Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
The visual analysis of human movement: a survey
Computer Vision and Image Understanding
Multimodal people ID for a multimedia meeting browser
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Viewing meeting captured by an omni-directional camera
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
FlyCam: practical panoramic video
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Proceedings of the tenth ACM international conference on Multimedia
Non-parametric Model for Background Subtraction
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
WACV '96 Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96)
Image segmentation in video sequences: a probabilistic approach
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Proceedings of the tenth ACM international conference on Multimedia
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We have developed a meeting recorder system which captures a panoramic video of a meeting room. Segmentation of people from this video is required for tracking and retrieval applications. However, the application scenario makes it difficult to rely on the usual solution of static background initialization and purely motion-based tracking for segmenting people. In this paper, we describe a novel framework for segmenting people in these videos using adaptive Gaussian mixtures for both background and object modeling. Based on a Bayesian formulation of the problem, results of object segmentation provide feedback to the background segmentation module. Experimental results on real meeting videos are presented.