Abstract
In this paper the first-order spatial properties of optical flow, such as singular points and elementary motions, are used to describe and analyze moving images. First, it is shown that the spatial structure of the viewed motion of rigid objects, with the exception of surface and motion boundaries, can usually be approximated over rather large regions of the image plane by a linear vector field. Second, a method is proposed in which optical flow is computed as a piecewise linear vector field. The obtained first-order properties of optical flow are then used to devise methods for distinguishing between different kinds of motion, extracting qualitative information about shape, and segmenting the viewed image into the different moving objects. Experimental results on several sequences of real images are presented and discussed. Since the methods which are proposed rely upon patchwise and not pointwise flow estimates, the obtained results are usually very good and insensitive to noise. It is concluded that the first-order properties of optical flow are very helpful for the understanding of visual motion.
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