Object Contour Tracking Using Foreground and Background Distribution Matching
In this paper, we propose an effective approach for tracking distribution of objects. The approach uses a competition between a tracked objet and background distributions using active contours. Only the segmentation of the object in the first frame is required for initialization. The object contour is tracked by assigning pixels in a way that maximizes the likelihood of the object versus the background. We implement the approach using an EM-like algorithm which evolves the object contour exactly to its boundaries and adapts the distribution parameters of the object and the background to data.
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