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Authors: Mircea Paul Muresan ; Sergiu Nedevschi and Radu Danescu

Affiliation: Technical University of Cluj-Napoca, Romania

ISBN: 978-989-758-227-1

Keyword(s): Dense Stereo, Block Matching, Slanted Surfaces, Disparity Refinement, Binary Descriptors.

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: Stereo cameras are a suitable solution for reconstructing the 3D information of the observed scenes, and, because of their low price and ease to set up and operate, they can be used in a wide area of applications, ranging from autonomous driving to advanced driver assistance systems or robotics. Due to the high quality of the results, energy based reconstruction methods like semi global matching have gained a lot of popularity in recent years. The disadvantages of semi global matching are the large memory footprint and the high computational complexity. In contrast, window based matching methods have a lower complexity, and are leaner with respect to the memory consumption. The downside of block matching methods is that they are more error prone, especially on surfaces which are not parallel to the image plane. In this paper we present a novel block matching scheme that improves the quality of local stereo correspondence algorithms. The first contribution of the paper consists in an o riginal method for reliably reconstructing the environment on slanted surfaces. The second contribution consists in the creation of set of local constraints that filter out possible outlier disparity values. The third and final contribution consists in the creation of a refinement technique which improves the resulted disparity map. The proposed stereo correspondence approach has been validated on the KITTI stereo dataset. (More)

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Paper citation in several formats:
Muresan, M.; Nedevschi, S. and Danescu, R. (2017). A Multi Patch Warping Approach for Improved Stereo Block Matching.In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-227-1, pages 459-466. DOI: 10.5220/0006134104590466

@conference{visapp17,
author={Mircea Paul Muresan. and Sergiu Nedevschi. and Radu Danescu.},
title={A Multi Patch Warping Approach for Improved Stereo Block Matching},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={459-466},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006134104590466},
isbn={978-989-758-227-1},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017)
TI - A Multi Patch Warping Approach for Improved Stereo Block Matching
SN - 978-989-758-227-1
AU - Muresan, M.
AU - Nedevschi, S.
AU - Danescu, R.
PY - 2017
SP - 459
EP - 466
DO - 10.5220/0006134104590466

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