Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
FlyCam: practical panoramic video
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Catadioptric Omnidirectional Camera
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
The Representation and Recognition of Human Movement Using Temporal Templates
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Multi-Camera Networks: Eyes from Eyes
OMNIVIS '00 Proceedings of the IEEE Workshop on Omnidirectional Vision
Frame-Rate Omnidirectional Surveillance & Tracking of Camouflaged and Occluded Targets
VS '99 Proceedings of the Second IEEE Workshop on Visual Surveillance
Multi-Camera Multi-Person Tracking for EasyLiving
VS '00 Proceedings of the Third IEEE International Workshop on Visual Surveillance (VS'2000)
Hydra: Multiple People Detection and Tracking Using Silhouettes
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
A Multi-Agent Framework for Visual Surveillance
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
A Theory of Catadioptric Image Formation
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Survey and analysis of multimodal sensor planning and integration for wide area surveillance
ACM Computing Surveys (CSUR)
Smart meeting systems: A survey of state-of-the-art and open issues
ACM Computing Surveys (CSUR)
Inferring social activities with mobile sensor networks
Proceedings of the 15th ACM on International conference on multimodal interaction
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In this paper we propose an approach for monitoring human activities in an indoor environment using an omnidirectional camera. Robustly tracking people is prerequisite for modeling and recognizing human activities. An omnidirectional camera mounted on the ceiling is less prone to problems of occlusion. We use the Markov Random Field (MRF) to present both background and foreground, and adapt models effectively against environment changes. We employ a deformable model to adapt the foreground models to optimally match objects in different position within a pattern of view of omnidirectional camera. In order to monitor human activity, we represent positions of people as spatial points and analyze moving trajectories within a time-spatial window. The method provides an efficient way to monitoring high-level human activities without exploring identities.