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Proceedings Paper

Stereo matching using convolution neural network and LIDAR support point grid
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Paper Abstract

This paper proposes a stereo matching method that uses a support point grid in order to compute the prior disparity. Convolutional neural networks are used to compute the matching cost between pixels in two pictures. The network architecture is described as well as teaching process. The method was evaluated on Middlebury benchmark images. The results of accuracy estimation in case of using data from a LIDAR as an input for the support points grid is described. This approach can be used in multi-sensor devices and can give an advantage in accuracy up to 15%.

Paper Details

Date Published: 18 November 2019
PDF: 7 pages
Proc. SPIE 11187, Optoelectronic Imaging and Multimedia Technology VI, 111871J (18 November 2019); doi: 10.1117/12.2537723
Show Author Affiliations
Sergei Bykovskii, ITMO Univ. (Russian Federation)
Aleksei Denisov, ITMO Univ. (Russian Federation)
Andrey Zhdanov, ITMO Univ. (Russian Federation)
Alexander Belozubov, ITMO Univ. (Russian Federation)
Alexander Antonov, ITMO Univ. (Russian Federation)
Elizaveta Kormilitsyna, ITMO Univ. (Russian Federation)
Dmitry Zhdanov, ITMO Univ. (Russian Federation)

Published in SPIE Proceedings Vol. 11187:
Optoelectronic Imaging and Multimedia Technology VI
Qionghai Dai; Tsutomu Shimura; Zhenrong Zheng, Editor(s)

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