in Tsunami-Like Flow Conditions .” 2016. Web. 09 Dec 2019.

Vancouver:

Stolle J. Experimental Modelling of Debris Dynamics in Tsunami-Like Flow Conditions . [Internet] [Thesis]. University of Ottawa; 2016. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/10393/34959.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Stolle J. Experimental Modelling of Debris Dynamics in Tsunami-Like Flow Conditions . [Thesis]. University of Ottawa; 2016. Available from: http://hdl.handle.net/10393/34959

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Rochester Institute of Technology

15. Case, Isaac. Automatic object detection and tracking in video.

Degree: Computer Science (GCCIS), 2010, Rochester Institute of Technology

URL: https://scholarworks.rit.edu/theses/244

► One ability of the human visual system is the ability to identify and track moving objects. Examples of this can easily be seen in any… (more)

Subjects/Keywords: Computer vision; Motion tracking; Object detection

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APA (6^th Edition):

Case, I. (2010). Automatic object detection and tracking in video. (Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/244

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Case, Isaac. “Automatic object detection and tracking in video.” 2010. Thesis, Rochester Institute of Technology. Accessed December 09, 2019. https://scholarworks.rit.edu/theses/244.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Case, Isaac. “Automatic object detection and tracking in video.” 2010. Web. 09 Dec 2019.

Vancouver:

Case I. Automatic object detection and tracking in video. [Internet] [Thesis]. Rochester Institute of Technology; 2010. [cited 2019 Dec 09]. Available from: https://scholarworks.rit.edu/theses/244.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Case I. Automatic object detection and tracking in video. [Thesis]. Rochester Institute of Technology; 2010. Available from: https://scholarworks.rit.edu/theses/244

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

16. Spruyt, Vincent. Robust and real-time hand detection and tracking in monocular video.

Degree: 2015, Ghent University

URL: http://hdl.handle.net/1854/LU-5872175

► In recent years, personal computing devices such as laptops, tablets and smartphones have become ubiquitous. Moreover, intelligent sensors are being integrated into many consumer devices… (more)

▼ In recent years, personal computing devices such as laptops, tablets and smartphones have become ubiquitous. Moreover, intelligent sensors are being integrated into many consumer devices such as eyeglasses, wristwatches and smart televisions. With the advent of touchscreen technology, a new human-computer interaction (HCI) paradigm arose that allows users to interface with their device in an intuitive manner. Using simple gestures, such as swipe or pinch movements, a touchscreen can be used to directly interact with a virtual environment. Nevertheless, touchscreens still form a physical barrier between the virtual interface and the real world. An increasingly popular field of research that tries to overcome this limitation, is video based gesture recognition, hand detection and hand tracking. Gesture based interaction allows the user to directly interact with the computer in a natural manner by exploring a virtual reality using nothing but his own body language. In this dissertation, we investigate how robust hand detection and tracking can be accomplished under real-time constraints. In the context of human-computer interaction, real-time is defined as both low latency and low complexity, such that a complete video frame can be processed before the next one becomes available. Furthermore, for practical applications, the algorithms should be robust to illumination changes, camera motion, and cluttered backgrounds in the scene. Finally, the system should be able to initialize automatically, and to detect and recover from tracking failure. We study a wide variety of existing algorithms, and propose significant improvements and novel methods to build a complete detection and tracking system that meets these requirements. Hand detection, hand tracking and hand segmentation are related yet technically different challenges. Whereas detection deals with finding an object in a static image, tracking considers temporal information and is used to track the position of an object over time, throughout a video sequence. Hand segmentation is the task of estimating the hand contour, thereby separating the object from its background. Detection of hands in individual video frames allows us to automatically initialize our tracking algorithm, and to detect and recover from tracking failure. Human hands are highly articulated objects, consisting of finger parts that are connected with joints. As a result, the appearance of a hand can vary greatly, depending on the assumed hand pose. Traditional detection algorithms often assume that the appearance of the object of interest can be described using a rigid model and therefore can not be used to robustly detect human hands. Therefore, we developed an algorithm that detects hands by exploiting their articulated nature. Instead of resorting to a template based approach, we probabilistically model the spatial relations between different hand parts, and the centroid of the hand. Detecting hand parts, such as fingertips, is much easier than detecting a complete hand. Based on our model of the… Advisors/Committee Members: Philips, Wilfried, Ledda, Alessandro.

