Abstract
Tracking people from a moving platform is a useful skill for the coming generation of service and human-interaction robots. It is also a challenging problem, involving sensing, interpretation, planning, and control, all in a real time and dynamic environment. Techniques used in existing people-trackers that operate from fixed locations, noting changes against a fixed background, are not applicable. Instead, we apply a vision-based approach using real-time stereo and 3D reconstruction, that explicitly models both foreground and background objects in an efficient manner. The main novelties of our approach include (1) remapping the stereo disparities to an orthographic “occupancy map”, which simplifies person modeling, and (2) updating a background occupancy map based on robot motion. The current version of our system, running on a Pioneer II mobile robot, can follow people at up to 1.2 m/s in an indoor environment.
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References
LaValle, S., D. Lin, L.J. Guibas, J.C. Latombe, and R. Motwani. Finding an Unpredictable Target in a Workspace with Obstacles. Proc. 1997 IEEE ICRA.
Haritaoglu, I., D. Harwood, and L.S. Davis. W 4 S: A Real-Time System for Detecting and Tracking People in 2 1/2D. in European Conference on Computer Vision. 1998. Freiburg, Germany.
Wren, C, et al., Pfinder: Real-Time Tracking of the Human Body. IEEE Transactions of Pattern Analysis and Machine Intelligence, 1997. 19(7).
Beymer, D. and K. Konolige. Real-Time Tracking of Multiple People Using Stereo. in IEEE Frame Rate Workshop. 1999. Corfu, Greece.
Eveland, C., K. Konolige, and R. C. Bolles. Background modeling for segmentation of video-rate stereo sequences. CVPR98, Santa Barbara, CA.
Jojic, N., M. Turk, and T.S. Huang. Tracking Self-Occluding Articulated Objects in Dense Disparity Maps. in ICCV 1999. Kerkyra, Greece.
Lin, M.H. Tracking Articulated Objects in Real-Time Range Image Sequences. in ICCV 1999. Kerkyra, Greece.
Darrell, T., G. Gordon, and M. Harville. Integrated person tracking using stereo, color, and pattern detection. in CVPR 1998. Santa Barbara, California.
Huber, E. and D. Kortenkamp. Using stereo vision to pursue moving agents with a mobile robot. ICRA, 1995.
Robots Alive! Scientific American Frontiers television show on SRI’s FLAKEYrobot, October 1996.
Cham, T.-J. and J.M. Rehg. A Multiple Hypothesis Approach to Figure Tracking. in IEEE Conference on Computer Vision and Pattern Recognition. 1999. Fort Collins, CO, pp. 239–245.
Isard, M. and A. Blake. Contour Tracking by Stochastic Propagation of Conditional Density. in European Conference on Computer Vision. 1996.
Konolige, K. Small Vision Systems: Hardware and Implementation. in Eighth International Symposium on Robotics Research. 1997. Hayama, Japan.
Tsai, R.Y., A Versatile Camera Calibration Technique for High-Accuracy 3D Machine Vision Metrology Using Off-the-Shelf TV Cameras and Lenses. IEEE JRA, 1987. RA-3(4).
K. Konolige. A Gradient Method for Realtime Robot Control. IROS, 2000.
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© 2003 Springer-Verlag Berlin Heidelberg
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Beymer, D., Konolige, K. (2003). Tracking People from a Mobile Platform. In: Siciliano, B., Dario, P. (eds) Experimental Robotics VIII. Springer Tracts in Advanced Robotics, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36268-1_20
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DOI: https://doi.org/10.1007/3-540-36268-1_20
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