Browse > Article

Reliable State Estimation Method using Stereo Vision-Based Virtual Model Extended Kalman Filter  

Lim, Young-Chul (Daegu Gyeongbuk Instiute of Science & Technology)
Lee, Chung-Hee (Daegu Gyeongbuk Instiute of Science & Technology)
Lee, Jong-Hoon (Daegu Gyeongbuk Instiute of Science & Technology)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SC / v.48, no.3, 2011 , pp. 21-29 More about this Journal
Abstract
This paper presents a method that estimates distance and velocity of an object with reliability regardless of maneuver status of the target in stereo vision system. A stereo vision system can calculate a distance with disparity from left and right images. However, the distance estimation error may occur due to quantization error of image pixel. A sub-pixel interpolation method minimizes the quantization error and estimates accurate disparity with real value. Extended Kalman filter (EKF) was used to minimize the error covariance and estimate the object's velocity. However, divergence problem occurs due to model uncertainty when a target maneuvers highly, which makes the estimation error increase. In this paper, we propose a virtual model extended Kalman filter (VMEKF) method that minimizes the processing time and provides reliable estimation ability regardless of maneuver status. Computer simulations and experimental results in real road environments demonstrate that the proposed method gives a reliable estimation performance and reduces processing time under various maneuver status while comparing other estimation filters.
Keywords
stereo vision; state estimation; sub-pixel interpolation; Kalman filter; maneuver;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 D. -J. Jwo, S. -H. Wang, "Adaptive Fuzzy Strong Tracking Extended Kalman Filtering for GPS Navigation," IEEE Sensors Journal, Vol. 7, no. 5, pp. 778-789, May. 2007.   DOI
2 임영철, 이충희, 권순, 이종훈, "스테레오 비전에서 향상된 적응형 퍼지 칼만 필터를 이용한 거리 추정 기법," 전자공학회논문지, 제45권 SC편, 제6호, 108-116쪽, 2008년 11월.
3 고정환, "산업용 AGV 시스템의 적응적 경로설정을 위한 지능형 시각 시스템의 구현," 전자공학회논문지, 제46권 IE편, 제1호, 23-30쪽, 2009년 3월
4 R. Zabih, J. Woodfill, "Non-parametric local transforms for computing visual correspondence." In Proceedings of ECCV, Vol. 2, pp. 151-158, Stockholm, Sweden, May 1994.
5 P. F. Felzenszwalb, D. P. Huttenlocher, "Efficient Belief Propagation for Early Vision," International Journal of Computer Vision, Vol. 70, no. 1, pp. 41-54, Oct. 2006.   DOI   ScienceOn
6 M. Bertozz, A. Broggia, A. Fasciolia, "Stereo inverse perspective mapping: theory and applications," Image and Vision Computing, Vol. 16, no. 8, pp. 585-590, June 1998.   DOI   ScienceOn
7 M. Shimizu, M. Okutomi, "Precise sub-pixel estimation on area-based matching," IEEE International Conference on Computer Vision, Vol. 1, pp. 90-97, Vancouver, Canada, July 2001.
8 E. Z. Psarakis, G. D. Evangelidis, "An enhanced correlation-based method for stereo correspondence with subpixel accuracy," IEEE International Conference on Computer Vision, Vol. 1, pp. 907-912, Beijing, China, Oct. 2005.
9 Y. C. Lim, C. H. Lee, S. Kwon, W. Y. Jung. "Distance estimation algorithm for both long and short ranges based on stereo vision system," IEEE Intelligent Vehicles Symposium, pp. 841-846, Eindhoven, Netherlands, June 2008.
10 Y. C. Lim, C. H. Lee, S. Kwon, J. h. Lee, "Tracking Distance and Velocity using a Stereo Vision System," International Conference on Future Generation Communication and Networking Symposia, pp. 48-50, Hainan Island, China, Dec. 2008.
11 D. H. Zhou and P. M. Frank, "Strong tracking Kalman filtering of non-linear time-varying stochastic systems with colored noise: Application to parameter estimation and empirical robustness analysis," Int. J. Control, Vol. 65, no. 2, pp. 295-307, Sep. 1996.   DOI   ScienceOn
12 Y. C. Lim, C. H. Lee, S. Kwon, J. h. Lee, "Position estimation and multiple obstacles tracking method based on stereo vision system," IEEE Intelligent Vehicles Symposium, pp. 72-77, Xi'an, China, June 2009.
13 P. Pan, X. Feng, F. Li, "Self-adaptive Constant Acceleration Model and Its Tracking Algorithm Based on STF," International Conference on Mechatronics and Automation, pp. 3784-3789, Aug. 2007.
14 Z. Jia, A. Balasuriya, and S. Challa, "Vision based data fusion for autonomous vehicles target tracking using interacting multiple dynamic models," Computer vision and image understanding, Vol. 109, no. 1, pp. 1-21, Jan. 2008.   DOI   ScienceOn