Subjects/Keywords: Technology and Engineering; object detection; hand tracking; Computer Vision; object tracking; particle filtering; hand detection

10 more images…

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APA (6^th Edition):

Spruyt, V. (2015). Robust and real-time hand detection and tracking in monocular video. (Thesis). Ghent University. Retrieved from http://hdl.handle.net/1854/LU-5872175

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Spruyt, Vincent. “Robust and real-time hand detection and tracking in monocular video.” 2015. Thesis, Ghent University. Accessed December 09, 2019. http://hdl.handle.net/1854/LU-5872175.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Spruyt, Vincent. “Robust and real-time hand detection and tracking in monocular video.” 2015. Web. 09 Dec 2019.

Vancouver:

Spruyt V. Robust and real-time hand detection and tracking in monocular video. [Internet] [Thesis]. Ghent University; 2015. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/1854/LU-5872175.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Spruyt V. Robust and real-time hand detection and tracking in monocular video. [Thesis]. Ghent University; 2015. Available from: http://hdl.handle.net/1854/LU-5872175

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Virginia Tech

17. Nguyen, Chuong Hoang. Features identification and tracking for an autonomous ground vehicle.

Degree: MS, Mechanical Engineering, 2013, Virginia Tech

URL: http://hdl.handle.net/10919/33127

► This thesis attempts to develop features identification and tracking system for an autonomous ground vehicle by focusing on four fundamental tasks: Motion detection, object tracking,… (more)

Subjects/Keywords: Motion detection; object tracking; scene recognition; object detection

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APA (6^th Edition):

Nguyen, C. H. (2013). Features identification and tracking for an autonomous ground vehicle. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/33127

Chicago Manual of Style (16^th Edition):

Nguyen, Chuong Hoang. “Features identification and tracking for an autonomous ground vehicle.” 2013. Masters Thesis, Virginia Tech. Accessed December 09, 2019. http://hdl.handle.net/10919/33127.

MLA Handbook (7^th Edition):

Nguyen, Chuong Hoang. “Features identification and tracking for an autonomous ground vehicle.” 2013. Web. 09 Dec 2019.

Vancouver:

Nguyen CH. Features identification and tracking for an autonomous ground vehicle. [Internet] [Masters thesis]. Virginia Tech; 2013. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/10919/33127.

Council of Science Editors:

Nguyen CH. Features identification and tracking for an autonomous ground vehicle. [Masters Thesis]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/33127

KTH

18. Shilo, Albina. Detection and tracking of unknown objects on the road based on sparse LiDAR data for heavy duty vehicles.

Degree: Electrical Engineering and Computer Science (EECS), 2018, KTH

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-236083

►

Environment perception within autonomous driving aims to provide a comprehensive and accurate model of the surrounding environment based on information from sensors. For the… (more)

▼

Environment perception within autonomous driving aims to provide a comprehensive and accurate model of the surrounding environment based on information from sensors. For the model to be comprehensive it must provide the kinematic state of surrounding objects. The existing approaches of object detection and tracking (estimation of kinematic state) are developed for dense 3D LiDAR data from a sensor mounted on a car. However, it is a challenge to design a robust detection and tracking algorithm for sparse 3D LiDAR data. Therefore, in this thesis we propose a framework for detection and tracking of unknown objects using sparse VLP-16 LiDAR data which is mounted on a heavy duty vehicle. Experiments reveal that the proposed framework performs well detecting trucks, buses, cars, pedestrians and even smaller objects of a size bigger than 61x41x40 cm. The detection distance range depends on the size of an object such that large objects (trucks and buses) are detected within 25 m while cars and pedestrians within 18 m and 15 m correspondingly. The overall multiple objecttracking accuracy of the framework is 79%.

Miljöperception inom autonom körning syftar till att ge en heltäckande och korrekt modell av den omgivande miljön baserat på information från sensorer. För att modellen ska vara heltäckande måste den ge information om tillstånden hos omgivande objekt. Den befintliga metoden för objektidentifiering och spårning (uppskattning av kinematiskt tillstånd) utvecklas för täta 3D-LIDAR-data från en sensor monterad på en bil. Det är dock en utmaning att designa en robust detektions och spårningsalgoritm för glesa 3D-LIDAR-data. Därför föreslår vi ett ramverk för upptäckt och spårning av okända objekt med hjälp av gles VLP-16-LIDAR-data som är monterat på ett tungt fordon. Experiment visar att det föreslagna ramverket upptäcker lastbilar, bussar, bilar, fotgängare och även mindre objekt om de är större än 61x41x40 cm. Detekteringsavståndet varierar beroende på storleken på ett objekt så att stora objekt (lastbilar och bussar) detekteras inom 25 m medan bilar och fotgängare detekteras inom 18 m respektive 15 m på motsvarande sätt. Ramverkets totala precision för objektspårning är 79%.

