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You searched for +publisher:"University of Texas – Austin" +contributor:("Aggarwal, J K."). Showing records 1 – 17 of 17 total matches.

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University of Texas – Austin

1. Yu, Qingfeng. Human extremity detection and its applications in action detection and recognition.

Degree: Electrical and Computer Engineering, 2009, University of Texas – Austin

 It is proven that locations of internal body joints are sufficient visual cues to characterize human motion. In this dissertation I propose that locations of… (more)

Subjects/Keywords: Human extremity detection; Action detection; Contour tracking; Human action recognition; Motion detection

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

APA (6th Edition):

Yu, Q. (2009). Human extremity detection and its applications in action detection and recognition. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/7650

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

Chicago Manual of Style (16th Edition):

Yu, Qingfeng. “Human extremity detection and its applications in action detection and recognition.” 2009. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/7650.

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

MLA Handbook (7th Edition):

Yu, Qingfeng. “Human extremity detection and its applications in action detection and recognition.” 2009. Web. 21 Apr 2019.

Vancouver:

Yu Q. Human extremity detection and its applications in action detection and recognition. [Internet] [Thesis]. University of Texas – Austin; 2009. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/7650.

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

Council of Science Editors:

Yu Q. Human extremity detection and its applications in action detection and recognition. [Thesis]. University of Texas – Austin; 2009. Available from: http://hdl.handle.net/2152/7650

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

2. Xia, Lu, active 21st century. Recognizing human activity using RGBD data.

Degree: Electrical and Computer Engineering, 2014, University of Texas – Austin

 Traditional computer vision algorithms try to understand the world using visible light cameras. However, there are inherent limitations of this type of data source. First,… (more)

Subjects/Keywords: Activity recognition; RGBD; Depth sensing; 3D; Human detection; First-person; Human interaction

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APA (6th Edition):

Xia, Lu, a. 2. c. (2014). Recognizing human activity using RGBD data. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/24981

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

Chicago Manual of Style (16th Edition):

Xia, Lu, active 21st century. “Recognizing human activity using RGBD data.” 2014. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/24981.

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

MLA Handbook (7th Edition):

Xia, Lu, active 21st century. “Recognizing human activity using RGBD data.” 2014. Web. 21 Apr 2019.

Vancouver:

Xia, Lu a2c. Recognizing human activity using RGBD data. [Internet] [Thesis]. University of Texas – Austin; 2014. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/24981.

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

Council of Science Editors:

Xia, Lu a2c. Recognizing human activity using RGBD data. [Thesis]. University of Texas – Austin; 2014. Available from: http://hdl.handle.net/2152/24981

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


University of Texas – Austin

3. Jain, Suyog Dutt. Facial expression recognition with temporal modeling of shapes.

Degree: Computer Sciences, 2011, University of Texas – Austin

 Conditional Random Fields (CRFs) is a discriminative and supervised approach for simultaneous sequence segmentation and frame labeling. Latent-Dynamic Conditional Random Fields (LDCRFs) incorporates hidden state… (more)

Subjects/Keywords: Facial expression recognition; Temporal modeling; Procrustes analysis

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APA (6th Edition):

Jain, S. D. (2011). Facial expression recognition with temporal modeling of shapes. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-08-4279

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

Chicago Manual of Style (16th Edition):

Jain, Suyog Dutt. “Facial expression recognition with temporal modeling of shapes.” 2011. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/ETD-UT-2011-08-4279.

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

MLA Handbook (7th Edition):

Jain, Suyog Dutt. “Facial expression recognition with temporal modeling of shapes.” 2011. Web. 21 Apr 2019.

Vancouver:

Jain SD. Facial expression recognition with temporal modeling of shapes. [Internet] [Thesis]. University of Texas – Austin; 2011. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-08-4279.

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

Council of Science Editors:

Jain SD. Facial expression recognition with temporal modeling of shapes. [Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-08-4279

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


University of Texas – Austin

4. Tamersoy, Birgi. Vehicle detection and tracking in highway surveillance videos.

Degree: Electrical and Computer Engineering, 2009, University of Texas – Austin

 We present a novel approach for vehicle detection and tracking in highway surveillance videos. This method incorporates well-studied computer vision and machine learning techniques to… (more)

Subjects/Keywords: vehicle detection; vehicle tracking; highway surveillance; traffic monitoring; unsupervised learning

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APA (6th Edition):

Tamersoy, B. (2009). Vehicle detection and tracking in highway surveillance videos. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2009-08-316

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

Chicago Manual of Style (16th Edition):

Tamersoy, Birgi. “Vehicle detection and tracking in highway surveillance videos.” 2009. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/ETD-UT-2009-08-316.

