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Proceedings Paper

On-road obstacle detection and tracking system using robust global stereo vision method
Author(s): Soon Kwon; Jong-Hun Lee; In-tae Na; Hong Jung
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Paper Abstract

In this paper, we present a visual obstacle detection and tracking system based on a dense stereo vision method. We combine a global stereo matcher with a correlation based cost function for generating a reliable disparity-map. An NCC algorithm is robust to illumination variation, and a BP based global disparity computation algorithm is efficient for recovering the disparity information of a large textureless area in real driving scenes. Then an obstacle detector and a tracker module are implemented and tested under actual driving conditions. Using U-V disparity representation, a road profile is efficiently extracted, and obstacle ROI can be detected. In the process of obstacle detection, a few heuristic constraints are applied to exclude wrong candidates, and a further verification step is proceeded by a tracker. Implemented system offers accurate and reliable range images under various noisy imaging conditions, which results in robust detection and tracking performance.

Paper Details

Date Published: 16 April 2010
PDF: 12 pages
Proc. SPIE 7698, Signal and Data Processing of Small Targets 2010, 769818 (16 April 2010); doi: 10.1117/12.852755
Show Author Affiliations
Soon Kwon, Daegu Gyeongbuk Institute of Science & Technology (Korea, Republic of)
Jong-Hun Lee, Daegu Gyeongbuk Institute of Science & Technology (Korea, Republic of)
In-tae Na, Pohang Univ. of Science and Technology (Korea, Republic of)
Hong Jung, Pohang Univ. of Science and Technology (Korea, Republic of)


Published in SPIE Proceedings Vol. 7698:
Signal and Data Processing of Small Targets 2010
Oliver E. Drummond, Editor(s)

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