Data association for visual tracking with particle filters
This thesis addresses the problem of tracking one or more objects in monocular video sequences for visual surveillance. Two probabilistic tracking frameworks are proposed. The first is a multi-cue-based tracking framework to fuse high-level object detection cues with low-level color and edge cues us...
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University of Surrey
2008
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| Online Access: | https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.486035 |