Browse > Article
http://dx.doi.org/10.3745/KIPSTB.2011.18B.5.255

Forward Vehicle Detection Algorithm Using Column Detection and Bird's-Eye View Mapping Based on Stereo Vision  

Lee, Chung-Hee (대구경북과학기술원)
Lim, Young-Chul (대구경북과학기술원)
Kwon, Soon (대구경북과학기술원)
Kim, Jong-Hwan (대구경북과학기술원)
Publication Information
The KIPS Transactions:PartB / v.18B, no.5, 2011 , pp. 255-264 More about this Journal
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.
Keywords
Stereo Vision; Vehicle Detection; Column Detection; Bird's-eye View Mapping; Obstacle Segmentation;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 C. Tzomakas and W. Seelen, "Vehicle Detection in Traffic Scenes Using Shadows," Technical report 98-06, Institute for Neuroinformatik, Ruht-university, 1998.
2 A. Broggi, M. Bertozzi, A. Fascioli, C.G.L., Bianco, and A. Piazzi, "Visual Perception of Obstacles and Vehicles for Platooning," IEEE Transactions on Intelligent Transportation Systems, Vol.1, No.3, pp.164-176, 2000.   DOI
3 H. G. Jung, Y. H. Lee, B. J. Kim, P. J. Yoon, and J. H. Kim, "Stereo Vision-Based Forward Obstacle Detection," International Journal of Automotive Technology, Vol.8, No.4, pp.493-504, 2007.
4 G. Toulminet, M. Bertozzi, S. Mousset, A. Bensrhair, and A. Broggi, "Vehicle Detection by Means of Stereo Vision-Based Obstacles Features Extraction and Monocular Pattern Analysis," IEEE Transactions on Image Processing, Vol.15, No.8, pp.2364-2375, 2006.   DOI   ScienceOn
5 R. Labayrade, D. Aubert, and J.-P. Tarel, "Real time obstacle detection on non flat road geometry through V-disparity representation," IEEE Intelligent Vehicles Symposium, Versailles, pp.646-651, 2002.
6 L. W. Tsai, J. W. Hsieh, and K. C. Fan, "Vehicle Detection Using Normalized Color and Edge Map," IEEE Transactions on Image Processing, Vol.16. No.3, pp.850-864, 2007.   DOI   ScienceOn
7 S. Zehang, B. George, and M. Ronald, "On-Road Vehicle Detection: A Review," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.28, No.5, pp.694-711, 2006.   DOI   ScienceOn
8 V. Kastinaki, M. Zervakis, and K. Kalaitozakis, "A survey of video processing techniques for traffic applications," Image, Vision, and Computing, Vol.21, No.4, pp.359-381, 2003.   DOI   ScienceOn
9 A. Broggi, P. Cerri, and P. C. Antonello, "Multi-resolution vehicle detection using artificial vision," 2004 IEEE Intelligent Vehicles Symposium, pp.310- 314, 2004.
10 이충희, 임영철, 권 순, 이종훈, "스테레오 비전 기반의 이동객체 용 실시간 환경 인식 시스템," 대한임베디드공학회, 제3권, 제3 호, pp.143-150, 2008
11 Chung-Hee Lee, Young-Chul Lim, Soon Kwon and Jong-Hun Lee, "Obstacle localization with a binarized v-disparity map using local maximum frequency values in stereo vision," International Conference on Signals, Circuits and Systems 2008, pp.1-4, Nov., 2008.
12 R. Hartley, and A. Zisserman, Multiple View Geometry, 2nd ed., Cambridge University Press, 2003.
13 T. Bdiri, F. Moutarde, and B. Steux, "Visual Object Categorization with New Keypoint-Based adaBoost Features," IEEE Intelligent Vehicles Symposium 2009, pp.393-398, 2009.
14 Brendan M. Collins, Alain L. Kornhauser, "Stereo vision for obstacle detection in autonomous navigation," DARPA grand challenge Princeton university technical paper, May, 2006.
15 Chung-Hee Lee, Young-Chul Lim, Soon Kwon and Jong-Hun Lee, "Stereo Vision-Based Vehicle Detection Using a Road Feature and Disparity Histogram," Optical Engineering, Vol.50, No.2, pp.027004-027004-23, 2011.   DOI   ScienceOn
16 이충희, 임영철, 권순, 이종훈, "U-시차맵과 조감도를 이용한 스테레오 비전 기반의 장애물체 검출 및 차량 검증 방법," 대한 전자공학회, 제47권, 제6호, pp.86-96, 2010   과학기술학회마을
17 이충희, 임영철, 권순, 이종훈, "스테레오 비전 기반의 도로 특징 정보 추출 및 장애물체 검출," 대한전자공학회, 제46권, 제6호, pp.28-37, 2009   과학기술학회마을
18 R. Labayrade, D. Aubert, "Onboard Road Obstacles Detection in Night Condition Using Binocular CCD Cameras," ESV 2003 Proceedings, pp.19-22, 2003.