Abstract
This paper shows how the output of a number of detection and tracking algorithms can be fused to achieve robust tracking of people in an indoor environment. The new tracking system contains three co-operating parts: i) an Active Shape Tracker using a PCA-generated model of pedestrian outline shapes, ii) a Region Tracker, featuring region splitting and merging for multiple hypothesis matching, and iii) a Head Detector to aid in the initialisation of tracks. Data from the three parts are fused together to select the best tracking hypotheses.
The new method is validated using sequences from surveillance cameras in a underground station. It is demonstrated that robust realtime tracking of people can be achieved with the new tracking system using standard PC hardware.
Chapter PDF
Similar content being viewed by others
References
I. Haritaoglu, D. Harwood, and L. S. Davis, “W4: Real-time surveillance of people and their actions,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, pp. 809–830, August 2000.
Q. Cai, A. Mitiche, and J. K. Aggarwal, “Tracking human motion in an indoor environment,” in Proceedings of the 2nd International Conference on ImageProcessing (ICIP’95), pp. 215–218, 1995.
C. Wren, A. Azarbayejani, T. Darrell, and A. Pentland, “Pfinder: Real-time tracking of the human body,” Tech. Rep. 353, MIT Media Laboratory Perceptual Computing Section, 1995.
F. Brémond and M. Thonnat, “Tracking multiple non-rigid objects in a cluttered scene,” in Proceedings of the 10th Scandinavian Conference on Image Analysis (SCIA’ 97), Lappeenranta, Finland, June 9-11, 1997, vol. 2, pp. 643–650, 1997.
A. M. Baumberg, Learning Deformable Models for Tracking Human Motion. PhD thesis, School of Computer Studies, University of Leeds, October 1995.
A. J. Lipton, H. Fujiyoshi, and R.S. Patil, “Moving target classification and tracking from real-time video,” in Proceedings of the DARPA Image Understanding Workshop (IUW’98), Monterey, CA, November 1998, pp. 129–136, 1998.
S. Khan, O. Javed, Z. Rasheed, and M. Shah, “Human tracking in multiple cameras,” in Proceedings of the 8th IEEE International Conference on Computer Vision (ICCV 2001), Vancouver, Canada. July 9-12, 2001, pp. 331–336, July 2001.
D. M. Gavrila and L. S. Davis, “Tracking of humans in action: A 3-D model-based approach,” in ARPA Image Understanding Workshop, (Palm Springs), pp. 737–746, February 1996.
H. Sidenbladh, M. J. Black, and D. J. Fleet, “Stochastic tracking of 3D human figures using 2D image motion,” in ECCV 2000, 6th European Conference on Computer Vision (D. Vernon, ed.), pp. 702–718, Springer Verlag, 2000.
J. L. Crowley and F. Bérard, “Multi-modal tracking of faces for video communication,” in Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR’97), pp. 640–645, 1997.
N. Oliver, A. P. Pentland, and F. Bérard, “Lafter: Lips and face real time tracker,” in Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR’97), pp. 123–129, 1997.
A. Baumberg, “Hierarchical shape fitting using an iterated linear filter,” in Proceedings of the Seventh British Machine Vision Conference (BMVC96), pp. 313–322, BMVA Press, 1996.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Siebel, N.T., Maybank, S. (2002). Fusion of Multiple Tracking Algorithms for Robust People Tracking. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds) Computer Vision — ECCV 2002. ECCV 2002. Lecture Notes in Computer Science, vol 2353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47979-1_25
Download citation
DOI: https://doi.org/10.1007/3-540-47979-1_25
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-43748-2
Online ISBN: 978-3-540-47979-6
eBook Packages: Springer Book Archive