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https://scholarbank.nus.edu.sg/handle/10635/71368
DC Field | Value | |
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dc.title | Particle filter for visual tracking using multiple cameras | |
dc.contributor.author | Wang, Y.-D. | |
dc.contributor.author | Wu, J.-K. | |
dc.contributor.author | Kassim, A.A. | |
dc.date.accessioned | 2014-06-19T03:22:58Z | |
dc.date.available | 2014-06-19T03:22:58Z | |
dc.date.issued | 2005 | |
dc.identifier.citation | 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. | |
dc.identifier.isbn | 4901122045 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/71368 | |
dc.description.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. | |
dc.source | Scopus | |
dc.type | Conference Paper | |
dc.contributor.department | ELECTRICAL & COMPUTER ENGINEERING | |
dc.description.sourcetitle | Proceedings of the 9th IAPR Conference on Machine Vision Applications, MVA 2005 | |
dc.description.page | 298-301 | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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