Pereira, Danillo R. [UNESP]Delpiano, JoséPapa, João P. [UNESP]2015-10-212015-10-212015-05-09Eurasip Journal On Image And Video Processing. Cham: Springer International Publishing Ag, v. 2015, n. 11, p. 1-10, 2015.1687-5281http://hdl.handle.net/11449/129416Optical 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.1-10engOptimization methodsEvolutionary algorithmsOptical flow methodsArtigo10.1186/s13640-015-0066-5WOS:000354709700001Acesso abertoWOS000354709700001.pdf