An efficient scalable object contour tracking scheme and its application for video segmentation

We present an efficient scalable object contours tracking algorithm and its application for video segmentation. It can track the contour of both rigid and nonrigid objects, even with partial occlusion. For each object, motion information is first used to predict the object contour. Next, texture information along the object contour is used to refine the predicted contour. Finally, active snake is used to snap the detected contour to the real object with high accuracy. The proposed energy terms in active snake model are normalized colour gradient and foreground/ background region properties along the contour. Experimental results illustrate the performance of the proposed tracking algorithm, which is able to track the object boundaries with large motion and partial occlusion.