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

MLA Handbook (7th Edition):

Tamersoy, Birgi. “Vehicle detection and tracking in highway surveillance videos.” 2009. Web. 21 Apr 2019.

Vancouver:

Tamersoy B. Vehicle detection and tracking in highway surveillance videos. [Internet] [Thesis]. University of Texas – Austin; 2009. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/ETD-UT-2009-08-316.

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

Council of Science Editors:

Tamersoy B. Vehicle detection and tracking in highway surveillance videos. [Thesis]. University of Texas – Austin; 2009. Available from: http://hdl.handle.net/2152/ETD-UT-2009-08-316

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


University of Texas – Austin

5. Chen, Chao-Yeh. Clues from the beaten path : location estimation with bursty sequences of tourist photos: Location estimation with bursty sequences of tourist photos.

Degree: Electrical and Computer Engineering, 2010, University of Texas – Austin

 Existing methods for image-based location estimation generally attempt to recognize every photo independently, and their resulting reliance on strong visual feature matches makes them most… (more)

Subjects/Keywords: Location estimation; Hidden Markov Model; Object recognition

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APA (6th Edition):

Chen, C. (2010). Clues from the beaten path : location estimation with bursty sequences of tourist photos: Location estimation with bursty sequences of tourist photos. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-12-2301

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

Chicago Manual of Style (16th Edition):

Chen, Chao-Yeh. “Clues from the beaten path : location estimation with bursty sequences of tourist photos: Location estimation with bursty sequences of tourist photos.” 2010. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/ETD-UT-2010-12-2301.

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

MLA Handbook (7th Edition):

Chen, Chao-Yeh. “Clues from the beaten path : location estimation with bursty sequences of tourist photos: Location estimation with bursty sequences of tourist photos.” 2010. Web. 21 Apr 2019.

Vancouver:

Chen C. Clues from the beaten path : location estimation with bursty sequences of tourist photos: Location estimation with bursty sequences of tourist photos. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-12-2301.

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

Council of Science Editors:

Chen C. Clues from the beaten path : location estimation with bursty sequences of tourist photos: Location estimation with bursty sequences of tourist photos. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-12-2301

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


University of Texas – Austin

6. Jun, Goo. Transfer learning for classification of spatially varying data.

Degree: Electrical and Computer Engineering, 2010, University of Texas – Austin

 Many real-world datasets have spatial components that provide valuable information about characteristics of the data. In this dissertation, a novel framework for adaptive models that… (more)

Subjects/Keywords: Machine learning; Classification and semi-supervised learning algorithms; Gaussian processes; Gaussian process regressions; Spatial statistics

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APA (6th Edition):

Jun, G. (2010). Transfer learning for classification of spatially varying data. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-08-1962

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

Chicago Manual of Style (16th Edition):

Jun, Goo. “Transfer learning for classification of spatially varying data.” 2010. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/ETD-UT-2010-08-1962.

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

MLA Handbook (7th Edition):

Jun, Goo. “Transfer learning for classification of spatially varying data.” 2010. Web. 21 Apr 2019.

Vancouver:

Jun G. Transfer learning for classification of spatially varying data. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1962.

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

Council of Science Editors:

Jun G. Transfer learning for classification of spatially varying data. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1962

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


University of Texas – Austin

7. Vijayanarasimhan, Sudheendra. Active visual category learning.

Degree: Computer Sciences, 2011, University of Texas – Austin

 Visual recognition research develops algorithms and representations to autonomously recognize visual entities such as objects, actions, and attributes. The traditional protocol involves manually collecting training… (more)

Subjects/Keywords: Artificial intelligence; Active learning; Object recognition; Object detection; Cost-sensitive learning; Multi-level learning; Budgeted learning; Large-scale active learning; Live learning; Machine learning; Visual recognition system

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APA (6th Edition):

Vijayanarasimhan, S. (2011). Active visual category learning. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-05-3014

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

Chicago Manual of Style (16th Edition):

Vijayanarasimhan, Sudheendra. “Active visual category learning.” 2011. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/ETD-UT-2011-05-3014.

