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Proceedings Paper

Stereo vision-based obstacle detection using dense disparity map
Author(s): Chung-Hee Lee; Young-Chul Lim; Soon Kwon; Jonghwan Kim
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Paper Abstract

In this paper, we propose stereo vision-based obstacle detection method on the road using a dense disparity map. We use the dense disparity map to detect obstacles robustly in real traffic situations. Our method consists of three stages, namely road feature extraction, column detection, obstacle segmentation. First, we extract a road feature from a v- disparity map calculated from a dense disparity map. And we perform a column detection using the extracted road feature as a criterion that decides whether obstacles exist or not. Finally, we perform a segmentation using a bird's-eye view mapping to divide the merged obstacle into each obstacle accurately. We conduct experiments to verify our method in the real traffic situations.

Paper Details

Date Published: 1 October 2011
PDF: 6 pages
Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 82853O (1 October 2011); doi: 10.1117/12.914442
Show Author Affiliations
Chung-Hee Lee, Daegu Gyeongbuk Institute of Science & Technology (Korea, Republic of)
Young-Chul Lim, Daegu Gyeongbuk Institute of Science & Technology (Korea, Republic of)
Soon Kwon, Daegu Gyeongbuk Institute of Science & Technology (Korea, Republic of)
Jonghwan Kim, Daegu Gyeongbuk Institute of Science & Technology (Korea, Republic of)


Published in SPIE Proceedings Vol. 8285:
International Conference on Graphic and Image Processing (ICGIP 2011)
Yi Xie; Yanjun Zheng, Editor(s)

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