A General Framework for Combining Visual Trackers --- The "Black Boxes" Approach
International Journal of Computer Vision
Rao-Blackwellized particle filter for multiple target tracking
Information Fusion
Robotics and Autonomous Systems
A feedback-based algorithm for motion analysis with application to object tracking
EURASIP Journal on Applied Signal Processing
Motion analysis for human-robot interaction
MMACTE'05 Proceedings of the 7th WSEAS International Conference on Mathematical Methods and Computational Techniques In Electrical Engineering
Closed-world tracking of multiple interacting targets for indoor-sports applications
Computer Vision and Image Understanding
Automated tracking in digitized videofluoroscopy sequences for spine kinematic analysis
Image and Vision Computing
Mice and larvae tracking using a particle filter with an auto-adjustable observation model
Pattern Recognition Letters
Joint multitarget object tracking and interaction analysis by a probabilistic bio-inspired model
Proceedings of the first ACM international workshop on Analysis and retrieval of tracked events and motion in imagery streams
Editors Choice Article: Tracking highly correlated targets through statistical multiplexing
Image and Vision Computing
Scatter search particle filter for 2d real-time hands and face tracking
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
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Abstract: We address the problem of tracking multiple objects encountered in many situations in signal or image processing. We consider stochastic dynamic systems nonlinearly and uncompletely observed. The difficulty lies on the fact that the estimation of the states requires the assignation of the observations to the multiple targets. We propose an extension of the classical particle filter where the stochastic vector of assignation is estimated by a Gibbs sampler. The merit of the method is assessed in bearings-only context and we present one application in image-based tracking.