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

MLA Handbook (7th Edition):

Vijayanarasimhan, Sudheendra. “Active visual category learning.” 2011. Web. 21 Apr 2019.

Vancouver:

Vijayanarasimhan S. Active visual category learning. [Internet] [Thesis]. University of Texas – Austin; 2011. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3014.

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

Council of Science Editors:

Vijayanarasimhan S. Active visual category learning. [Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3014

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


University of Texas – Austin

8. Coffman, Thayne Richard. Stochastic methods in computational stereo.

Degree: Electrical and Computer Engineering, 2011, University of Texas – Austin

 Computational stereo estimates 3D structure by analyzing visual changes between two or more passive images of a scene that are captured from different viewpoints. It… (more)

Subjects/Keywords: Computational stereo; Stereo vision; Multi-view stereo; Stochastic approximation; Hough transform; Distributed ray tracing; Autonomous systems; Object recognition

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APA (6th Edition):

Coffman, T. R. (2011). Stochastic methods in computational stereo. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-05-2702

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

Chicago Manual of Style (16th Edition):

Coffman, Thayne Richard. “Stochastic methods in computational stereo.” 2011. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/ETD-UT-2011-05-2702.

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

MLA Handbook (7th Edition):

Coffman, Thayne Richard. “Stochastic methods in computational stereo.” 2011. Web. 21 Apr 2019.

Vancouver:

Coffman TR. Stochastic methods in computational stereo. [Internet] [Thesis]. University of Texas – Austin; 2011. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-2702.

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

Council of Science Editors:

Coffman TR. Stochastic methods in computational stereo. [Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-2702

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


University of Texas – Austin

9. Lee, Yong Jae, 1984-. Visual object category discovery in images and videos.

Degree: Electrical and Computer Engineering, 2012, University of Texas – Austin

 The current trend in visual recognition research is to place a strict division between the supervised and unsupervised learning paradigms, which is problematic for two… (more)

Subjects/Keywords: Unsupervised learning; Visual category discovery; Image and video segmentation; Video summarization

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APA (6th Edition):

Lee, Yong Jae, 1. (2012). Visual object category discovery in images and videos. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-05-5381

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

Chicago Manual of Style (16th Edition):

Lee, Yong Jae, 1984-. “Visual object category discovery in images and videos.” 2012. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/ETD-UT-2012-05-5381.

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

MLA Handbook (7th Edition):

Lee, Yong Jae, 1984-. “Visual object category discovery in images and videos.” 2012. Web. 21 Apr 2019.

Vancouver:

Lee, Yong Jae 1. Visual object category discovery in images and videos. [Internet] [Thesis]. University of Texas – Austin; 2012. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5381.

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

Council of Science Editors:

Lee, Yong Jae 1. Visual object category discovery in images and videos. [Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5381

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

10. Wan, Shaohua. A scalable metric learning based voting method for expression recognition.

Degree: Electrical and Computer Engineering, 2013, University of Texas – Austin

 In this research work, we propose a facial expression classification method using metric learning-based k-nearest neighbor voting. To achieve accurate classification of a facial expression… (more)

Subjects/Keywords: Facial expression recognition; k Nearest Neighbor; Metric learning; Locality sensitive hashing

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APA (6th Edition):

Wan, S. (2013). A scalable metric learning based voting method for expression recognition. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/21521

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

Chicago Manual of Style (16th Edition):

Wan, Shaohua. “A scalable metric learning based voting method for expression recognition.” 2013. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/21521.

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

MLA Handbook (7th Edition):

Wan, Shaohua. “A scalable metric learning based voting method for expression recognition.” 2013. Web. 21 Apr 2019.

Vancouver:

Wan S. A scalable metric learning based voting method for expression recognition. [Internet] [Thesis]. University of Texas – Austin; 2013. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/21521.

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

Council of Science Editors:

Wan S. A scalable metric learning based voting method for expression recognition. [Thesis]. University of Texas – Austin; 2013. Available from: http://hdl.handle.net/2152/21521

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

11. Ryoo, Michael Sahngwon, 1983-. Semantic representation and recognition of human activities.

Degree: Electrical and Computer Engineering, 2008, University of Texas – Austin

 This dissertation describes a methodology for automated recognition of complex human activities. The dissertation presents a general framework which reliably recognizes various types of high-level… (more)

Subjects/Keywords: Optical pattern recognition; Image processing

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APA (6th Edition):

Ryoo, Michael Sahngwon, 1. (2008). Semantic representation and recognition of human activities. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/17742

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

Chicago Manual of Style (16th Edition):

Ryoo, Michael Sahngwon, 1983-. “Semantic representation and recognition of human activities.” 2008. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/17742.

