Tracking multiple mice
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2013
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| Online Access: | http://hdl.handle.net/1721.1/77001 |
| _version_ | 1826191122258460672 |
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| author | Braun, Stav |
| author2 | Tomaso Poggio. |
| author_facet | Tomaso Poggio. Braun, Stav |
| author_sort | Braun, Stav |
| collection | MIT |
| description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012. |
| first_indexed | 2024-09-23T08:50:51Z |
| format | Thesis |
| id | mit-1721.1/77001 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T08:50:51Z |
| publishDate | 2013 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/770012019-04-10T19:22:01Z Tracking multiple mice Braun, Stav 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 (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012. Cataloged from PDF version of thesis. Includes bibliographical references (p. 59-62). Monitoring mouse social behaviors over long periods of time is essential for neurobehavioral analysis of social mouse phenotypes. Currently, the primary method of social behavioral plienotyping utilizes human labelers, which is slow and costly. In order to achieve the high throughput desired for scientific studies, social behavioral phenotyping must be automated. The problem of automation can be divided into two tasks; tracking and phenotyping. First, individual body parts of mice must be accurately tracked. This is achieved using shape context descriptors to obtain precise point to point correspondences between templates and mice in any frame of a video. This method provides for greater precision and accuracy than current state of the art techniques. We propose a means by which this tracking information can be used to classify social behaviors between mice. by Stav Braun. M.Eng. 2013-02-14T15:36:58Z 2013-02-14T15:36:58Z 2012 2012 Thesis http://hdl.handle.net/1721.1/77001 825558388 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 62 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Braun, Stav Tracking multiple mice |
| title | Tracking multiple mice |
| title_full | Tracking multiple mice |
| title_fullStr | Tracking multiple mice |
| title_full_unstemmed | Tracking multiple mice |
| title_short | Tracking multiple mice |
| title_sort | tracking multiple mice |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/77001 |
| work_keys_str_mv | AT braunstav trackingmultiplemice |