Subjects/Keywords: Lidar; arbitrary object detection; object tracking; Robotics; Robotteknik och automation

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APA (6^th Edition):

Shilo, A. (2018). Detection and tracking of unknown objects on the road based on sparse LiDAR data for heavy duty vehicles. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-236083

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Shilo, Albina. “Detection and tracking of unknown objects on the road based on sparse LiDAR data for heavy duty vehicles.” 2018. Thesis, KTH. Accessed December 09, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-236083.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Shilo, Albina. “Detection and tracking of unknown objects on the road based on sparse LiDAR data for heavy duty vehicles.” 2018. Web. 09 Dec 2019.

Vancouver:

Shilo A. Detection and tracking of unknown objects on the road based on sparse LiDAR data for heavy duty vehicles. [Internet] [Thesis]. KTH; 2018. [cited 2019 Dec 09]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-236083.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Shilo A. Detection and tracking of unknown objects on the road based on sparse LiDAR data for heavy duty vehicles. [Thesis]. KTH; 2018. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-236083

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Georgia Tech

19. Sridhar, Sandhya. Computer vision for driver assistance systems.

Degree: MS, Electrical and Computer Engineering, 2018, Georgia Tech

URL: http://hdl.handle.net/1853/59938

► The objective of the proposed thesis is to illustrate the training, validation and evaluation of vehicle detection algorithms using computer vision and deep learning methods,… (more)

Subjects/Keywords: Computer vision; Deep learning; Autonomous driving; Object tracking; Object detection

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APA (6^th Edition):

Sridhar, S. (2018). Computer vision for driver assistance systems. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59938

Chicago Manual of Style (16^th Edition):

Sridhar, Sandhya. “Computer vision for driver assistance systems.” 2018. Masters Thesis, Georgia Tech. Accessed December 09, 2019. http://hdl.handle.net/1853/59938.

MLA Handbook (7^th Edition):

Sridhar, Sandhya. “Computer vision for driver assistance systems.” 2018. Web. 09 Dec 2019.

Vancouver:

Sridhar S. Computer vision for driver assistance systems. [Internet] [Masters thesis]. Georgia Tech; 2018. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/1853/59938.

Council of Science Editors:

Sridhar S. Computer vision for driver assistance systems. [Masters Thesis]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59938

Vanderbilt University

20. St.Clair, Rebecca. Through space and time: An examination of motion in multiple object tracking.

Degree: PhD, Psychology, 2012, Vanderbilt University

URL: http://etd.library.vanderbilt.edu//available/etd-03262012-153131/ ;

► Object correspondence is the process by which the visual system matches the identities of objects to their locations to form stable percepts. Object correspondence is… (more)

Subjects/Keywords: object correspondence; texture; motion; multiple object tracking; attention

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APA (6^th Edition):

St.Clair, R. (2012). Through space and time: An examination of motion in multiple object tracking. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://etd.library.vanderbilt.edu//available/etd-03262012-153131/ ;

Chicago Manual of Style (16^th Edition):

St.Clair, Rebecca. “Through space and time: An examination of motion in multiple object tracking.” 2012. Doctoral Dissertation, Vanderbilt University. Accessed December 09, 2019. http://etd.library.vanderbilt.edu//available/etd-03262012-153131/ ;.

MLA Handbook (7^th Edition):

St.Clair, Rebecca. “Through space and time: An examination of motion in multiple object tracking.” 2012. Web. 09 Dec 2019.

Vancouver:

St.Clair R. Through space and time: An examination of motion in multiple object tracking. [Internet] [Doctoral dissertation]. Vanderbilt University; 2012. [cited 2019 Dec 09]. Available from: http://etd.library.vanderbilt.edu//available/etd-03262012-153131/ ;.

