Real-time Stereo Vision System at Tunnel

Yuquan Xu, Seiichi Mita, Hossein Tehrani, Kazuhisa Ishimaru

2017

Abstract

Although stereo vision has made great progress in recent years, there are limited works which estimate the disparity for challenging scenes such as tunnel scenes. In such scenes, owing to the low light conditions and fast camera movement, the images are severely degraded by motion blur. These degraded images limit the performance of the standard stereo vision algorithms. To address this issue, in this paper, we combine the stereo vision with the image deblurring algorithms to improve the disparity result. The proposed algorithm consists of three phases: the PSF estimation phase; the image restoration phase; and the stereo vision phase. In the PSF estimation phase, we introduce three methods to estimate the blur kernel, which are optical flow based algorithm, cepstrum base algorithm and simple constant kernel algorithm, respectively. In the image restoration phase, we propose a fast non-blind image deblurring algorithm to recover the latent image. In the last phase, we propose a multi-scale multi-path Viterbi algorithm to compute the disparity given the deblurred images. The advantages of the proposed algorithm are demonstrated by the experiments with data sequences acquired in the tunnel.

Paper Citation

in Harvard Style

Xu Y., Mita S., Tehrani H. and Ishimaru K. (2017). Real-time Stereo Vision System at Tunnel . 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 402-409. DOI: 10.5220/0006112304020409

in Bibtex Style

@conference{visapp17,
author={Yuquan Xu and Seiichi Mita and Hossein Tehrani and Kazuhisa Ishimaru},
title={Real-time Stereo Vision System at Tunnel},
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={402-409},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006112304020409},
isbn={978-989-758-227-1},
}

in EndNote Style

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 - Real-time Stereo Vision System at Tunnel
SN - 978-989-758-227-1
AU - Xu Y.
AU - Mita S.
AU - Tehrani H.
AU - Ishimaru K.
PY - 2017
SP - 402
EP - 409
DO - 10.5220/0006112304020409