Please use this identifier to cite or link to this item: https://doi.org/10.1007/s11265-007-0090-5
Title: Adaptive particle filter for data fusion of multiple cameras
Authors: Wang, Y.-D.
Wu, J.-K.
Kassim, A.A. 
Keywords: Bayesian filter
Occlusion
Particle filter
Visual tracking
Issue Date: Dec-2007
Source: Wang, Y.-D., Wu, J.-K., Kassim, A.A. (2007-12). Adaptive particle filter for data fusion of multiple cameras. Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology 49 (3) : 363-376. ScholarBank@NUS Repository. https://doi.org/10.1007/s11265-007-0090-5
Abstract: Occlusion is a difficult problem for visual tracking and we use multiple wide baseline cameras to deal with occlusion. We propose a data fusion approach for visual tracking using multiple cameras with overlapping fields of view. First, we present a spatial and temporal recursive Bayesian filter to fuse information from multiple cameras. An adaptive particle filter is formulated to realize the spatial and temporal recursive Bayesian filter. Our algorithm is able to recover the target's position even under complete occlusion in a camera. © 2007 Springer Science+Business Media, LLC.
Source Title: Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology
URI: http://scholarbank.nus.edu.sg/handle/10635/54930
ISSN: 13875485
DOI: 10.1007/s11265-007-0090-5
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