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Authors: Ivan Cabezas 1 ; Maria Trujillo 1 and Margaret Florian 2

Affiliations: 1 Universidad del Valle, Colombia ; 2 Ayax Systems, Colombia

ISBN: 978-989-8565-04-4

Keyword(s): Computer Vision, Disparity Estimation, Error Measures, Quantitative Evaluation Methodologies, Stereo Correspondence.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Geometry and Modeling ; Image-Based Modeling ; Motion, Tracking and Stereo Vision ; Pattern Recognition ; Software Engineering ; Stereo Vision and Structure from Motion

Abstract: A comparison of stereo correspondence algorithms can be conducted by a quantitative evaluation of disparity maps. Among the existing evaluation methodologies, the Middlebury’s methodology is commonly used. However, the Middlebury’s methodology has shortcomings in the evaluation model and the error measure. These shortcomings may bias the evaluation results, and make a fair judgment about algorithms accuracy difficult. An alternative, the A* methodology is based on a multiobjective optimisation model that only provides a subset of algorithms with comparable accuracy. In this paper, a quantitative evaluation of disparity maps is proposed. It performs an exhaustive assessment of the entire set of algorithms. As innovative aspect, evaluation results are shown and analysed as disjoint groups of stereo correspondence algorithms with comparable accuracy. This innovation is obtained by a partitioning and grouping algorithm. On the other hand, the used error measure offers advantages over the error measure used in the Middlebury’s methodology. The experimental validation is based on the Middlebury’s test-bed and algorithms repository. The obtained results show seven groups with different accuracies. Moreover, the top-ranked stereo correspondence algorithms by the Middlebury’s methodology are not necessarily the most accurate in the proposed methodology. (More)

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Paper citation in several formats:
Cabezas, I.; Trujillo, M. and Florian, M. (2012). AN EVALUATION METHODOLOGY FOR STEREO CORRESPONDENCE ALGORITHMS.In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-04-4, pages 154-163. DOI: 10.5220/0003850801540163

@conference{visapp12,
author={Ivan Cabezas. and Maria Trujillo. and Margaret Florian.},
title={AN EVALUATION METHODOLOGY FOR STEREO CORRESPONDENCE ALGORITHMS},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={154-163},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003850801540163},
isbn={978-989-8565-04-4},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)
TI - AN EVALUATION METHODOLOGY FOR STEREO CORRESPONDENCE ALGORITHMS
SN - 978-989-8565-04-4
AU - Cabezas, I.
AU - Trujillo, M.
AU - Florian, M.
PY - 2012
SP - 154
EP - 163
DO - 10.5220/0003850801540163

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