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In this paper, we propose a novel approach that combines particle filter tracking and 3D graph cut based segmentation to achieve silhouette tracking against drastic scale change and occlusion. The segmentation module offers particle filter tracking procedure the target shape information to compensate spatial information loss in the histogram based particle filter tracking process. Meanwhile, particle...
The goal of this paper is to introduce a new tracking framework, which exploits dynamic feature and signature selection techniques for data association models. It performs robust multiple object tracking in a noisy, cluttered environment with closely spaced targets. This method extends the back-end processing capabilities of tracking systems by creating a hierarchy between the parallelly extracted...
Robust and real time moving object tracking is a tricky job in computer vision problems. Particle filtering has been proven very successful for non-Gaussian and non-linear estimation problems. In this paper, we first try to develop a color based particle filter. In this approach, the object tracking system relies on the deterministic search of window, whose color content matches a reference histogram...
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