Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/71368
Title: Particle filter for visual tracking using multiple cameras
Authors: Wang, Y.-D.
Wu, J.-K.
Kassim, A.A. 
Issue Date: 2005
Source: Wang, Y.-D.,Wu, J.-K.,Kassim, A.A. (2005). Particle filter for visual tracking using multiple cameras. Proceedings of the 9th IAPR Conference on Machine Vision Applications, MVA 2005 : 298-301. ScholarBank@NUS Repository.
Abstract: This article proposes an approach for visual track ing using multiple cameras with overlapping fields of view. A spatial and temporal recursive Bayesian filtering approach using particle filter is proposed to fuse image sequences of multiple cameras to optimally estimate the state of the system, i.e., the target.s location. An approximation method for importance sampling function and weight update function is also proposed. Our results show that our algorithm is effective when complete occlusions occur. This method can be used for data fusion for multiple measurements in dynamic systems. Copyright © 2005 by MVA Conference Committee.
Source Title: Proceedings of the 9th IAPR Conference on Machine Vision Applications, MVA 2005
URI: http://scholarbank.nus.edu.sg/handle/10635/71368
ISBN: 4901122045
Appears in Collections:Staff Publications

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