A biologically inspired system for action recognition
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.
| Main Author: | |
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2008
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| Online Access: | http://hdl.handle.net/1721.1/42247 |
| _version_ | 1811079177887023104 |
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| author | Jhuang, Hueihan |
| author2 | Tomaso Poggio. |
| author_facet | Tomaso Poggio. Jhuang, Hueihan |
| author_sort | Jhuang, Hueihan |
| collection | MIT |
| description | Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007. |
| first_indexed | 2024-09-23T11:11:06Z |
| format | Thesis |
| id | mit-1721.1/42247 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T11:11:06Z |
| publishDate | 2008 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/422472019-04-10T13:56:45Z A biologically inspired system for action recognition Jhuang, Hueihan Tomaso Poggio. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007. Includes bibliographical references (p. 51-58). We present a biologically-motivated system for the recognition of actions from video sequences. The approach builds on recent work on object recognition based on hierarchical feedforward architectures and extends a neurobiological model of motion processing in the visual cortex. The system consists of a hierarchy of spatio-temporal feature detectors of increasing complexity: an input sequence is first analyzed by an array of motion-direction sensitive units which, through a hierarchy of processing stages, lead to position-invariant spatio-temporal feature detectors. We experiment with different types of motion-direction sensitive units as well as different system architectures. Besides, we find that sparse features in intermediate stages outperform dense ones and that using a simple feature selection approach leads to an efficient system that performs better with far fewer features. We test the approach on different publicly available action datasets, in all cases achieving the best results reported to date. by Hueihan Jhuang. S.M. 2008-09-03T15:04:11Z 2008-09-03T15:04:11Z 2007 2007 Thesis http://hdl.handle.net/1721.1/42247 231634026 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 58 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Jhuang, Hueihan A biologically inspired system for action recognition |
| title | A biologically inspired system for action recognition |
| title_full | A biologically inspired system for action recognition |
| title_fullStr | A biologically inspired system for action recognition |
| title_full_unstemmed | A biologically inspired system for action recognition |
| title_short | A biologically inspired system for action recognition |
| title_sort | biologically inspired system for action recognition |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/42247 |
| work_keys_str_mv | AT jhuanghueihan abiologicallyinspiredsystemforactionrecognition AT jhuanghueihan biologicallyinspiredsystemforactionrecognition |