Council of Science Editors:

St.Clair R. Through space and time: An examination of motion in multiple object tracking. [Doctoral Dissertation]. Vanderbilt University; 2012. Available from: http://etd.library.vanderbilt.edu//available/etd-03262012-153131/ ;

KTH

21. Murray, Samuel. Real-Time Multiple Object Tracking : A Study on the Importance of Speed.

Degree: Computer Science and Communication (CSC), 2017, KTH

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215117

►

Multiple object tracking consists of detecting and identifying objects in video. In some applications, such as robotics and surveillance, it is desired that the… (more)

▼

Multiple object tracking consists of detecting and identifying objects in video. In some applications, such as robotics and surveillance, it is desired that the tracking is performed in real-time. This poses a challenge in that it requires the algorithm to run as fast as the frame-rate of the video. Today's top performing tracking methods run at only a few frames per second, and can thus not be used in real-time. Further, when determining the speed of the tracker, it is common to not include the time it takes to detect objects. We argue that this way of measuring speed is not relevant for robotics or embedded systems, where the detecting of objects is done on the same machine as the tracking. We propose that one way of running a method in real-time is to not look at every frame, but skip frames to make the video have the same frame-rate as the tracking method. However, we believe that this will lead to decreased performance. In this project, we implement a multiple object tracker, following the tracking-by-detection paradigm, as an extension of an existing method. It works by modelling the movement of objects by solving the filtering problem, and associating detections with predicted new locations in new frames using the Hungarian algorithm. Three different similarity measures are used, which use the location and shape of the bounding boxes. Compared to other trackers on the MOTChallenge leaderboard, our method, referred to as C++SORT, is the fastest non-anonymous submission, while also achieving decent score on other metrics. By running our model on the Okutama-Action dataset, sampled at different frame-rates, we show that the performance is greatly reduced when running the model - including detecting objects - in real-time. In most metrics, the score is reduced by 50%, but in certain cases as much as 90%. We argue that this indicates that other, slower methods could not be used for tracking in real-time, but that more research is required specifically on this.

För att spåra rörliga objekt i video (eng: multiple object tracking) krävs att man lokaliserar och identifierar dem. I vissa tillämpningar, såsom robotik och övervakning, kan det krävas att detta görs i realtid, vilket kan vara svårt i praktiken, då det förutsätter att algoritmen kan köras lika fort som videons bildfrekvensen. De kraftfullaste algoritmerna idag kan bara analysera ett fåtal bildrutor per sekund, och lämpar sig därför inte för realtidsanvändning. Dessutom brukar tiden per bildruta inte inkludera den tid det tar att lokalisera objekt, när hastigheten av en algoritm presenteras. Vi anser att det sättet att beräkna hastigheten inte är lämpligt inom robotik eller inbyggda system, där lokaliseringen och identifiering av objekt sker på samma maskin. Många algoritmer kan köras i realtid genom att hoppa över det antal bildrutor i videon som krävs för att bildfrekvensen ska bli densamma som algoritmens frekvens. Dock tror vi att detta leder till sämre prestanda. I det här projektet implementerar vi en…

Subjects/Keywords: multiple object tracking; tracking-by-detection; Computer Sciences; Datavetenskap (datalogi)

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APA (6^th Edition):

Murray, S. (2017). Real-Time Multiple Object Tracking : A Study on the Importance of Speed. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215117

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Murray, Samuel. “Real-Time Multiple Object Tracking : A Study on the Importance of Speed.” 2017. Thesis, KTH. Accessed December 09, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215117.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Murray, Samuel. “Real-Time Multiple Object Tracking : A Study on the Importance of Speed.” 2017. Web. 09 Dec 2019.

Vancouver:

Murray S. Real-Time Multiple Object Tracking : A Study on the Importance of Speed. [Internet] [Thesis]. KTH; 2017. [cited 2019 Dec 09]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215117.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Murray S. Real-Time Multiple Object Tracking : A Study on the Importance of Speed. [Thesis]. KTH; 2017. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215117

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Western Ontario

22. Ramin, Marjan. Improvements to Tracking Pedestrians in Video Streams Using a Pre-trained Convolutional Neural Network.

Degree: 2016, University of Western Ontario

URL: https://ir.lib.uwo.ca/etd/3886

► Safety has been a very crucial aspect in our lives and much attention has been paid to this issue since we need to remain safe… (more)

Subjects/Keywords: Multiple Pedestrian Tracking; Deep Learning; Object Tracking; Computer Engineering

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APA (6^th Edition):

Ramin, M. (2016). Improvements to Tracking Pedestrians in Video Streams Using a Pre-trained Convolutional Neural Network. (Thesis). University of Western Ontario. Retrieved from https://ir.lib.uwo.ca/etd/3886

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Ramin, Marjan. “Improvements to Tracking Pedestrians in Video Streams Using a Pre-trained Convolutional Neural Network.” 2016. Thesis, University of Western Ontario. Accessed December 09, 2019. https://ir.lib.uwo.ca/etd/3886.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Ramin, Marjan. “Improvements to Tracking Pedestrians in Video Streams Using a Pre-trained Convolutional Neural Network.” 2016. Web. 09 Dec 2019.