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

MLA Handbook (7th Edition):

Ryoo, Michael Sahngwon, 1983-. “Semantic representation and recognition of human activities.” 2008. Web. 21 Apr 2019.

Vancouver:

Ryoo, Michael Sahngwon 1. Semantic representation and recognition of human activities. [Internet] [Thesis]. University of Texas – Austin; 2008. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/17742.

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

Council of Science Editors:

Ryoo, Michael Sahngwon 1. Semantic representation and recognition of human activities. [Thesis]. University of Texas – Austin; 2008. Available from: http://hdl.handle.net/2152/17742

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


University of Texas – Austin

12. Park, Sangho. A hierarchical graphical model for recognizing human actions and interactions in video.

Degree: Electrical and Computer Engineering, 2004, University of Texas – Austin

 Understanding human behavior in video data is essential in numerous applications including smart surveillance, video annotation/retrieval, and human – computer interaction. Recognizing human interactions is… (more)

Subjects/Keywords: Computer vision; Motion perception (Vision) – Data processing; Electronic surveillance – Data processing; Graphical modeling (Statistics); Bayesian statistical decision theory

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APA (6th Edition):

Park, S. (2004). A hierarchical graphical model for recognizing human actions and interactions in video. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/2160

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

Chicago Manual of Style (16th Edition):

Park, Sangho. “A hierarchical graphical model for recognizing human actions and interactions in video.” 2004. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/2160.

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

MLA Handbook (7th Edition):

Park, Sangho. “A hierarchical graphical model for recognizing human actions and interactions in video.” 2004. Web. 21 Apr 2019.

Vancouver:

Park S. A hierarchical graphical model for recognizing human actions and interactions in video. [Internet] [Thesis]. University of Texas – Austin; 2004. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/2160.

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

Council of Science Editors:

Park S. A hierarchical graphical model for recognizing human actions and interactions in video. [Thesis]. University of Texas – Austin; 2004. Available from: http://hdl.handle.net/2152/2160

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


University of Texas – Austin

13. Sato, Koichi. Temporal spatio-velocity transform and its applications.

Degree: Electrical and Computer Engineering, 2006, University of Texas – Austin

 Object tracking is important in various applications such as video surveillance systems, video annotation systems, and human interaction classification systems. Occlusion and noise are the… (more)

Subjects/Keywords: Automatic tracking; Image processing

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APA (6th Edition):

Sato, K. (2006). Temporal spatio-velocity transform and its applications. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/2637

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

Chicago Manual of Style (16th Edition):

Sato, Koichi. “Temporal spatio-velocity transform and its applications.” 2006. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/2637.

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

MLA Handbook (7th Edition):

Sato, Koichi. “Temporal spatio-velocity transform and its applications.” 2006. Web. 21 Apr 2019.

Vancouver:

Sato K. Temporal spatio-velocity transform and its applications. [Internet] [Thesis]. University of Texas – Austin; 2006. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/2637.

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

Council of Science Editors:

Sato K. Temporal spatio-velocity transform and its applications. [Thesis]. University of Texas – Austin; 2006. Available from: http://hdl.handle.net/2152/2637

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

14. Harguess, Joshua David. Face recognition from video.

Degree: Electrical and Computer Engineering, 2011, University of Texas – Austin

 While the area of face recognition has been extensively studied in recent years, it remains a largely open problem, despite what movie and television studios… (more)

Subjects/Keywords: Face recognition; Computer vision; Face tracking; Face recognition from video; Multiple camera tracking; Multiple camera face recognition; Average half face; Face symmetry

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APA (6th Edition):

Harguess, J. D. (2011). Face recognition from video. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-12-4711

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

Chicago Manual of Style (16th Edition):

Harguess, Joshua David. “Face recognition from video.” 2011. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/ETD-UT-2011-12-4711.

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

MLA Handbook (7th Edition):

Harguess, Joshua David. “Face recognition from video.” 2011. Web. 21 Apr 2019.

