EURASIP Journal on Applied Signal Processing
Mean field approach for tracking similar objects
Computer Vision and Image Understanding
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IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Multiple object tracking via multi-layer multi-modal framework
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
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ICVS'08 Proceedings of the 6th international conference on Computer vision systems
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ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on twitter and microblogging services, social recommender systems, and CAMRa2010: Movie recommendation in context
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on agent communication, trust in multiagent systems, intelligent tutoring and coaching systems
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This paper breaks with the common practice of using a joint state space representation and performing the joint data association in multi-object tracking. Instead, we present an interactively distributed framework with linear complexity for real-time applications. When objects do not interact on each other, our approach performs like multiple independent trackers. When the objects are in close proximity or present occlusions, we propose a magnetic-inertia potential model to handle the "error merge" and "labelling" problems in a particle filtering framework. Specifically, we propose to model the interactive likelihood densities by a "gravitation" and "magnetic" repulsion scheme and relax the common first-order Markov chain assumption by using an "Inertia" Markov chain. Our model represents the cumulative effect of virtual physical forces that objects undergo while interacting with others. It implicitly handles the "error merge" and "labelling" problems and thus solves the difficult object occlusion and data association problems using an innovative scheme. Our preliminary work has demonstrated that the proposed approach is far superior to existing methods not only in robustness but also in speed.