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스테레오 비전기반의 컬럼 검출과 조감도 맵핑을 이용한 전방 차량 검출 알고리즘

Title
스테레오 비전기반의 컬럼 검출과 조감도 맵핑을 이용한 전방 차량 검출 알고리즘
Translated Title
Forward Vehicle Detection Algorithm Using Column Detection and Bird's-Eye View Mapping Based on Stereo Vision
Authors
이충희임영철권순김종환
DGIST Authors
이충희임영철권순
Issue Date
2011
Citation
정보처리학회논문지, 18(5), 255-264
Type
Article
Keywords
스테레오 비전차량 검출컬럼 검출조감도장애물체 세그멘테이션
ISSN
1598-284X
Abstract
In this paper, we propose a forward vehicle detection algorithm using column detection and bird's-eye view mapping based on stereo vision. The algorithm can detect forward vehicles robustly in real complex traffic situations. The algorithm consists of the three steps,namely road feature-based column detection, bird's-eye view mapping-based obstacle segmentation, obstacle area remerging and vehicle verification. First, we extract a road feature using maximum frequent values in v-disparity map. And we perform a column detection using the road feature as a new criterion. The road feature is more appropriate criterion than the median value because it is not affected by a road traffic situation, for example the changing of obstacle size or the number of obstacles. But there are still multiple obstacles in the obstacle areas. Thus, we perform a bird's-eye view mapping-based obstacle segmentation to divide obstacle accurately. We can segment obstacle easily because a bird's-eye view mapping can represent the position of obstacle on planar plane using depth map and camera information. Additionally, we perform obstacle area remerging processing because a segmented obstacle area may be same obstacle. Finally, we verify the obstacles whether those are vehicles or not using a depth map and gray image. We conduct experiments to prove the vehicle detection performance by applying our algorithm to real complex traffic situations.
URI
http://hdl.handle.net/20.500.11750/6497
DOI
10.3745/KIPSTB.2011.18B.5.255
Publisher
한국정보처리학회
Related Researcher
Files:
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Collection:
Convergence Research Center for Future Automotive Technology1. Journal Articles


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