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An enhanced particle Filter (PF) is introduced for object tracking. In this work, a new likelihood model is proposed. It depends on multiple of likelihood functions: position likelihood; gray level intensity likelihood; and similarity likelihood. Also, it combines information about the tracked object to get a robust and an accurate tracking performance. The proposed enhanced PF is implemented and...
Robust and real-time object tracking of any objects is a challenging task. Particle filtering has been proven very successful for non-gaussian and non-linear estimation problems. This paper describes a new approach to improve the moving object tracking system with particle filter using shape similarity. The shape similarity between a template and estimated regions in the video sequences can be measured...
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