Computing optic flow by scale-space integration of normal flow

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Abstract

In this paper we will present a least committed multi-scale method for computation of optic flow fields. We extract optic flow fields from normal flow, by fitting the normal components of a local polynomial model of the optic flow to the normal flow. This fitting is based on an analytically solvable optimization problem, in which an integration scale- space over the normal flow field regularizes the solution. An automatic local scale selection mechanism is used in order to adapt to the local structure of the flow field. The performance profile of the method is compared with that of existing optic flow techniques and we show that the proposed method performs at least as well as the leading algorithms on the benchmark image sequences proposed by Barron et al. [3]. We also do a performance comparison on a synthetic fire particle sequence and apply our method to a real sequence of smoke circulation in a pigsty. Both consist of highly complex non-rigid motion.

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Pedersen, K. S., & Nielsen, M. (2001). Computing optic flow by scale-space integration of normal flow. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2106, pp. 14–25). Springer Verlag. https://doi.org/10.1007/3-540-47778-0_2

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