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 March 08, 2021. 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. 08 Mar 2021.

Vancouver:

Nyström A. Evaluation of Multiple Object Tracking in Surveillance Video. [Internet] [Thesis]. Linköping University; 2019. [cited 2021 Mar 08]. 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

University of Adelaide

2. Wang, Xinyu. High-performance Object Detection and Tracking Using Deep Learning.

Degree: 2019, University of Adelaide

URL: http://hdl.handle.net/2440/124521

► Human detection and tracking are two fundamental problems in computer vision, which have been cornerstones for many real-world applications such as video surveillance, intelligent transportation… (more)

▼ Human detection and tracking are two fundamental problems in computer vision, which have been cornerstones for many real-world applications such as video surveillance, intelligent transportation systems and autonomous driving. Benefiting from deep learning technologies such as convolutional neural networks, modern object detectors and trackers have been achieving much improved accuracy on public benchmarks. In this work, we aim to improve deep learning based human detection. Our main idea is to exploit semantic context information for human detection by using deeply learned semantic features provided by semantic segmentation masks. These segmentation masks play as an attention mechanism and enforce the detectors to focus on the image regions where potential object candidates are likely to appear. Furthermore, after reviewing some widely used detection benchmarks, we found that the annotation quality for small and crowd objects does not meet to a satisfied standard. Hence, we introduce a new dataset which includes more than 8000 images for detecting small and crowd targets in fixed angle videos. Meanwhile, a baseline detector was proposed to exploit motion channel features for boosting the detection performance. The experimental results show that our proposed approach significantly improve the detection accuracy for the baseline detectors. In addition to a novel method for object tracking, we propose to transfer the deep feature which is learned originally for image classification to the visual tracking domain. The domain adaptation is achieved via some “grafted” auxiliary networks which are trained by regressing the object location in tracking frames. Moreover, the adaptation is also naturally used for introducing the objectness concept into visual tracking. This removes a long-standing target ambiguity in visual tracking tasks and we illustrate the empirical superiority of the more well-defined task. We also experimentally demonstrate the effectiveness of our proposed tracker on two widely used benchmarks Advisors/Committee Members: Shen, Chunhua (advisor), Liu, Lingqiao (advisor), School of Computer Science (school).

Subjects/Keywords: Object detection; object tracking; deep learning

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APA (6^th Edition):

Wang, X. (2019). High-performance Object Detection and Tracking Using Deep Learning. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/124521

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):

Wang, Xinyu. “High-performance Object Detection and Tracking Using Deep Learning.” 2019. Thesis, University of Adelaide. Accessed March 08, 2021. http://hdl.handle.net/2440/124521.

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

MLA Handbook (7^th Edition):

Wang, Xinyu. “High-performance Object Detection and Tracking Using Deep Learning.” 2019. Web. 08 Mar 2021.

Vancouver:

Wang X. High-performance Object Detection and Tracking Using Deep Learning. [Internet] [Thesis]. University of Adelaide; 2019. [cited 2021 Mar 08]. Available from: http://hdl.handle.net/2440/124521.

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

Council of Science Editors:

Wang X. High-performance Object Detection and Tracking Using Deep Learning. [Thesis]. University of Adelaide; 2019. Available from: http://hdl.handle.net/2440/124521

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

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

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 March 08, 2021. 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. 08 Mar 2021.

Vancouver:

Zhu G. An Exploration into Model-Free Online Visual Object Tracking . [Internet] [Thesis]. Australian National University; 2016. [cited 2021 Mar 08]. 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 Windsor

4. Kiani, Kasra. Estimation, Detection and Tracking of Point Objects ON VIDEO.

Degree: MA, Electrical and Computer Engineering, 2020, University of Windsor

URL: https://scholar.uwindsor.ca/etd/8378

► Detecting an extremely small object in a image has always been an important problem. The problem of detecting an object with circular Point Spread Function… (more)

Subjects/Keywords: Eye Tracking; Eye-Gaze Estimation; Image Processing; Object Detection; Tracking Object

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APA (6^th Edition):

Kiani, K. (2020). Estimation, Detection and Tracking of Point Objects ON VIDEO. (Masters Thesis). University of Windsor. Retrieved from https://scholar.uwindsor.ca/etd/8378

Chicago Manual of Style (16^th Edition):

Kiani, Kasra. “Estimation, Detection and Tracking of Point Objects ON VIDEO.” 2020. Masters Thesis, University of Windsor. Accessed March 08, 2021. https://scholar.uwindsor.ca/etd/8378.

