Online selection of tracking features using AdaBoost
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Multimedia - Special issue on integration of context and content
PDF target detection and tracking
Signal Processing
Real-time multiple object centroid tracking for gesture recognition based on FPGA
Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
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This paper considers the problem of simultaneously detecting and tracking multiple targets. The problem can be formulated in a Bayesian framework and solved, in principle, by computation of the joint multitarget probability density (JMPD). In practice, exact computation of the JMPD is impossible, and the predominant challenge is to arrive at a computationally tractable approximation. A particle filtering scheme is developed for this purpose in which each particle is a hypothesis on the number of targets present and the states of those targets. The importance density for the particle filter is designed in such a way that the measurements can guide sampling of both the target number and the target states. Simulation results, with measurements generated from real target trajectories, demonstrate the ability of the proposed procedure to simultaneously detect and track ten targets with a reasonable sample size