Track-based and object-based occlusion for people tracking refinement in indoor surveillance
Proceedings of the ACM 2nd international workshop on Video surveillance & sensor networks
Analysis and query of person-vehicle interactions in homography domain
Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Optimal Camera Placement for Automated Surveillance Tasks
Journal of Intelligent and Robotic Systems
Understanding human interactions with track and body synergies (TBS) captured from multiple views
Computer Vision and Image Understanding
Difference of Gaussian Edge-Texture Based Background Modeling for Dynamic Traffic Conditions
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
A neural approach to extract foreground from human movement images
Computer Methods and Programs in Biomedicine
On-line modeling for real-time 3D target tracking
Machine Vision and Applications
Adaptive foreground and shadow detection in image sequences
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
A matching-based approach for human motion analysis
MMM'07 Proceedings of the 13th International conference on Multimedia Modeling - Volume Part II
Foreground-to-Ghost discrimination in single-difference pre-processing
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
Multi-perspective video analysis of persons and vehicles for enhanced situational awareness
ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
Tracking of individuals in very long video sequences
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
| Hi-index | 0.00 |
A computer vision system for tracking multiple people in relatively unconstrained environments is described. Tracking is performed at three levels of abstraction: regions, people and groups. A novel, adaptive background subtraction method that combines color and gradient information is used to cope with shadows and unreliable color cues. People are tracked through mutual occlusions as they form groups and part from one another. Strong use is made of color information to disambiguate occlusions and to provide qualitative estimates of depth ordering and position during occlusion. Some simple interactions with objects can also be detected. The system is tested using indoor and outdoor sequences. It is robust and should provide a useful mechanism for bootstrapping and re-initialization of tracking using more specific but less robust human models.