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18 November 2019 Stereo matching using convolution neural network and LIDAR support point grid
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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%.
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Sergei Bykovskii, Aleksei Denisov, Andrey Zhdanov, Alexander Belozubov, Alexander Antonov, Elizaveta Kormilitsyna, and Dmitry Zhdanov "Stereo matching using convolution neural network and LIDAR support point grid", Proc. SPIE 11187, Optoelectronic Imaging and Multimedia Technology VI, 111871J (18 November 2019); https://doi.org/10.1117/12.2537723
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