Tracking Based on SURF and Superpixel

In this paper we present a novel algorithm for object tracking in video sequence based on SURF key-point and super pixel. SURF key-point is very effective for object matching between two images and we can use it to locate object by and large. But only in this way it can't guarantee the success of object tracking because many available key-points are un-matched and can't be used to locate the object. In order to solve this problem we take the advantage of super pixel to obtain more available key-points based on its property that all points in the same super pixel region belong to the same object. At last we construct a weight map for each frame to refine the location of target object. The experiments demonstrate that our work is robust for tracking, especially dealing with occlusions and object transformations.

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