Advanced SearchSearch Tips
A Study on Vehicle Ego-motion Estimation by Optimizing a Vehicle Platform
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
A Study on Vehicle Ego-motion Estimation by Optimizing a Vehicle Platform
Song, Moon-Hyung; Shin, Dong-Ho;
This paper presents a novel methodology for estimating vehicle ego-motion, i.e. tri-axis linear velocities and angular velocities by using stereo vision sensor and 2G1Y sensor (longitudinal acceleration, lateral acceleration, and yaw rate). The estimated ego-motion information can be utilized to predict future ego-path and improve the accuracy of 3D coordinate of obstacle by compensating for disturbance from vehicle movement representatively for collision avoidance system. For the purpose of incorporating vehicle dynamic characteristics into ego-motion estimation, the state evolution model of Kalman filter has been augmented with lateral vehicle dynamics and the vanishing point estimation has been also taken into account because the optical flow radiates from a vanishing point which might be varied due to vehicle pitch motion. Experimental results based on real-world data have shown the effectiveness of the proposed methodology in view of accuracy.
ego-motion;Kalman filter;stereo camera;optical flow;vehicle lateral dynamics;
 Cited by
G. P. Stein, O. Mano, and A. Shashua, "A robust method for computing vehicle ego-motion," Proc. of the 2000 IEEE, Intelligent Vehicle Symposium, Dearborn, MI, USA, pp. 362-368, Oct. 2000.

K. Yamaguchi, T. Kato, and Y. Ninomica, "Vehicle ego-motion estimation and moving object detection using a monocular camera," 18th International Conference on Pattern Recognition (ICPR), Hong Kong, vol. 4, pp. 610-613, 2006.

O. Pink, F. Moosmann, and A. Bachmann, "Visual feature for vehicle localization and ego-motion estimation," Proceedings of the 2009 IEEE, Intelligent Vehicles Symposium, Xi'an, China, pp. 254-260, Jun. 2009.

F. Raudies and H. Neumann, "An efficient linear method for the estimation of ego-motion from optical flow," 31st DAGM Symposium, Jena, Germany, pp. 11-20, Sep. 2009.

A. Bak, S. Bouchafa, and D. Aubert, "Detection of independently moving objects through stereo vision and ego-motion extraction," Proc. of the 2010 IEEE Intelligent Vehicle Symposium, San Diego, USA, vol. IV, pp. 863-870, Jun. 2010.

Y. W. Choi, K. S. Choi, J. W. Choi, and S. G. Lee, "Localization using ego motion based on fisheye warping image," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 20, no. 1, pp. 70-77, 2014. crossref(new window)

Y. W. Choi, J. W. Choi, Y. Y. Dai, and S. G. Lee, "Omni-directional vision SLAM using a motion estimation method based on fisheye image," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 20, no. 8, pp. 686-874, 2014.

A. Mallet, S. Lacroix, and L. Gallo, "Position estimation in outdoor environments using pixel tracking and stereovision," Proc. of the 2000 IEEE International Conference on Robotics and Automation ICRA 2000, San Francisco, USA, vol. 4, pp. 3519-3524, Apr. 2000.

C.-F. Lin, "Three-dimensional relative positioning and tracking using LDRI," US patent no. 6, 677,941, Jan. 13, 2004.

W. O. Nassir and G. Panin, "3D point tracking and pose estimation of a space object using stereo images," 21st International Conference on Pattern Recognition (ICPR 2012), Tsukuba, Japan, pp. 796-800, Nov. 2012.

U. Franke, C. Rabe, H. Badino, and S. Gehrig, "6D-vision: fusion of stereo and motion for robust environment perception," 27th DAGM Symposium, Vienna, Austria, pp. 216-223, Aug.-Sep. 2005.

H. Badino, U. Franke, C. Rabe, and S. Gehrig, "Stereo vision based detection of moving objects under strong camera motion," First International Conference on Computer Vision Theory and Applications, Setubal, Portugal, pp. 25-28. Feb. 2006.

C. Rabe, U. Franke, and S. Gehrig, "Fast detection of moving objects in complex," Proc. of the 2007 IEEE, Intelligent Vehicle Symposium, Istanbul, Turkey, pp. 398-403, Jun. 2007.

B. Kitt, B. Ranft, and H. Lategahn, "Detection and tracking of independently moving objects in urban environments," 13th International IEEE Conference on Intelligent Transportation Systems (ITSC), Funchal, Portugal, pp. 1396-1401, Jun. 2010.

R. Rajamani, Vehicle Dynamics and Control, Springer-Verlag New York Inc, 2005.

H. C. Longuet-Higgins and K. Prazdny, "The interpretation of a moving retinal image," Proc. of the Royal Society of London, Series B, Biological Sciences, vol. 208, no. 1173, pp. 385-397, Jul. 1980.

C. F. Keller, M. Enzweiler, M. Rohrbach, L. D. Fernandez, C. Schnorr, and D. M. Gavrila, "The benefits of dense stereo for pedestrian detection," IEEE Intelligent Transportation Systems, vol. 12, no. 4, pp. 1096-1106, Dec. 2011. crossref(new window)