M2Tracker: A Multi-View Approach to Segmenting and Tracking People in a Cluttered Scene
International Journal of Computer Vision
Towards Monitoring Human Activities Using an Omnidirectional Camera
ICMI '02 Proceedings of the 4th IEEE International Conference on Multimodal Interfaces
Closed-Loop Person Tracking and Detection
CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
Detecting motion patterns via direction maps with application to surveillance
Computer Vision and Image Understanding
A Shape and Energy Based Approach to Vertical People Separation in Video Surveillance
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
Review: A survey of active and passive indoor localisation systems
Computer Communications
Tracking multiple people in the context of video surveillance
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Proceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments
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Hydra is a real-time system for detecting and tracking multiple people when they appear in a group. We describe the computational models employed by Hydra to track multiple people before, during and after occlusion. Hydra combines a silhouette-based shape model, a motion model, and correlation-based matching methods to classify whether or not a foreground region contains multiple people, and to segment the region into its constituent people and track them. Experimental results demonstrate robustness and real-time performance of the algorithm.