Learning to Track Multiple People in Omnidirectional Video

Fernando De la Torre Frade, Carlos Vallespi-Gonzalez, Paul Rybski, Manuela Veloso, and Takeo Kanade
Proceedings of the 2005 IEEE International Conference on Robotics and Automation (ICRA-2005), April, 2005, pp. 4150 - 4155.


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Abstract
Meetings are a very important part of everyday life for professionals working in universities, companies or governmental institutions. We have designed a physical awareness system called CAMEO (Camera Assisted Meeting Event Observer), a hardware/software system to record and monitor people's activities in meetings. CAMEO captures a high resolution omnidirectional view of the meeting by stitching images coming from almost concentric cameras. Besides recording capability, CAMEO automatically detects people and learns a person-specific facial appearance model (PSFAM) for each of the participants. The PSFAMs allow more robust/reliable tracking and identification. In this paper, we describe the video-capturing device, photometric/geometric autocalibration process, and the multiple people tracking system. The effectiveness and robustness of the proposed system is demonstrated over several real-time experiments and a large data set of videos.

Keywords
Omnidirectional-video capturing, Multiple people tracking, Subspace methods, Meeting understanding, Person-specific models.

Notes
Sponsor: DARPA
Associated Center(s) / Consortia: Vision and Autonomous Systems Center
Associated Lab(s) / Group(s): People Image Analysis Consortium and MultiRobot Lab
Associated Project(s): Camera Assisted Meeting Event Observer
Number of pages: 6

Text Reference
Fernando De la Torre Frade, Carlos Vallespi-Gonzalez, Paul Rybski, Manuela Veloso, and Takeo Kanade, "Learning to Track Multiple People in Omnidirectional Video," Proceedings of the 2005 IEEE International Conference on Robotics and Automation (ICRA-2005), April, 2005, pp. 4150 - 4155.

BibTeX Reference
@inproceedings{De_la_Torre_Frade_2005_4910,
   author = "Fernando {De la Torre Frade} and Carlos Vallespi-Gonzalez and Paul Rybski and Manuela Veloso and Takeo Kanade",
   title = "Learning to Track Multiple People in Omnidirectional Video",
   booktitle = "Proceedings of the 2005 IEEE International Conference on Robotics and Automation (ICRA-2005)",
   pages = "4150 - 4155",
   month = "April",
   year = "2005",
}