Publicação: On the optical flow model selection through metaheuristics
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2015-05-09
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Springer
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Optical flow methods are accurate algorithms for estimating the displacement and velocity fields of objects in a wide variety of applications, being their performance dependent on the configuration of a set of parameters. Since there is a lack of research that aims to automatically tune such parameters, in this work, we have proposed an optimization-based framework for such task based on social-spider optimization, harmony search, particle swarm optimization, and Nelder-Mead algorithm. The proposed framework employed the well-known large displacement optical flow (LDOF) approach as a basis algorithm over the Middlebury and Sintel public datasets, with promising results considering the baseline proposed by the authors of LDOF.
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Eurasip Journal On Image And Video Processing. Cham: Springer International Publishing Ag, v. 2015, n. 11, p. 1-10, 2015.