MLA Handbook (7^th Edition):

Kiani, Kasra. “Estimation, Detection and Tracking of Point Objects ON VIDEO.” 2020. Web. 08 Mar 2021.

Vancouver:

Kiani K. Estimation, Detection and Tracking of Point Objects ON VIDEO. [Internet] [Masters thesis]. University of Windsor; 2020. [cited 2021 Mar 08]. Available from: https://scholar.uwindsor.ca/etd/8378.

Council of Science Editors:

Kiani K. Estimation, Detection and Tracking of Point Objects ON VIDEO. [Masters Thesis]. University of Windsor; 2020. Available from: https://scholar.uwindsor.ca/etd/8378

Universiteit Utrecht

5. 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 March 08, 2021. 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. 08 Mar 2021.

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 2021 Mar 08]. 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

6. 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 March 08, 2021. 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. 08 Mar 2021.

Vancouver:

Huang T. Automatic Video Analysis for Electronic Monitoring of Fishery Activities. [Internet] [Doctoral dissertation]. University of Washington; 2019. [cited 2021 Mar 08]. 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

Delft University of Technology

7. Arya Senna Abdul Rachman, Arya (author). 3D-LIDAR Multi Object Tracking for Autonomous Driving: Multi-target Detection and Tracking under Urban Road Uncertainties.

Degree: 2017, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:f536b829-42ae-41d5-968d-13bbaa4ec736

►

The recent advancement of the autonomous vehicle has raised the need for reliable environmental perception. This is evident, as an autonomous vehicle has to perceive… (more)

▼

The recent advancement of the autonomous vehicle has raised the need for reliable environmental perception. This is evident, as an autonomous vehicle has to perceive and interpret its local environment in order to execute reactive and predictive control action. Object Tracking is an integral part of vehicle perception, as it enables the vehicle to estimate surrounding objects trajectories to achieve dynamic motion planning. The 3D LIDAR has been widely used in object tracking research since the mechanically compact sensor provides rich, far-reaching and real-time data of spatial information around the vehicle. On the other hand, the development of autonomous driving is heading toward its use in the urban-driving situation. In an urban situation, a robust detection and tracking algorithm is required due to increasing number of Vulnerable Road User (e.g. pedestrian and cyclist), heterogeneous terrain, inherent measurement uncertainties and limited sensor reach. This thesis presents an integrated framework of multi-target object detection and tracking using 3D LIDAR geared toward urban use. The framework combines occlusion-aware detection methods, probabilistic adaptive filtering and computationally efficient heuristics logic-based filtering to handle uncertainties arising from sensing limitation of 3D LIDAR and complexity of the target object movement. The implemented framework takes a raw 3D LIDAR data as input to perform multi-target object detection while simultaneously maintaining track of the detected objects' kinematic states and dimension in robust, causal, and real-time manner. Robust detection is enabled by slope-based ground removal and L-shape fitting to reliably enclose bounding box to objects of interest in the presence of sensor occlusion. The tracker utilises three combined Bayesian filters (IMM-UK-JPDAF) which simultaneously tackle association uncertainties, motion uncertainties and estimate non-linear stochastic motion model in real-time. Logic-based rule filters are also designed to augment the rest of detection and tracking based on the understanding of LIDAR sensor limitation and occlusion characteristic. The evaluation results using real-world pre-recorded 3D LIDAR data show the proposed framework can achieve promising real-time tracking performance in urban situations. Diverse datasets are deliberately chosen to evaluate if the MOT system is capable of working in a varying driving scenario. The benchmark results highlight that the designed and implemented MOT system is performing on par with the state-of-art works and yield satisfying accuracy and precision in most given urban settings.

Systems and Control

Advisors/Committee Members: Campoy Cervera, Pascual (mentor), Sefati, Mohsen (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: Multi-object Tracking; Vehicle Perception; 3D LIDAR; Object detection; Object tracking; Probabilistic Tracking; Autonomous driving; Machine vision; Adaptive Filtering; Heuristic Rules

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APA (6^th Edition):

Arya Senna Abdul Rachman, A. (. (2017). 3D-LIDAR Multi Object Tracking for Autonomous Driving: Multi-target Detection and Tracking under Urban Road Uncertainties. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:f536b829-42ae-41d5-968d-13bbaa4ec736

Chicago Manual of Style (16^th Edition):

Arya Senna Abdul Rachman, Arya (author). “3D-LIDAR Multi Object Tracking for Autonomous Driving: Multi-target Detection and Tracking under Urban Road Uncertainties.” 2017. Masters Thesis, Delft University of Technology. Accessed March 08, 2021. http://resolver.tudelft.nl/uuid:f536b829-42ae-41d5-968d-13bbaa4ec736.