Vancouver:

Ramin M. Improvements to Tracking Pedestrians in Video Streams Using a Pre-trained Convolutional Neural Network. [Internet] [Thesis]. University of Western Ontario; 2016. [cited 2019 Dec 09]. Available from: https://ir.lib.uwo.ca/etd/3886.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ramin M. Improvements to Tracking Pedestrians in Video Streams Using a Pre-trained Convolutional Neural Network. [Thesis]. University of Western Ontario; 2016. Available from: https://ir.lib.uwo.ca/etd/3886

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Universidade Nova

23. Silva, João Miguel Ferreira da. People and object tracking for video annotation.

Degree: 2012, Universidade Nova

URL: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/8953

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Object tracking is a thoroughly researched problem, with a body of associated literature dating at… (more)

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Object tracking is a thoroughly researched problem, with a body of associated literature dating at least as far back as the late 1970s. However, and despite the development of some satisfactory real-time trackers, it has not yet seen widespread use. This is not due to a lack of applications for the technology, since several interesting ones exist. In this document, it is postulated that this status quo is due, at least in part, to a lack of easy to use software libraries supporting object tracking. An overview of the problems associated with object tracking is presented and the process of developing one such library is documented. This discussion includes how to overcome problems like heterogeneities in object representations and requirements for training or initial object position hints. Video annotation is the process of associating data with a video’s content. Associating data with a video has numerous applications, ranging from making large video archives or long videos searchable, to enabling discussion about and augmentation of the video’s content. Object tracking is presented as a valid approach to both automatic and manual video annotation, and the integration of the developed object tracking library into an existing video annotator, running on a tablet computer, is described. The challenges involved in designing an interface to support the association of video annotations with tracked objects in real-time are also discussed. In particular, we discuss our interaction approaches to handle moving object selection on live video, which we have called “Hold and Overlay” and “Hold and Speed Up”. In addition, the results of a set of preliminary tests are reported.

project “TKB – A Transmedia Knowledge Base for contemporary dance” (PTDC/EA /AVP/098220/2008 funded by FCT/MCTES), the UTAustin – Portugal, Digital Media Program (SFRH/BD/42662/2007 FCT/MCTES) and by CITI/DI/FCT/UNL (Pest-OE/EEI/UI0527/2011)

Advisors/Committee Members: Correia, Nuno.

Subjects/Keywords: Multimedia; People tracking; Object tracking; Video; Video annotation; Computer vision

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APA (6^th Edition):

Silva, J. M. F. d. (2012). People and object tracking for video annotation. (Thesis). Universidade Nova. Retrieved from http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/8953

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Silva, João Miguel Ferreira da. “People and object tracking for video annotation.” 2012. Thesis, Universidade Nova. Accessed December 09, 2019. http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/8953.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Silva, João Miguel Ferreira da. “People and object tracking for video annotation.” 2012. Web. 09 Dec 2019.

Vancouver:

Silva JMFd. People and object tracking for video annotation. [Internet] [Thesis]. Universidade Nova; 2012. [cited 2019 Dec 09]. Available from: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/8953.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Silva JMFd. People and object tracking for video annotation. [Thesis]. Universidade Nova; 2012. Available from: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/8953

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

King Abdullah University of Science and Technology

24. Mueller, Matthias. Persistent Aerial Tracking.

Degree: 2016, King Abdullah University of Science and Technology

URL: http://hdl.handle.net/10754/608605

► In this thesis, we propose a new aerial video dataset and benchmark for low altitude UAV target tracking, as well as, a photo-realistic UAV simulator… (more)

Subjects/Keywords: object tracking; Aerial tracking; UAV; surveillance; Benchmark; Simulator

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APA (6^th Edition):

Mueller, M. (2016). Persistent Aerial Tracking. (Thesis). King Abdullah University of Science and Technology. Retrieved from http://hdl.handle.net/10754/608605

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Mueller, Matthias. “Persistent Aerial Tracking.” 2016. Thesis, King Abdullah University of Science and Technology. Accessed December 09, 2019. http://hdl.handle.net/10754/608605.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Mueller, Matthias. “Persistent Aerial Tracking.” 2016. Web. 09 Dec 2019.

