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Image motion estimation by clustering

Image motion is estimated by matching feature “interest” points in different frames of video image sequences. The matching is based on local similarity of the displacement vectors. Clustering in the displacement vector space is used to determine the set of plausible match vectors. Subsequently, a similarity‐based algorithm performs the actual matching. The feature points are computed using a multiple‐filter image decomposition operator. The algorithm has been tested on synthetic as well as real video images. The novelty of the approach is that it handles multiple motions and performs motion segmentation.