Evaluation of the Capabilities of Confidence Measures for Assessing Optical Flow Quality

Patricia Marquez-Valle, Debora Gil, Aura Hernandez-Sabate; The IEEE International Conference on Computer Vision (ICCV) Workshops, 2013, pp. 624-631

Abstract


Assessing Optical Flow (OF) quality is essential for its further use in reliable decision support systems. The absence of ground truth in such situations leads to the computation of OF Confidence Measures (CM) obtained from either input or output data. A fair comparison across the capabilities of the different CM for bounding OF error is required in order to choose the best OF-CM pair for discarding points where OF computation is not reliable. This paper presents a statistical probabilistic framework for assessing the quality of a given CM. Our quality measure is given in terms of the percentage of pixels whose OF error bound can not be determined by CM values. We also provide statistical tools for the computation of CM values that ensures a given accuracy of the flow field.

Related Material


[pdf]
[bibtex]
@InProceedings{Marquez-Valle_2013_ICCV_Workshops,
author = {Patricia Marquez-Valle and Debora Gil and Aura Hernandez-Sabate},
title = {Evaluation of the Capabilities of Confidence Measures for Assessing Optical Flow Quality},
journal = {The IEEE International Conference on Computer Vision (ICCV) Workshops},
month = {June},
year = {2013}
}