Vancouver:

Mueller M. Persistent Aerial Tracking. [Internet] [Thesis]. King Abdullah University of Science and Technology; 2016. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/10754/608605.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mueller M. Persistent Aerial Tracking. [Thesis]. King Abdullah University of Science and Technology; 2016. Available from: http://hdl.handle.net/10754/608605

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Rochester Institute of Technology

25. Li, Feng. Optimizations and applications in head-mounted video-based eye tracking.

Degree: Chester F. Carlson Center for Imaging Science (COS), 2011, Rochester Institute of Technology

URL: https://scholarworks.rit.edu/theses/2939

► Video-based eye tracking techniques have become increasingly attractive in many research fields, such as visual perception and human-computer interface design. The technique primarily relies on… (more)

▼ Video-based eye tracking techniques have become increasingly attractive in many research fields, such as visual perception and human-computer interface design. The technique primarily relies on the positional difference between the center of the eye's pupil and the first-surface reflection at the cornea, the corneal reflection (CR). This difference vector is mapped to determine an observer's point of regard (POR). In current head-mounted video-based eye trackers, the systems are limited in several aspects, such as inadequate measurement range and misdetection of eye features (pupil and CR). This research first proposes a new `structured illumination' configuration, using multiple IREDs to illuminate the eye, to ensure that eye positions can still be tracked even during extreme eye movements (up to ±45° horizontally and ±25° vertically). Then eye features are detected by a two-stage processing approach. First, potential CRs and the pupil are isolated based on statistical information in an eye image. Second, genuine CRs are distinguished by a novel CR location prediction technique based on the well-correlated relationship between the offset of the pupil and that of the CR. The optical relationship of the pupil and CR offsets derived in this thesis can be applied to two typical illumination configurations - collimated and near-source ones- in the video-based eye tracking system. The relationships from the optical derivation and that from an experimental measurement match well. Two application studies, smooth pursuit dynamics in controlled static (laboratory) and unconstrained vibrating (car) environments were conducted. In the first study, the extended stimuli (color photographs subtending 2° and 17°, respectively) were found to enhance smooth pursuit movements induced by realistic images, and the eye velocity for tracking a small dot (subtending <0.1°) was saturated at about 64 deg/sec while the saturation velocity occurred at higher velocities for the extended images. The difference in gain due to target size was significant between dot and the two extended stimuli, while no statistical difference existed between the two extended stimuli. In the second study, twovisual stimuli same as in the first study were used. The visual performance was impaired dramatically due to the whole body motion in the car, even in the tracking of a slowly moving target (2 deg/sec); the eye was found not able to perform a pursuit task as smooth as in the static environment though the unconstrained head motion in the unstable condition was supposed to enhance the visual performance. Advisors/Committee Members: Pelz, Jeff.

Subjects/Keywords: Eye tracker; Eye tracking; Feature detection; Object tracking; Smooth pursuit

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APA (6^th Edition):

Li, F. (2011). Optimizations and applications in head-mounted video-based eye tracking. (Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/2939

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Li, Feng. “Optimizations and applications in head-mounted video-based eye tracking.” 2011. Thesis, Rochester Institute of Technology. Accessed December 09, 2019. https://scholarworks.rit.edu/theses/2939.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Li, Feng. “Optimizations and applications in head-mounted video-based eye tracking.” 2011. Web. 09 Dec 2019.

Vancouver:

Li F. Optimizations and applications in head-mounted video-based eye tracking. [Internet] [Thesis]. Rochester Institute of Technology; 2011. [cited 2019 Dec 09]. Available from: https://scholarworks.rit.edu/theses/2939.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Li F. Optimizations and applications in head-mounted video-based eye tracking. [Thesis]. Rochester Institute of Technology; 2011. Available from: https://scholarworks.rit.edu/theses/2939

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Exeter

26. De Ath, G. Object tracking in video with part-based tracking by feature sampling.

Degree: PhD, 2019, University of Exeter

URL: http://hdl.handle.net/10871/38781

► Visual tracking of arbitrary objects is an active research topic in computer vision, with applications across multiple disciplines including video surveillance, activity analysis, robot vision,… (more)

