%0 Conference Proceedings
%T Local Analysis of Confidence Measures for Optical Flow Quality Evaluation
%A Patricia Marquez
%A Debora Gil
%A R.Mester
%A Aura Hernandez-Sabate
%B 9th International Conference on Computer Vision Theory and Applications
%D 2014
%V 3
%F Patricia Marquez2014
%O IAM; ADAS; 600.044; 600.060; 600.057; 601.145; 600.076; 600.075
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=2432), last updated on Thu, 10 Nov 2016 11:46:44 +0100
%X Optical Flow (OF) techniques facing the complexity of real sequences have been developed in the last years. Even using the most appropriate technique for our specific problem, at some points the output flow might fail to achieve the minimum error required for the system. Confidence measures computed from either input data or OF output should discard those points where OF is not accurate enough for its further use. It follows that evaluating the capabilities of a confidence measure for bounding OF error is as important as the definitionitself. In this paper we analyze different confidence measures and point out their advantages and limitations for their use in real world settings. We also explore the agreement with current tools for their evaluation of confidence measures performance.
%K Optical Flow
%K Confidence Measure
%K Performance Evaluation.
%U http://refbase.cvc.uab.es/files/MGM2014.pdf
%P 450-457