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Massachusetts Institute of Technology

Multiple mice tracking using Microsoft Kinect

Abstract

dc:description.abstract

Mouse tracking is integral to any attempt to automate mouse behavioral analysis in neuroscience. Systems that rely on vision have successfully tracked a single mouse in one cage[10], but when attempting to track multiple mice, video-based systems often struggle when the mice interact physically. In this thesis, I develop a novel vision-based tracking system that addresses the challenge of tracking multiple deformable mice with identical appearance, especially during complex occlusions. The system integrates both image and depth modalities to identify the boundary of two occluding mice, and then performs pose estimation to locate nose and tail locations of each mouse. Detailed performance evaluation shows that the system is robust and reliable, with low rate of identity swap after each occlusion event and accurate pose estimation during occlusion. To evaluate the tracking system, I introduce a dataset containing two 30-minute videos recorded with Microsoft's Kinect from the top view. Each video records the social reciprocal experiment of a pair of mice. I also explore applying the new tracking system to automated social behavior analysis, by detecting social interactions defined with position- and orientation-based features from tracking data. The preliminary results enable us to characterize lowered social activity of the Shank3 knockout mouse, and demonstrate the potential of this system for quantitaive study of mice social behavior.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2013

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Wang, Chun-Kai, M. Eng. Massachusetts Institute of Technology
Advisor dc:contributor.advisor
  • Tomaso Poggio.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • 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.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/85517
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/85517

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Wang, Chun-Kai, M. Eng. Massachusetts Institute of Technology. Multiple mice tracking using Microsoft Kinect. Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/85517