Position estimation and multiple obstacles tracking method based on stereo vision system

IEEE Intelligent Vehicles Symposium, Proceedings

Volumn , Issue , 2009, Pages 72-77

  Lim, Young Chul ^a   Lee, Chung Hee ^a   Kwon, Soon ^a   Lee, Jong Hun ^a  

^a Daegu Gyeongbuk Institute of Science and Technology   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

DATA ASSOCIATION; ERROR VARIANCE; GEOMETRIC PROBLEMS; IMAGE DISTORTIONS; INTERACTING MULTIPLE MODEL; KAIMAN FILTER; MEAN ERRORS; MEASURE DISTANCE; MULTI LAYER PERCEPTRON; MULTIPLE OBJECTS; NEAREST NEIGHBORHOOD; NONSTATIONARY; POSITION ESTIMATION; RECTIFICATION PROCESS; SAMPLING ERRORS; STEREO CAMERAS; STEREO VISION SYSTEM; STRONG TRACKING; SUBMODELS; TARGET VEHICLES; TRACKING METHOD;

INTELLIGENT VEHICLE HIGHWAY SYSTEMS; MOBILE TELECOMMUNICATION SYSTEMS; NAVIGATION SYSTEMS; SETTLING TANKS; TRACKING (POSITION);

STEREO VISION;

EID: 70449561180     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IVS.2009.5164255     Document Type: Conference Paper

References (12)

1. S. Nedevschi, R. Danescu, D. Frentiu, T. Marita, F. Oniga, C. Pocol, R. Schmidt, and T. Graf, "High accuracy stereo vision system for far distance obstacle detection," in Proc. IEEE Intelligent Vehicles Symposium, pp. 292-297, June 2004.
2. B. Mobus, A. Joos, and U. Kolbe, "Multi-target multi-object radar tracking," in Proc. IEEE Intelligent Vehicles Symposium, pp. 489-494, June 2003.
3. J. Wang, F. Gao, S. Shi, and J. Wang, "A new method for distance and relative velocity measurement in vehicle collision warning system," in Proc. IEEE Intelligent Systems Design and Applications, pp. 1142-1147, Oct. 2006.
4. M. Shimizu, and M. Okutomi, "Precise sub-pixel estimation on area-based matching," in Proc. IEEE International Conference on Computer Vision, Vol. 1, pp. 90-97, July 2001.
5. E. Z. Psarakis, and G. D. Evangelidis, "An enhanced correlation-based method for stereo correspondence with subpixel accuracy," in Proc. IEEE International Conference on Computer Vision, Vol. 1, pp. 907-912, Oct. 2005.
6. Y.-C. Lim, C.-H. Lee, S. Kwon, and J.-h. Leem "Distance estimation algorithm for both long and short ranges based on stereo vision system," in Proc. IEEE Intelligent Vehicles Symposium, pp. 841-846, June 2007.
7. D. H. Zhou and P. M. Frank, "Strong tracking Kaiman 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
8. D.-J. Jwo, and S.-H. Wang, "Adaptive fuzzy strong tracking extended Kaiman filtering for GPS navigation," IEEE Sensors Journal, Vol. 7, No. 5, pp. 778-789, May. 2007
9. Y.-C. Lim, C.-H. Lee, S. Kwon, and J.-h. Lee "Tracking distance and velocity using a stereo vision system," International Symposium on SIP, pp. 48-50, Dec. 2008
10. 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.
11. X. R. Li, and Y. Bar-Shalom, "Tracking in clutter with nearest neighbor filters: analysis and performance," Aerospace and Electronic Systems, IEEE Trans. Aerospace and Electronic Systems, Vol. 32, no. 3, pp. 995-1010, Jul. 1996.
12. K. Choeychuen, P. Kumhom, and K. Chamnongthai, "An efficient implementation of the nearest neighbor based visual objects Tracking," International Symposium on ISPACS, pp. 574-577, Dec. 2006.