M2Tracker: A Multi-View Approach to Segmenting and Tracking People in a Cluttered Scene
International Journal of Computer Vision
VS '99 Proceedings of the Second IEEE Workshop on Visual Surveillance
Tracking Across Multiple Cameras With Disjoint Views
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Principal Axis-Based Correspondence between Multiple Cameras for People Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-camera calibration, object tracking and query generation
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
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
Automated Visual Surveillance in Realistic Scenarios
IEEE MultiMedia
Multicamera People Tracking with a Probabilistic Occupancy Map
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian-Competitive Consistent Labeling for People Surveillance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Understanding human interactions with track and body synergies (TBS) captured from multiple views
Computer Vision and Image Understanding
Incremental, scalable tracking of objects inter camera
Computer Vision and Image Understanding
People tracking across two distant self-calibrated cameras
AVSS '07 Proceedings of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance
Automated multi-camera planar tracking correspondence modeling
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
A multiview approach to tracking people in crowded scenes using a planar homography constraint
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Tracking of individuals in very long video sequences
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
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This paper presents an automatic visual analysis system for simultaneously tracking humans and vehicles using multiple cameras in an unconstrained outdoor environment. The system establishes correspondence between views using a principal axis approach for humans and a footage region approach for vehicles. Novel methods for locating humans in groups and solving ambiguity when matching vehicles across views are presented. Foreground segmentation for each view is performed using the codebook method and HSV shadow suppression. The tracking of objects is performed in each view, and occlusion situations are resolved by probabilistic appearance models. The system is tested on hours of video and on three different datasets.