Abstract
An algorithm is presented to compute the shape of moving objects in image sequences. We assume that locally the motion fields of both the object and its environment can be represented by affine approximations. Based on hypotheses about these fields, an optimality principle is formulated to compute the shape of an object in terms of deformations of an arbitrary convex polygonal domain. As input data the algorithm merely requires first order derivatives of the image function. Numerical experiments using synthesized and real image data are presented. The results suggest that our approach is suited for tracking tasks within an bottom-up/top-down framework.
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© 1995 Springer-Verlag Berlin Heidelberg
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Schnörr, C., Peckar, W. (1995). Motion-based identification of deformable templates. In: Hlaváč, V., Šára, R. (eds) Computer Analysis of Images and Patterns. CAIP 1995. Lecture Notes in Computer Science, vol 970. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60268-2_288
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DOI: https://doi.org/10.1007/3-540-60268-2_288
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