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Comparison of stereo matching algorithms for obstacle detection and collision avoidance
Author(s): A. Gladkov; S. Gladilin; E. Ershov
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Paper Abstract

In this paper the authors compared the accuracy of several stereo matching algorithms using problem-oriented metrics developed by the authors earlier for obstacle detection. For comparison we have chosen the most computationally effective open-source algorithms, suitable for using in autonomous systems with limited processor capacities. The quality of the algorithms was compared on the public dataset KITTI Stereo Evaluation 2015. The hypothesis that the problemoriented metric of the stereo matching quality will lead to a different ranking than the universal metric, was not confirmed. At the same time, our measurements of the algorithms execution time showed results significantly different from those stated on KITTI portal.

Paper Details

Date Published: 15 March 2019
PDF: 9 pages
Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 1104122 (15 March 2019); doi: 10.1117/12.2523116
Show Author Affiliations
A. Gladkov, Institute for Information Transmission Problems (Russian Federation)
S. Gladilin, Institute for Information Transmission Problems (Russian Federation)
E. Ershov, Institute for Information Transmission Problems (Russian Federation)


Published in SPIE Proceedings Vol. 11041:
Eleventh International Conference on Machine Vision (ICMV 2018)
Antanas Verikas; Dmitry P. Nikolaev; Petia Radeva; Jianhong Zhou, Editor(s)

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