Real-time people localization and tracking through fixed stereo vision
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
ACM Computing Surveys (CSUR)
Real-time people localization and tracking through fixed stereo vision
Applied Intelligence
HECOL: Homography and epipolar-based consistent labeling for outdoor park surveillance
Computer Vision and Image Understanding
Note: Target tracking with incomplete detection
Computer Vision and Image Understanding
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
Dynamic appearance model for particle filter based visual tracking
Pattern Recognition
Part-based spatio-temporal model for multi-person re-identification
Pattern Recognition Letters
Editor's Choice Article: A survey of approaches and trends in person re-identification
Image and Vision Computing
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We present an approach for reacquisition of detected moving objects. We address the tracking problem by modeling the appearance of the moving region using stochastic models. The appearance of the object is described by multiple models representing spatial distributions of objects' colors and edges. This representation is invariant to 2D rigid and scale transformation. It provides a good description of the object being tracked, and produces an efficient blob similarity measure for tracking. Three different similarity measures are proposed, and compared to show the performance of each model. The proposed appearance model allows to track a large number of moving people with partial and total occlusions and permits to reacquire objects that have been previously tracked. We demonstrate the performance of the system on several real video surveillance sequences.