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Authors: Maren Brumm ; Jan Marek Marcinczak and Rolf-Rainer Grigat

Affiliation: Hamburg University of Technology, Germany

ISBN: 978-989-758-091-8

ISSN: 2184-4321

Keyword(s): Variational Optical Flow, Confidence Measure, Performance Evaluation, Structure-Texture Decomposition.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Motion, Tracking and Stereo Vision ; Optical Flow and Motion Analyses ; Stereo Vision and Structure from Motion ; Tracking and Visual Navigation

Abstract: In the last decades variational optical flow algorithms have been intensively studied by the computer vision community. However, relatively few effort has been made to obtain robust confidence measures for the estimated flow field. As many applications do not require the whole flow field, it would be helpful to identify the parts of the field where the flow is most accurate. We propose a confidence measure based on the energy functional that is minimized during the optical flow calculation and analyze the performance of different data terms. For evaluation, 7 datasets of the Middlebury benchmark are used. The results show that the accuracy of the flow field can be improved by 53.3 % if points are selected according to the proposed confidence measure. The suggested method leads to an improvement of 35.2 % compared to classical confidence measures.

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Paper citation in several formats:
Brumm, M.; Marcinczak, J. and Grigat, R. (2015). Improved Confidence Measures for Variational Optical Flow.In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-091-8, ISSN 2184-4321, pages 389-394. DOI: 10.5220/0005167203890394

@conference{visapp15,
author={Maren Brumm. and Jan Marek Marcinczak. and Rolf{-}Rainer Grigat.},
title={Improved Confidence Measures for Variational Optical Flow},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={389-394},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005167203890394},
isbn={978-989-758-091-8},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)
TI - Improved Confidence Measures for Variational Optical Flow
SN - 978-989-758-091-8
AU - Brumm, M.
AU - Marcinczak, J.
AU - Grigat, R.
PY - 2015
SP - 389
EP - 394
DO - 10.5220/0005167203890394

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