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Robust 3D visual tracking for moving object using pan/tilt stereo cameras  

Cho, Che-Seung (대구기계부품연구원)
Chung, Byeong-Mook (영남대학교 기계공학과)
Choi, In-Su (상주대학교 자동차공학과)
Nho, Sang-Hyun (대구공업대학교 자동차과)
Lim, Yoon-Kyu (울산발전진흥재단 전략발전기획단)
Publication Information
Journal of the Korean Society for Precision Engineering / v.22, no.9, 2005 , pp. 77-84 More about this Journal
Abstract
In most vision applications, we are frequently confronted with determining the position of object continuously. Generally, intertwined processes ire needed for target tracking, composed with tracking and control process. Each of these processes can be studied independently. In case of actual implementation we must consider the interaction between them to achieve robust performance. In this paper, the robust real time visual tracking in complex background is considered. A common approach to increase robustness of a tracking system is to use known geometric models (CAD model etc.) or to attach the marker. In case an object has arbitrary shape or it is difficult to attach the marker to object, we present a method to track the target easily as we set up the color and shape for a part of object previously. Robust detection can be achieved by integrating voting-based visual cues. Kalman filter is used to estimate the motion of moving object in 3D space, and this algorithm is tested in a pan/tilt robot system. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.
Keywords
Kalman Filter; Visual Tracking; Moving Object; Cue Integration;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 Papanikolopoulous, N. P. and Khosla, P. K., 'Adaptive robotic visual tracking: Theory and experiments,' IEEE Transaction on Automation and Control, Vol.38, pp. 429-445, 1993   DOI   ScienceOn
2 Allen, P., 'Automated tracking and grasping of a moving object with a robotic hand-eye system,' IEEE Transactions on robotics and automation, Vol. 9,p.152, 1993   DOI   ScienceOn
3 Yi, J. W., Yang, T. S. and Oh, J. H., 'Estimation of depth and 3D motion parameters of moving objects with multiple stereo images by using Kalman filter,' IEEE IECON 21st International Conference on Industrial Electronics, Control, and Instrumentation, Vol.2, pp.1225-1230, Nov. 1995
4 Gonzalez, R. C. and Wood, R. E., 'Digital Image Processing,' Addison Wesley, 1992
5 Heijden, F., 'Image based Measurement system,' Wiley, 1994
6 Grewal, M. S. and Andrews, A. P., 'Kalman filtering theory and practice,' Prentice hall, 1993
7 Hirzinger, G., Fisher, M., Brunner, B., Koeppe, R., Otter, M., Grebenstein, M. and Schafer, I., 'Advanced in robotics: The DLR experience,' International Journal of robotics research, Vol. 18, pp. 1064-1087, Nov. 1999   DOI
8 Kopp-Borotsching, H. and Pinz, A., 'A new concept for active fusion in image understanding applying fuzzy set theory,' Fifth IEEE International Conference on Fuzzy Systems, Vol. 2, pp793 -799, sep. 1996   DOI
9 Parhami, B., 'Voting algorithm,' IEEE Transaction on Reliability, Vol.43, No.4, pp. 617-629, 1994   DOI
10 Bloch, I., 'Information combination operators for data fusion,' IEEE Transaction on System Man and Cybernatics, Vol.26, No.1, pp.42-52, 1996   DOI
11 Kragic, D. and Christensen, H. I., 'Cue integration for visual servoing,' IEEE Transaction on robotics and automation, Vol.17, No.1, pp. 18-26, 2001   DOI   ScienceOn
12 Wang, J. and Wilson, W. J., '3-D relative position and orientation estimation using Kalman filter for robot control,' IEEE Iinternational conference on Robotics and automation, pp. 2638-2645, 1992
13 Maniere, E. C., Couvignou, P. and Khosla, P. K., 'Robotic contour following based on visual servoing,' Proceedings of the IEEE/RSJ International Conference on intelligent robotics and system, pp. 716-722, July, 1993   DOI
14 Kollnig, H. and Nagel, H., '3D pose estimation by directly matching poly-hedral models to gray value gradients,' International Journal of Computer Vision, Vol. 23, No.3, pp. 282-302,1997
15 Lim,Y. N. and Lee, S. C., 'Real-time Target Tracking System by Extended Kalman Filter,' Journal of the Korean Society of Precision Engineering, pp. 175-181,1998   과학기술학회마을
16 He, D., Hujic, D., Mills, J. K. and Benhabib, B., 'Moving object recognition using premarking and active vision,' Proceedings of the IEEE International Conference on robotics and automation, pp. 1980-1985, April, 1996   DOI
17 Cretual, A., 'Complex object tracking by visual servoing based on 2D image motion,' Proceedings 14th International Conference on Pattern Recognition, Vol. 2, pp.1251 -1254,1998   DOI