Vehicle Trajectory from an Uncalibrated Stereo-Rig with Super-Homography

We present in this article an original manner to estimate the trajectory of a vehicle running in urban-like areas. The method consists in extracting then tracking features (points, lines) with an uncalibrated stereo-rig from the road assumed as a plane to compute homographies relative to the camera(s) motions. The purposed method copes with the dense traffic conditions: the free space required (first ten meters in front of the vehicle) is slightly equivalent to the security distance between two vehicles. Experimental issues from real data are presented and discussed

[1]  Nicolas Simond,et al.  Trajectography of an uncalibrated stereo rig in urban environments , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[2]  Amnon Shashua,et al.  A robust method for computing vehicle ego-motion , 2000, Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511).

[3]  Y. Shirai,et al.  A View-Based Outdoor Navigation Using Object Recognition Robust to Changes of Weather and Seasons , 2005 .

[4]  Nicolas Simond,et al.  Homography from a vanishing point in urban scenes , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[5]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[6]  Peter K. Allen,et al.  Localization methods for a mobile robot in urban environments , 2004, IEEE Transactions on Robotics.

[7]  Seth J. Teller,et al.  Automatic recovery of relative camera rotations for urban scenes , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[8]  Larry H. Matthies,et al.  Real-time detection of moving objects in a dynamic scene from moving robotic vehicles , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[9]  Roberto Cipolla,et al.  Multi-view Constraints between Collineations: Application to Self-Calibration from Unknown Planar Structures , 2000, ECCV.

[10]  Michel Dhome,et al.  Towards an alternative GPS sensor in dense urban environment from visual memory , 2004, BMVC.

[11]  Maurizio Pilu,et al.  A direct method for stereo correspondence based on singular value decomposition , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[12]  Michael Brady,et al.  Road feature detection and estimation , 2003, Machine Vision and Applications.

[13]  H. C. Longuet-Higgins,et al.  An algorithm for associating the features of two images , 1991, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[14]  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).

[15]  Takeo Kanade,et al.  Transforming camera geometry to a virtual downward-looking camera: robust ego-motion estimation and ground-layer detection , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[16]  Christian Laugier,et al.  Geometrical model to drive vision systems with error propagation , 2004, ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004..