Complex ground plane detection based on V-disparity map in off-road environment

The work in the paper is to apply image pairs gathered by vehicle-mounted stereo cameras to detect the position of ground. The research focus is to detect complex ground planes for vehicle from image pairs based on investigating of the V-disparity map. This paper describes an enhancement of traditional V-disparity algorithm for off-road environment especially. The enhanced method can acquire the parameters of ground plane such as slope and pit. Experimental results with real data from stereo cameras mounted on a vehicle moving in off-road environment are presented. According to the simulation results, by comparison with traditional V-disparity algorithm, the average of recognition rate for ground using the enhanced V-disparity algorithm increases from 37.68% to 86.67%. The enhanced method can minimize errors of ground representation, and it is an efficient way to extract more details of ground structure than traditional V-disparity algorithm. The process is without dealing with any explicit structure such as road edges or lane marking. So it can be used for autonomous vehicle driving in off-road environment in the future.

[1]  Zhang Zhao-yang.  Depth Extraction Method Based on Multi-view Stereo Matching , 2010 .

[2]  Masatoshi Okutomi,et al.  Ego-motion estimation by matching dewarped road regions using stereo images , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[3]  N. Hautiere,et al.  Road Segmentation Supervised by an Extended V-Disparity Algorithm for Autonomous Navigation , 2007, 2007 IEEE Intelligent Vehicles Symposium.

[4]  Jun Zhao,et al.  Global Correlation Based Ground Plane Estimation Using V-Disparity Image , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[5]  Junichi Maruyama,et al.  Robust estimation of planar regions for visual navigation using sequential stereo images , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[6]  Andreas Birk,et al.  Fast plane detection and polygonalization in noisy 3D range images , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Alberto Broggi,et al.  Obstacle Detection with Stereo Vision for Off-Road Vehicle Navigation , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[8]  Hu Shu-shu.  Color Stereo Image-Based Obstacle Detection with Complicated Backgrounds , 2007 .

[9]  Nan-Feng Xiao,et al.  Plane extraction for navigation of humanoid robot , 2011 .

[10]  Jean-Philippe Tarel,et al.  Real time obstacle detection in stereovision on non flat road geometry through "v-disparity" representation , 2002, Intelligent Vehicle Symposium, 2002. IEEE.

[11]  Didier Aubert,et al.  A single framework for vehicle roll, pitch, yaw estimation and obstacles detection by stereovision , 2003, IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683).

[12]  Ma Yide,et al.  Application of Pulsed Coupled Neural Network in Vehicle License Plate Location , 2010 .

[13]  Xinxin Zhao,et al.  An obstacle detection algorithm based on U-V disparity map analysis , 2010, 2010 IEEE International Conference on Information Theory and Information Security.

[14]  C. Teoh,et al.  Ground plane detection for autonomous vehicle in rainforest terrain , 2010, 2010 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology.

[15]  Keiichi Uchimura,et al.  A complete U-V-disparity study for stereovision based 3D driving environment analysis , 2005, Fifth International Conference on 3-D Digital Imaging and Modeling (3DIM'05).

[16]  Le Thanh Sach,et al.  A robust road profile estimation method for low texture stereo images , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[17]  Naim Dahnoun,et al.  Obstacle detection with 3D camera using U-V-Disparity , 2011, International Workshop on Systems, Signal Processing and their Applications, WOSSPA.

[18]  John G. Rarity,et al.  U-V-Disparity based Obstacle Detection with 3D Camera and steerable filter , 2011, 2011 IEEE Intelligent Vehicles Symposium (IV).

[19]  Shang Guan.  Research of Obstacle Recognition Technology Based on U-V Disparity , 2011 .