MLA Handbook (7^th Edition):

Arya Senna Abdul Rachman, Arya (author). “3D-LIDAR Multi Object Tracking for Autonomous Driving: Multi-target Detection and Tracking under Urban Road Uncertainties.” 2017. Web. 08 Mar 2021.

Vancouver:

Arya Senna Abdul Rachman A(. 3D-LIDAR Multi Object Tracking for Autonomous Driving: Multi-target Detection and Tracking under Urban Road Uncertainties. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2021 Mar 08]. Available from: http://resolver.tudelft.nl/uuid:f536b829-42ae-41d5-968d-13bbaa4ec736.

Council of Science Editors:

Arya Senna Abdul Rachman A(. 3D-LIDAR Multi Object Tracking for Autonomous Driving: Multi-target Detection and Tracking under Urban Road Uncertainties. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:f536b829-42ae-41d5-968d-13bbaa4ec736

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

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 March 08, 2021. 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. 08 Mar 2021.

Vancouver:

Ahmadi, Kaveh a. Dim Object Tracking in Cluttered Image Sequences. [Internet] [Doctoral dissertation]. University of Toledo; 2016. [cited 2021 Mar 08]. 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

NSYSU

9. 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 March 08, 2021. 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. 08 Mar 2021.

Vancouver:

Hsu C. Application of an Omnidirectional Camera to Detection of Moving Objects in 3D Space. [Internet] [Thesis]. NSYSU; 2011. [cited 2021 Mar 08]. 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

10. 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)

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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 March 08, 2021. 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. 08 Mar 2021.

Vancouver:

Lopes NV. Fuzzy logic based approach for object feature tracking. [Internet] [Thesis]. Instituto Politécnico de Leiria; 2012. [cited 2021 Mar 08]. 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

University of Ottawa

11. 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 March 08, 2021. 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. 08 Mar 2021.

Vancouver:

Stolle J. Experimental Modelling of Debris Dynamics in Tsunami-Like Flow Conditions . [Internet] [Thesis]. University of Ottawa; 2016. [cited 2021 Mar 08]. 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

University of Melbourne

12. Lapierre, Mark David. Interaction of attention and memory: a working memory model of multiple object tracking.

Degree: 2013, University of Melbourne

URL: http://hdl.handle.net/11343/39744

► To accurately perceive a dynamic environment, the visual system must create mental representations of specific objects and their place in the environment, must quickly and… (more)

Subjects/Keywords: attention; memory; multiple object tracking; perception; vision

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APA (6^th Edition):

Lapierre, M. D. (2013). Interaction of attention and memory: a working memory model of multiple object tracking. (Doctoral Dissertation). University of Melbourne. Retrieved from http://hdl.handle.net/11343/39744

Chicago Manual of Style (16^th Edition):

Lapierre, Mark David. “Interaction of attention and memory: a working memory model of multiple object tracking.” 2013. Doctoral Dissertation, University of Melbourne. Accessed March 08, 2021. http://hdl.handle.net/11343/39744.

MLA Handbook (7^th Edition):

Lapierre, Mark David. “Interaction of attention and memory: a working memory model of multiple object tracking.” 2013. Web. 08 Mar 2021.

Vancouver:

Lapierre MD. Interaction of attention and memory: a working memory model of multiple object tracking. [Internet] [Doctoral dissertation]. University of Melbourne; 2013. [cited 2021 Mar 08]. Available from: http://hdl.handle.net/11343/39744.

Council of Science Editors:

Lapierre MD. Interaction of attention and memory: a working memory model of multiple object tracking. [Doctoral Dissertation]. University of Melbourne; 2013. Available from: http://hdl.handle.net/11343/39744

California State University – Sacramento

13. 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 March 08, 2021. 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. 08 Mar 2021.

