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Accuracy improvement of depth estimation with tilted optics by optimizing neural network
Author(s): Hiroshi Ikeoka; Takayuki Hamamoto
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Paper Abstract

We have been investigating a novel depth estimation system that adopts tilted-lens optics for real-time usage, e.g., automotive tasks. Herein, we obtained depth values for each pixel from the sharpness ratio of only two tilted optics images; we used a monocular camera system with a spectroscopic mirror. However, the method causes some estimation errors because of the difference between the optical theory and the actual camera system. Therefore, to reduce the error, we adopted a neural network to obtain the depth map. In this paper, we report our improvement by optimizing the neural network construction which calculates the depth value for each pixel from 3 × 3 pixel values at each image and y-coordinate.

Paper Details

Date Published: 22 March 2019
PDF: 6 pages
Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 1104934 (22 March 2019); doi: 10.1117/12.2521101
Show Author Affiliations
Hiroshi Ikeoka, Fukuyama Univ. (Japan)
Takayuki Hamamoto, Tokyo Univ. of Science (Japan)


Published in SPIE Proceedings Vol. 11049:
International Workshop on Advanced Image Technology (IWAIT) 2019
Qian Kemao; Kazuya Hayase; Phooi Yee Lau; Wen-Nung Lie; Yung-Lyul Lee; Sanun Srisuk; Lu Yu, Editor(s)

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