Multi-objective optimization for characterization of optical flow methods

José Delpiano, Luis Pizarro, Rodrigo Verschae, Javier Ruiz-Del-Solar

Research output: Contribution to conferencePaper

4 Scopus citations

Abstract

Optical flow methods are among the most accurate techniques for estimating displacement and velocity fields in a number of applications that range from neuroscience to robotics. The performance of any optical flow method will naturally depend on the configuration of its parameters. Beyond the standard practice of manual (ad-hoc) selection of parameters for a specific application, in this article we propose a framework for automatic parameter setting that allows searching for an approximated Pareto-optimal set of configurations in the whole parameter space. This final Pareto front characterizes each specific method, enabling proper method comparison. We define two performance criteria, namely the accuracy and speed of the optical flow methods. Copyright
Original languageAmerican English
Pages566-573
Number of pages8
DOIs
StatePublished - 1 Jan 2014
EventVISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications -
Duration: 1 Jan 2014 → …

Conference

ConferenceVISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications
Period1/01/14 → …

Keywords

  • Multi-objective Optimization
  • Optical Flow

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