Vancouver:

Wadhwani H. A tool for tracking objects through V1KU, a neural network system. [Internet] [Masters thesis]. California State University – Sacramento; 2011. [cited 2021 Mar 08]. 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

14. 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 March 08, 2021. 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. 08 Mar 2021.

Vancouver:

Spruyt V. Robust and real-time hand detection and tracking in monocular video. [Internet] [Thesis]. Ghent University; 2015. [cited 2021 Mar 08]. 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

Vanderbilt University

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

Degree: PhD, Psychology, 2012, Vanderbilt University

URL: http://hdl.handle.net/1803/11419

► 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://hdl.handle.net/1803/11419

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 March 08, 2021. http://hdl.handle.net/1803/11419.

MLA Handbook (7^th Edition):

St.Clair, Rebecca. “Through space and time: An examination of motion in multiple object tracking.” 2012. Web. 08 Mar 2021.

Vancouver:

St.Clair R. Through space and time: An examination of motion in multiple object tracking. [Internet] [Doctoral dissertation]. Vanderbilt University; 2012. [cited 2021 Mar 08]. Available from: http://hdl.handle.net/1803/11419.

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://hdl.handle.net/1803/11419

KTH

16. 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 March 08, 2021. 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. 08 Mar 2021.

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 2021 Mar 08]. 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

Victoria University of Wellington

17. Ajmal, Aisha. Active Shift Attention Based Object Tracking System.

Degree: 2020, Victoria University of Wellington

URL: http://hdl.handle.net/10063/9233

► The human vision system (HVS) collects a huge amount of information and performs a variety of biological mechanisms to select relevant information. Computational models based… (more)

Subjects/Keywords: Saliency; Object detection; Kalman Filter; Computer Vision; Object Tracking

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APA (6^th Edition):

Ajmal, A. (2020). Active Shift Attention Based Object Tracking System. (Masters Thesis). Victoria University of Wellington. Retrieved from http://hdl.handle.net/10063/9233

Chicago Manual of Style (16^th Edition):

Ajmal, Aisha. “Active Shift Attention Based Object Tracking System.” 2020. Masters Thesis, Victoria University of Wellington. Accessed March 08, 2021. http://hdl.handle.net/10063/9233.

MLA Handbook (7^th Edition):

Ajmal, Aisha. “Active Shift Attention Based Object Tracking System.” 2020. Web. 08 Mar 2021.

Vancouver:

Ajmal A. Active Shift Attention Based Object Tracking System. [Internet] [Masters thesis]. Victoria University of Wellington; 2020. [cited 2021 Mar 08]. Available from: http://hdl.handle.net/10063/9233.

Council of Science Editors:

Ajmal A. Active Shift Attention Based Object Tracking System. [Masters Thesis]. Victoria University of Wellington; 2020. Available from: http://hdl.handle.net/10063/9233

Virginia Tech

18. 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 March 08, 2021. 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. 08 Mar 2021.

Vancouver:

Nguyen CH. Features identification and tracking for an autonomous ground vehicle. [Internet] [Masters thesis]. Virginia Tech; 2013. [cited 2021 Mar 08]. 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

Texas A&M University

19. Nyman, Tristin. Object Individuation Using Function in Infancy: An Eye-Tracking Study.

Degree: MS, Psychology, 2018, Texas A&M University

URL: http://hdl.handle.net/1969.1/174426

► The age at which infants are able to individuate between objects on the basis of the functional category to which it belongs has yet to… (more)

▼ The age at which infants are able to individuate between objects on the basis of the functional category to which it belongs has yet to be determined. Object individuation depends on a variety of object characteristics such as function, color, shape, or name, as well as infant characteristics such as age. Recently, research has emphasized the importance of individuation using functional information in infancy. In this study, looking time performance for infants aged 3- to 8 months and 12- to 18- months was evaluated using eye-tracking technology to assess infants’ abilities to individuate objects based on functional categories. Infants were either given the opportunity to create a functional category (i.e., roller and cutter) by viewing functional examples in the Experimental Condition, or they were not given this opportunity in the Control Condition. Across both conditions no significant differences were found among looking time during the final phase of the test trials for infants aged 3- to 8- months, but there was a significant difference between the scores for the Experimental Condition (M = 0.4303; SD = .244) and the Control Condition (M = 0.2965; SD = .230) during the second test trial; t(87) = 2.596, p = 0.011, d = 0.278. In addition, there was a significant difference in the scores for Experimental (M=0.4827, SD = 0.268) and Control (M = 0.326, SD = 0.171) Conditions during the third test trial; t(87) = 3.099, p =0.002, d = 0.332. Additionally, there was a significant difference between the percent-to-center looking times for Trial 1 (M= 0.302, SD = 0.196) and Trial 2 (M = 0.430, SD = 0.244); t(52) = -3.896, p < .01, d = -0.540; and Trial 1 and Trial 3 (M = 0.483, SD = 0.268); t(52) = -4.099, p ˂.01, d = -0.568 for infants aged 12- to 18- months. This suggests that infants aged 12- to 18- months, but not 3- to 8- months, are able to use functional information to establish categories and use this functional category information to later individuate objects based on function. Advisors/Committee Members: Wilcox, Teresa (advisor), Heffer, Robert W (advisor), Riccio, Cynthia (committee member).