Vancouver:

Harguess JD. Face recognition from video. [Internet] [Thesis]. University of Texas – Austin; 2011. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4711.

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

Council of Science Editors:

Harguess JD. Face recognition from video. [Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4711

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

15. Chen, Chia-Chih, 1979-. Recognizing human activities from low-resolution videos.

Degree: Electrical and Computer Engineering, 2011, University of Texas – Austin

 Human activity recognition is one of the intensively studied areas in computer vision. Most existing works do not assume video resolution to be a problem… (more)

Subjects/Keywords: Human activity recognition; Human-vehicle interaction recognition; Low resolution; Aerial view; Distant view; Shadow removal

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

APA (6th Edition):

Chen, Chia-Chih, 1. (2011). Recognizing human activities from low-resolution videos. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-12-4621

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

Chicago Manual of Style (16th Edition):

Chen, Chia-Chih, 1979-. “Recognizing human activities from low-resolution videos.” 2011. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/ETD-UT-2011-12-4621.

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

MLA Handbook (7th Edition):

Chen, Chia-Chih, 1979-. “Recognizing human activities from low-resolution videos.” 2011. Web. 21 Apr 2019.

Vancouver:

Chen, Chia-Chih 1. Recognizing human activities from low-resolution videos. [Internet] [Thesis]. University of Texas – Austin; 2011. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4621.

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

Council of Science Editors:

Chen, Chia-Chih 1. Recognizing human activities from low-resolution videos. [Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4621

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

16. Lee, Jong Taek, 1983-. Recognition of human interactions with vehicles using 3-D models and dynamic context.

Degree: Electrical and Computer Engineering, 2012, University of Texas – Austin

 This dissertation describes two distinctive methods for human-vehicle interaction recognition: one for ground level videos and the other for aerial videos. For ground level videos,… (more)

Subjects/Keywords: Computer vision; Human activity recognition; Vehicle alignment; Human-vehicle interaction; 3-D vehicle model; Event context; Dynamic context; Aerial video analysis

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

APA (6th Edition):

Lee, Jong Taek, 1. (2012). Recognition of human interactions with vehicles using 3-D models and dynamic context. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-05-5002

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

Chicago Manual of Style (16th Edition):

Lee, Jong Taek, 1983-. “Recognition of human interactions with vehicles using 3-D models and dynamic context.” 2012. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/ETD-UT-2012-05-5002.

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

MLA Handbook (7th Edition):

Lee, Jong Taek, 1983-. “Recognition of human interactions with vehicles using 3-D models and dynamic context.” 2012. Web. 21 Apr 2019.

Vancouver:

Lee, Jong Taek 1. Recognition of human interactions with vehicles using 3-D models and dynamic context. [Internet] [Thesis]. University of Texas – Austin; 2012. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5002.

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

Council of Science Editors:

Lee, Jong Taek 1. Recognition of human interactions with vehicles using 3-D models and dynamic context. [Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5002

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

17. LeBorgne, Matthew Ronald. Modeling the post shear failure behavior of reinforced concrete columns.

Degree: Civil, Architectural, and Environmental Engineering, 2012, University of Texas – Austin

 Numerous reinforced concrete buildings vulnerable to earthquake induced collapse have been constructed in seismic zones prior to the 1970s. A major contributor to building collapse… (more)

Subjects/Keywords: Shear failure; Axial failure; Nonlinear analysis; Reinforced concrete columns; Seismic evaluation; Risk assessment; Calibrated model; Dynamic analysis; Degrading behavior; Existing buildings; Poor column details

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

APA (6th Edition):

LeBorgne, M. R. (2012). Modeling the post shear failure behavior of reinforced concrete columns. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-05-4975

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

Chicago Manual of Style (16th Edition):

LeBorgne, Matthew Ronald. “Modeling the post shear failure behavior of reinforced concrete columns.” 2012. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/ETD-UT-2012-05-4975.

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

MLA Handbook (7th Edition):

LeBorgne, Matthew Ronald. “Modeling the post shear failure behavior of reinforced concrete columns.” 2012. Web. 21 Apr 2019.

Vancouver:

LeBorgne MR. Modeling the post shear failure behavior of reinforced concrete columns. [Internet] [Thesis]. University of Texas – Austin; 2012. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-4975.

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

Council of Science Editors:

LeBorgne MR. Modeling the post shear failure behavior of reinforced concrete columns. [Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-4975

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

.