Tracking People in Meetings with Particles

Automatic meeting analysis is an emerging research field. In this paper, we present stochastic algorithms for tracking people in multi-sensor meeting rooms, for a number of relevant tasks, including tracking multiple people, tracking head pose towards analysis of visual focus-of-attention, and tracking speaker activity using audio-visual information. A Bayesian framework based on Sequential Monte Carlo methods is used in all cases. We discuss the advantages and limitations of our approach, illustrate it with results, and highlight a number of open issues.


Année
2004
Publisher:
Martigny, Switzerland, IDIAP
Mots-clefs:
Note:
in Proc. Int. Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS), invited paper, Montreux, Apr. 2005.
Laboratoires:




 Notice créée le 2006-03-10, modifiée le 2018-03-17

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