Subjects/Keywords: Infant development; object categorization; object individuation; eye-tracking

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APA (6^th Edition):

Nyman, T. (2018). Object Individuation Using Function in Infancy: An Eye-Tracking Study. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/174426

Chicago Manual of Style (16^th Edition):

Nyman, Tristin. “Object Individuation Using Function in Infancy: An Eye-Tracking Study.” 2018. Masters Thesis, Texas A&M University. Accessed March 08, 2021. http://hdl.handle.net/1969.1/174426.

MLA Handbook (7^th Edition):

Nyman, Tristin. “Object Individuation Using Function in Infancy: An Eye-Tracking Study.” 2018. Web. 08 Mar 2021.

Vancouver:

Nyman T. Object Individuation Using Function in Infancy: An Eye-Tracking Study. [Internet] [Masters thesis]. Texas A&M University; 2018. [cited 2021 Mar 08]. Available from: http://hdl.handle.net/1969.1/174426.

Council of Science Editors:

Nyman T. Object Individuation Using Function in Infancy: An Eye-Tracking Study. [Masters Thesis]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/174426

Rochester Institute of Technology

20. 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 March 08, 2021. 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. 08 Mar 2021.

Vancouver:

Li F. Optimizations and applications in head-mounted video-based eye tracking. [Internet] [Thesis]. Rochester Institute of Technology; 2011. [cited 2021 Mar 08]. 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

21. 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: 004; Object Tracking; Computer Vision; Segmentation; Initialisation; Single-Target Tracking

10 more images…

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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 March 08, 2021. 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. 08 Mar 2021.

Vancouver:

De Ath G. Object tracking in video with part-based tracking by feature sampling. [Internet] [Doctoral dissertation]. University of Exeter; 2019. [cited 2021 Mar 08]. 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

Universidade Nova

22. 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

►

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)

▼

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 March 08, 2021. 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. 08 Mar 2021.

Vancouver:

Silva JMFd. People and object tracking for video annotation. [Internet] [Thesis]. Universidade Nova; 2012. [cited 2021 Mar 08]. 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

University of Western Ontario

23. 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 March 08, 2021. 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. 08 Mar 2021.

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 2021 Mar 08]. 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

York University

24. Chen, Bao Xin. Real-Time Online Human Tracking with a Stereo Camera for Person-Following Robots.

Degree: MSc -MS, Computer Science, 2020, York University

URL: https://yorkspace.library.yorku.ca/xmlui/handle/10315/37376

► Person-Following Robots have been studied for multiple decades now. Recently, person-following robots have relied on various sensors (e.g., radar, infrared, laser, ultrasonic, etc). However, these… (more)

Subjects/Keywords: Robotics; Person-following robots; Human following; Human tracking; Object tracking

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APA (6^th Edition):

Chen, B. X. (2020). Real-Time Online Human Tracking with a Stereo Camera for Person-Following Robots. (Masters Thesis). York University. Retrieved from https://yorkspace.library.yorku.ca/xmlui/handle/10315/37376

Chicago Manual of Style (16^th Edition):

Chen, Bao Xin. “Real-Time Online Human Tracking with a Stereo Camera for Person-Following Robots.” 2020. Masters Thesis, York University. Accessed March 08, 2021. https://yorkspace.library.yorku.ca/xmlui/handle/10315/37376.

MLA Handbook (7^th Edition):

Chen, Bao Xin. “Real-Time Online Human Tracking with a Stereo Camera for Person-Following Robots.” 2020. Web. 08 Mar 2021.

