Pereira, Danillo R.
Papa, Joao P.
Número total de Autores: 3
Afiliação do(s) autor(es):
 Sao Paulo State Univ, BR-17033360 Bauru, SP - Brazil
 Univ Andes, Santiago 12445 - Chile
Número total de Afiliações: 2
Tipo de documento:
EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING;
MAY 9 2015.
Citações Web of Science:
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. (AU)