ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Continuous Multi-Views Tracking using Tensor Voting
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
Automatic Tracking of Human Motion in Indoor Scenes Across Multiple Synchronized Video Streams
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Inference of Human Postures by Classification of 3D Human Body Shape
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
View-invariant Alignment and Matching of Video Sequences
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Tracking Across Multiple Cameras With Disjoint Views
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Bridging the gaps between cameras
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Learning a discriminative classifier using shape context distances
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Continuous tracking within and across camera streams
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
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
Object matching in disjoint cameras using a color transfer approach
Machine Vision and Applications
Camera handoff and placement for automated tracking systems with multiple omnidirectional cameras
Computer Vision and Image Understanding
Camera handoff with adaptive resource management for multi-camera multi-object tracking
Image and Vision Computing
Distributed tracking in a large-scale network of smart cameras
Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras
Multiple hypothesis target tracking using merge and split of graph’s nodes
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
People reidentification in surveillance and forensics: A survey
ACM Computing Surveys (CSUR)
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We present an approach for persistent tracking of moving objects observed by non-overlapping and moving cameras. Our approach robustly recovers the geometry of non-overlapping views using a moving camera that pans across the scene. We address the tracking problem by modeling the appearance and motion of the moving regions. The appearance of the detected blobs is described by multiple spatial distributions models of blobs' colors and edges. This representation is invariant to 2D rigid and scale transformation. It provides a rich description of the detected regions, and produces an efficient blob similarity measure for tracking. The motion model is obtained using a Kalman Filter (KF) process, which predicts the position of the moving objects while taking into account the camera motion. Tracking is performed by the maximization of a joint probability model combining objects' appearance and motion. The novelty of our approach consists in defining a spatio-temporal Joint Probability Data Association Filter (JPDAF) for integrating multiple cues. The proposed method tracks a large number of moving people with partial and total occlusions and provides automatic handoff of tracked objects. We demonstrate the performance of the system on several real video surveillance sequences.