Vancouver:

Chen BX. Real-Time Online Human Tracking with a Stereo Camera for Person-Following Robots. [Internet] [Masters thesis]. York University; 2020. [cited 2021 Mar 08]. Available from: https://yorkspace.library.yorku.ca/xmlui/handle/10315/37376.

Council of Science Editors:

Chen BX. Real-Time Online Human Tracking with a Stereo Camera for Person-Following Robots. [Masters Thesis]. York University; 2020. Available from: https://yorkspace.library.yorku.ca/xmlui/handle/10315/37376

King Abdullah University of Science and Technology

25. Mueller, Matthias. Persistent Aerial Tracking.

Degree: Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, 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 March 08, 2021. 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. 08 Mar 2021.

Vancouver:

Mueller M. Persistent Aerial Tracking. [Internet] [Thesis]. King Abdullah University of Science and Technology; 2016. [cited 2021 Mar 08]. 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

26. Ambardekar, Amol. Vehicle Classification Framework: Online Classification with Tracking.

Degree: 2012, University of Nevada – Reno

URL: http://hdl.handle.net/11714/3546

► Video surveillance has significant application prospects such as security, law enforcement, and traffic monitoring. Visual traffic surveillance using computer vision techniques can be non-invasive, cost… (more)

▼ Video surveillance has significant application prospects such as security, law enforcement, and traffic monitoring. Visual traffic surveillance using computer vision techniques can be non-invasive, cost effective and automated. Detecting and recognizing the objects in a video is an important part of many video surveillance systems which can help in tracking of the detected objects and gathering important information. In case of traffic video surveillance, vehicle detection and classification is important as it can help in traffic control and gathering of traffic statistics that can be used in intelligent transportation systems. Vehicle classification poses a difficult problem as vehicles have high intra class variation and relatively low inter class variation. In this work, we investigate five different object recognition techniques: PCA+DFVS, PCA+DIVS, PCA+SVM, LDA, and constellation based modeling applied to the problem of vehicle classification. We also compare them with the state-of-the-art techniques in vehicle classification. In case of the PCA based approaches, we extend face detection using a PCA approach for the problem of vehicle classification to carry out multi-class classification. We also implement constellation model-based approach that uses the dense representation of SIFT features. We consider three classes: sedans, vans, and taxis and record classification accuracy as high as 99.25% in case of cars vs vans and 97.57% in case of sedans vs taxis. We also present a fusion approach that uses both PCA+DFVS and PCA+DIVS and achieves classification accuracy of 96.42% in case of sedans vs vans vs taxis. We incorporated three of the techniques that performed well into a unified traffic surveillance system for online classification of vehicles which uses tracking results to improve the classification accuracy. We processed 31 minutes of traffic video containing multi-lane traffic intersection to evaluate the accuracy of the system. We were able to achieve classification accuracy as high as 90.49% while classifying correctly tracked vehicles into four classes: Cars, SUVs/Vans, Pickup Trucks, and Buses/Semis. While processing a video, our system also records important traffic parameters such as color of a vehicle, speed of a vehicle, etc. This information was later used in a search assistant tool (SAT) to find interesting traffic events. For the evaluation of video surveillance applications that employ an object classification module, it is important to establish the ground truth. However, it is a time consuming process when done manually. We developed a ground truth verification tool (GTVT) that can help in this process by automating some of the work. Advisors/Committee Members: Nicolescu, Mircea (advisor), Bebis, George (committee member), Nicolescu, Monica (committee member), Tian, Zong (committee member), Pinsky, Mark (committee member).

Subjects/Keywords: Computer Vision; Object Classification; Object Recognition; Object Tracking; Traffic Surveillance; Video Surveillance

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APA (6^th Edition):

Ambardekar, A. (2012). Vehicle Classification Framework: Online Classification with Tracking. (Thesis). University of Nevada – Reno. Retrieved from http://hdl.handle.net/11714/3546

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):

Ambardekar, Amol. “Vehicle Classification Framework: Online Classification with Tracking.” 2012. Thesis, University of Nevada – Reno. Accessed March 08, 2021. http://hdl.handle.net/11714/3546.

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

MLA Handbook (7^th Edition):

Ambardekar, Amol. “Vehicle Classification Framework: Online Classification with Tracking.” 2012. Web. 08 Mar 2021.