▼ Visual tracking of arbitrary objects is an active research topic in computer vision, with applications across multiple disciplines including video surveillance, activity analysis, robot vision, and human computer interface. Despite great progress having been made in object tracking in recent years, it still remains a challenge to design trackers that can deal with difficult tracking scenarios, such as camera motion, object motion change, occlusion, illumination changes, and object deformation. A promising way of tackling these types of problems is to use a part-based method; one which models and tracks small regions of the object and estimates the location of the object based on the tracked part's positions. These approaches typically model parts of objects with histograms of various hand-crafted features extracted from the region in which the part is located. However, it is unclear how such relatively homogeneous regions should be represented to form an effective part-based tracker. In this thesis we present a part-based tracker that includes a model for object parts that is designed to empirically characterise the underlying colour distribution of an image region, representing it by pairs of randomly selected colour features and counts of how many pixels are similar to each feature. This novel feature representation is used to find probable locations for the part in future frames via a Bhattacharyya Distance-based metric, which is modified to prefer higher quality matches. Sets of candidate patch locations are generated by randomly generating non-shearing affine transformations of the part's previous locations and locally optimising the most likely sets of parts to allow for small intra-frame object deformations. We also present a study of model initialisation in online, model-free tracking and evaluate several techniques for selecting the regions of an image, given a target bounding box most likely to contain an object. The strengths and limitations of the combined tracker are evaluated on the VOT2016 and VOT2018 datasets using their evaluation protocol, which also allows an extensive evaluation of parameter robustness. The presented tracker is ranked first among part-based trackers on the VOT2018 dataset and is particularly robust to changes in object and camera motion, as well as object size changes.

Subjects/Keywords: Object Tracking; Computer Vision; Segmentation; Initialisation; Single-Target Tracking

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

De Ath, G. (2019). Object tracking in video with part-based tracking by feature sampling. (Doctoral Dissertation). University of Exeter. Retrieved from http://hdl.handle.net/10871/38781

Chicago Manual of Style (16^th Edition):

De Ath, G. “Object tracking in video with part-based tracking by feature sampling.” 2019. Doctoral Dissertation, University of Exeter. Accessed December 09, 2019. http://hdl.handle.net/10871/38781.

MLA Handbook (7^th Edition):

De Ath, G. “Object tracking in video with part-based tracking by feature sampling.” 2019. Web. 09 Dec 2019.

Vancouver:

De Ath G. Object tracking in video with part-based tracking by feature sampling. [Internet] [Doctoral dissertation]. University of Exeter; 2019. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/10871/38781.

Council of Science Editors:

De Ath G. Object tracking in video with part-based tracking by feature sampling. [Doctoral Dissertation]. University of Exeter; 2019. Available from: http://hdl.handle.net/10871/38781

27. Shanmuga Vadivel, Karthikeyan. Modeling Eye Tracking Data with Application to Object Detection.

Degree: 2014, University of California – eScholarship, University of California

URL: http://www.escholarship.org/uc/item/556687hq

► This research focuses on enhancing computer vision algorithms using eye tracking and visual saliency. Recent advances in eye tracking device technology have enabled large scale… (more)

Subjects/Keywords: Engineering; Electrical engineering; Computer science; Eye Tracking; Multiple Object Tracking; Object Detection; Text Detection; Visual Saliency

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APA (6^th Edition):

Shanmuga Vadivel, K. (2014). Modeling Eye Tracking Data with Application to Object Detection. (Thesis). University of California – eScholarship, University of California. Retrieved from http://www.escholarship.org/uc/item/556687hq

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Shanmuga Vadivel, Karthikeyan. “Modeling Eye Tracking Data with Application to Object Detection.” 2014. Thesis, University of California – eScholarship, University of California. Accessed December 09, 2019. http://www.escholarship.org/uc/item/556687hq.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Shanmuga Vadivel, Karthikeyan. “Modeling Eye Tracking Data with Application to Object Detection.” 2014. Web. 09 Dec 2019.

Vancouver:

Shanmuga Vadivel K. Modeling Eye Tracking Data with Application to Object Detection. [Internet] [Thesis]. University of California – eScholarship, University of California; 2014. [cited 2019 Dec 09]. Available from: http://www.escholarship.org/uc/item/556687hq.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Shanmuga Vadivel K. Modeling Eye Tracking Data with Application to Object Detection. [Thesis]. University of California – eScholarship, University of California; 2014. Available from: http://www.escholarship.org/uc/item/556687hq

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

28. Liu, Jia-Ying. Real-time Face Recognition System with Self-learning.

Degree: Master, Computer Science and Engineering, 2017, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0426117-093435

► Face recognition has matured over the recent years, it is widely used in access control system, immigration control system even lecture attendance system. Traditional face… (more)

Subjects/Keywords: Face recognition; Face detection; Skin color detection; Moving object detection; Object tracking

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APA (6^th Edition):

Liu, J. (2017). Real-time Face Recognition System with Self-learning. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0426117-093435

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Liu, Jia-Ying. “Real-time Face Recognition System with Self-learning.” 2017. Thesis, NSYSU. Accessed December 09, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0426117-093435.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Liu, Jia-Ying. “Real-time Face Recognition System with Self-learning.” 2017. Web. 09 Dec 2019.

