Computer and Robot Vision
Structured Kalman Filter for Tracking Partially Occluded Moving Objects
BMVC '00 Proceedings of the First IEEE International Workshop on Biologically Motivated Computer Vision
Detection and Location of People in Video Images Using Adaptive Fusion of Color and Edge Information
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
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A new segmentation strategy is proposed to precisely extract moving objects in video sequences. It is based on the automatic detection of the static elements, and its classification as background and foreground using static differences and contextual information. Additionally, tracking information is incorporated to reduce the computational cost. Finally, segmentation is refined through a Markov random field (MRF) change detection analysis including the foreground information, which allows improving the accuracy of the segmentation. This strategy is presented in the context of low quality sequences of surveillance applications but it could be applied to other applications, the only requirement being to have a static or quasi static background.