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Stereo Vision-Based Obstacle Detection and Vehicle Verification Methods Using U-Disparity Map and Bird's-Eye View Mapping  

Lee, Chung-Hee (Daegu Gyeongbuk Institute of Science & Technology)
Lim, Young-Chul (Daegu Gyeongbuk Institute of Science & Technology)
Kwon, Soon (Daegu Gyeongbuk Institute of Science & Technology)
Lee, Jong-Hun (Daegu Gyeongbuk Institute of Science & Technology)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SC / v.47, no.6, 2010 , pp. 86-96 More about this Journal
Abstract
In this paper, we propose stereo vision-based obstacle detection and vehicle verification methods using U-disparity map and bird's-eye view mapping. First, we extract a road feature using maximum frequent values in each row and column. And we extract obstacle areas on the road using the extracted road feature. To extract obstacle areas exactly we utilize U-disparity map. We can extract obstacle areas exactly on the U-disparity map using threshold value which consists of disparity value and camera parameter. But there are still multiple obstacles in the extracted obstacle areas. Thus, we perform another processing, namely segmentation. We convert the extracted obstacle areas into a bird's-eye view using camera modeling and parameters. We can segment obstacle areas on the bird's-eye view robustly because obstacles are represented on it according to ranges. Finally, we verify the obstacles whether those are vehicles or not using various vehicle features, namely road contacting, constant horizontal length, aspect ratio and texture information. We conduct experiments to prove the performance of our proposed algorithms in real traffic situations.
Keywords
Stereo vision; Obstacle detection; Vehicle verification; U-disparity; Bird's-eye view;
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Times Cited By KSCI : 3  (Citation Analysis)
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