Vancouver:

Ambardekar A. Vehicle Classification Framework: Online Classification with Tracking. [Internet] [Thesis]. University of Nevada – Reno; 2012. [cited 2021 Mar 08]. Available from: http://hdl.handle.net/11714/3546.

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

Council of Science Editors:

Ambardekar A. Vehicle Classification Framework: Online Classification with Tracking. [Thesis]. University of Nevada – Reno; 2012. Available from: http://hdl.handle.net/11714/3546

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

Clemson University

27. Hunde, Andinet Negash. Multi Sensor Multi Target Perception and Tracking for Informed Decisions in Public Road Scenarios.

Degree: PhD, Automotive Engineering, 2020, Clemson University

URL: https://tigerprints.clemson.edu/all_dissertations/2692

► Multi-target tracking in public traffic calls for a tracking system with automated track initiation and termination facilities in a randomly evolving driving environment. Besides,… (more)

▼ Multi-target tracking in public traffic calls for a tracking system with automated track initiation and termination facilities in a randomly evolving driving environment. Besides, the key problem of data association needs to be handled effectively considering the limitations in the computational resources on-board an autonomous car. The challenge of the tracking problem is further evident in the use of high-resolution automotive sensors which return multiple detections per object. Furthermore, it is customary to use multiple sensors that cover different and/or over-lapping Field of View and fuse sensor detections to provide robust and reliable tracking. As a consequence, in high-resolution multi-sensor settings, the data association uncertainty, and the corresponding tracking complexity increases pointing to a systematic approach to handle and process sensor detections. In this work, we present a multi-target tracking system that addresses target birth/initiation and death/termination processes with automatic track management features. These tracking functionalities can help facilitate perception during common events in public traffic as participants (suddenly) change lanes, navigate intersections, overtake and/or brake in emergencies, etc. Various tracking approaches including the ones based on joint integrated probability data association (JIPDA) filter, Linear Multi-target Integrated Probabilistic Data Association (LMIPDA) Filter, and their multi-detection variants are adapted to specifically include algorithms that handle track initiation and termination, clutter density estimation and track management. The utility of the filtering module is further elaborated by integrating it into a trajectory tracking problem based on model predictive control. To cope with tracking complexity in the case of multiple high-resolution sensors, we propose a hybrid scheme that combines the approaches of data clustering at the local sensor and multiple detections tracking schemes at the fusion layer. We implement a track-to-track fusion scheme that de-correlates local (sensor) tracks to avoid double counting and apply a measurement partitioning scheme to re-purpose the LMIPDA tracking algorithm to multi-detection cases. In addition to the measurement partitioning approach, a joint extent and kinematic state estimation scheme are integrated into the LMIPDA approach to facilitate perception and tracking of an individual as well as group targets as applied to multi-lane public traffic. We formulate the tracking problem as a two hierarchical layer. This arrangement enhances the multi-target tracking performance in situations including but not limited to target initialization(birth process), target occlusion, missed detections, unresolved measurement, target maneuver, etc. Also, target groups expose complex individual target interactions to help in situation assessment which is challenging to capture otherwise. The simulation studies are complemented by experimental studies performed on single and… Advisors/Committee Members: Yunyi Jia, Zoran Filipi, Ioannis Karamouzas, Bing Li.

Subjects/Keywords: Autonomous Perception and Tracking; Camera and Radar Sensor Fusion; Extended Object Tracking; Group Target Tracking; Multi-Target Tracking; Public Traffic

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APA (6^th Edition):

Hunde, A. N. (2020). Multi Sensor Multi Target Perception and Tracking for Informed Decisions in Public Road Scenarios. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_dissertations/2692

Chicago Manual of Style (16^th Edition):

Hunde, Andinet Negash. “Multi Sensor Multi Target Perception and Tracking for Informed Decisions in Public Road Scenarios.” 2020. Doctoral Dissertation, Clemson University. Accessed March 08, 2021. https://tigerprints.clemson.edu/all_dissertations/2692.

MLA Handbook (7^th Edition):

Hunde, Andinet Negash. “Multi Sensor Multi Target Perception and Tracking for Informed Decisions in Public Road Scenarios.” 2020. Web. 08 Mar 2021.

Vancouver:

Hunde AN. Multi Sensor Multi Target Perception and Tracking for Informed Decisions in Public Road Scenarios. [Internet] [Doctoral dissertation]. Clemson University; 2020. [cited 2021 Mar 08]. Available from: https://tigerprints.clemson.edu/all_dissertations/2692.