Vancouver:

Liu J. Real-time Face Recognition System with Self-learning. [Internet] [Thesis]. NSYSU; 2017. [cited 2019 Dec 09]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0426117-093435.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Liu J. Real-time Face Recognition System with Self-learning. [Thesis]. NSYSU; 2017. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0426117-093435

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Colorado

29. Cox, Rebecca E. Merging Local and Global 3d Perception for Robotic Grasping and Manipulation.

Degree: MS, Electrical, Computer & Energy Engineering, 2017, University of Colorado

URL: https://scholar.colorado.edu/ecen_gradetds/148

► This paper presents our results towards fusing RGB-D images with data from contact and proximity sensors embedded in a robotic hand for improved object perception,… (more)

Subjects/Keywords: robotics; object perception; optics; sensor calibration; object tracking; contact detection; Computer Engineering; Robotics

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APA (6^th Edition):

Cox, R. E. (2017). Merging Local and Global 3d Perception for Robotic Grasping and Manipulation. (Masters Thesis). University of Colorado. Retrieved from https://scholar.colorado.edu/ecen_gradetds/148

Chicago Manual of Style (16^th Edition):

Cox, Rebecca E. “Merging Local and Global 3d Perception for Robotic Grasping and Manipulation.” 2017. Masters Thesis, University of Colorado. Accessed December 09, 2019. https://scholar.colorado.edu/ecen_gradetds/148.

MLA Handbook (7^th Edition):

Cox, Rebecca E. “Merging Local and Global 3d Perception for Robotic Grasping and Manipulation.” 2017. Web. 09 Dec 2019.

Vancouver:

Cox RE. Merging Local and Global 3d Perception for Robotic Grasping and Manipulation. [Internet] [Masters thesis]. University of Colorado; 2017. [cited 2019 Dec 09]. Available from: https://scholar.colorado.edu/ecen_gradetds/148.

Council of Science Editors:

Cox RE. Merging Local and Global 3d Perception for Robotic Grasping and Manipulation. [Masters Thesis]. University of Colorado; 2017. Available from: https://scholar.colorado.edu/ecen_gradetds/148

Louisiana State University

30. Erdman, Justin Lee. SeaVipers - Computer Vision and Inertial Position Reference Sensor System (CVIPRSS).

Degree: PhD, Computer Sciences, 2015, Louisiana State University

URL: etd-06012015-195140 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1208

► This work describes the design and development of an optical, Computer Vision (CV) based sensor for use as a Position Reference System (PRS) in Dynamic… (more)

Subjects/Keywords: TLD; machine learning; object detection; computer vision; dynamic positioning; position reference system; object tracking

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APA (6^th Edition):

Erdman, J. L. (2015). SeaVipers - Computer Vision and Inertial Position Reference Sensor System (CVIPRSS). (Doctoral Dissertation). Louisiana State University. Retrieved from etd-06012015-195140 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1208

Chicago Manual of Style (16^th Edition):

Erdman, Justin Lee. “SeaVipers - Computer Vision and Inertial Position Reference Sensor System (CVIPRSS).” 2015. Doctoral Dissertation, Louisiana State University. Accessed December 09, 2019. etd-06012015-195140 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1208.

MLA Handbook (7^th Edition):

Erdman, Justin Lee. “SeaVipers - Computer Vision and Inertial Position Reference Sensor System (CVIPRSS).” 2015. Web. 09 Dec 2019.

Vancouver:

Erdman JL. SeaVipers - Computer Vision and Inertial Position Reference Sensor System (CVIPRSS). [Internet] [Doctoral dissertation]. Louisiana State University; 2015. [cited 2019 Dec 09]. Available from: etd-06012015-195140 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1208.

Council of Science Editors:

Erdman JL. SeaVipers - Computer Vision and Inertial Position Reference Sensor System (CVIPRSS). [Doctoral Dissertation]. Louisiana State University; 2015. Available from: etd-06012015-195140 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1208

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Open Access Theses and Dissertations