Council of Science Editors:

Hunde AN. Multi Sensor Multi Target Perception and Tracking for Informed Decisions in Public Road Scenarios. [Doctoral Dissertation]. Clemson University; 2020. Available from: https://tigerprints.clemson.edu/all_dissertations/2692

28. 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 March 08, 2021. 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. 08 Mar 2021.

Vancouver:

Shanmuga Vadivel K. Modeling Eye Tracking Data with Application to Object Detection. [Internet] [Thesis]. University of California – eScholarship, University of California; 2014. [cited 2021 Mar 08]. 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

UCLA

29. Taylor, Brian. Leveraging Occlusion Cues for Causal Video Object Segmentation.

Degree: Computer Science, 2016, UCLA

URL: http://www.escholarship.org/uc/item/3xz0z5k9

► This thesis describes a framework leveraging occlusions as a cue for detecting objects and accurately localizing their boundaries throughout the course of a video. Triggered… (more)

Subjects/Keywords: Computer science; depth layer segmentation; object tracking; occlusions; video object segmentation; video segmentation

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APA (6^th Edition):

Taylor, B. (2016). Leveraging Occlusion Cues for Causal Video Object Segmentation. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/3xz0z5k9

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):

Taylor, Brian. “Leveraging Occlusion Cues for Causal Video Object Segmentation.” 2016. Thesis, UCLA. Accessed March 08, 2021. http://www.escholarship.org/uc/item/3xz0z5k9.

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

MLA Handbook (7^th Edition):

Taylor, Brian. “Leveraging Occlusion Cues for Causal Video Object Segmentation.” 2016. Web. 08 Mar 2021.

Vancouver:

Taylor B. Leveraging Occlusion Cues for Causal Video Object Segmentation. [Internet] [Thesis]. UCLA; 2016. [cited 2021 Mar 08]. Available from: http://www.escholarship.org/uc/item/3xz0z5k9.

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

Council of Science Editors:

Taylor B. Leveraging Occlusion Cues for Causal Video Object Segmentation. [Thesis]. UCLA; 2016. Available from: http://www.escholarship.org/uc/item/3xz0z5k9

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

30. Budi, Sugandi. Study on Object Tracking Under Outdoor Environments Using Video Cameras : ビデオカメラを用いた屋外環境下での物体追跡に関する研究.

Degree: 博士（工学）, 2017, Kyushu Institute of Technology / 九州工業大学

URL: http://hdl.handle.net/10228/4886

► In this thesis, we investigated the development of the object tracking system including object detection, object tracking and object identification/recognition and related issues. We explored… (more)

Subjects/Keywords: Object tracking; PISC image; Particle filter; Color feature; Object occlusion; Multi-camera

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

APA (6^th Edition):

Budi, S. (2017). Study on Object Tracking Under Outdoor Environments Using Video Cameras : ビデオカメラを用いた屋外環境下での物体追跡に関する研究. (Thesis). Kyushu Institute of Technology / 九州工業大学. Retrieved from http://hdl.handle.net/10228/4886

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):

Budi, Sugandi. “Study on Object Tracking Under Outdoor Environments Using Video Cameras : ビデオカメラを用いた屋外環境下での物体追跡に関する研究.” 2017. Thesis, Kyushu Institute of Technology / 九州工業大学. Accessed March 08, 2021. http://hdl.handle.net/10228/4886.

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

MLA Handbook (7^th Edition):

Budi, Sugandi. “Study on Object Tracking Under Outdoor Environments Using Video Cameras : ビデオカメラを用いた屋外環境下での物体追跡に関する研究.” 2017. Web. 08 Mar 2021.

Vancouver:

Budi S. Study on Object Tracking Under Outdoor Environments Using Video Cameras : ビデオカメラを用いた屋外環境下での物体追跡に関する研究. [Internet] [Thesis]. Kyushu Institute of Technology / 九州工業大学; 2017. [cited 2021 Mar 08]. Available from: http://hdl.handle.net/10228/4886.

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

Council of Science Editors:

Budi S. Study on Object Tracking Under Outdoor Environments Using Video Cameras : ビデオカメラを用いた屋外環境下での物体追跡に関する研究. [Thesis]. Kyushu Institute of Technology / 九州工業大学; 2017. Available from: http://hdl.handle.net/10228/4886

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

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