Consistent Labeling for Multi-camera Object Tracking

  • Simone Calderara
  • Andrea Prati
  • Roberto Vezzani
  • Rita Cucchiara
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)

Abstract

In this paper, we present a new approach to multi-camera object tracking based on the consistent labeling. An automatic and reliable procedure allows to obtain the homographic transformation between two overlapped views, without any manual calibration of the cameras. Object’s positions are matched by using the homography when the object is firstly detected in one of the two views. The approach has been tested also in the case of simultaneous transitions and in the case in which people are detected as a group during the transition. Promising results are reported over a real setup of overlapped cameras.

Keywords

Ground Plane Support Point Multiple Camera Multiple People Simultaneous Transition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Khan, S., Shah, M.: Consistent labeling of tracked objects in multiple cameras with overlapping fields of view. IEEE Trans. on PAMI 25, 1355–1360 (2003)Google Scholar
  2. 2.
    Li, J., Chua, C., Ho, Y.: Color based multiple people tracking. In: Proc. of IEEE Intl Conf. on Control, Automation, Robotics and Vision., vol. 1, pp. 309–314 (2002)Google Scholar
  3. 3.
    Krumm, J., Harris, S., Meyers, B., Brumitt, B., Hale, M., Shafer, S.: Multi-camera multiperson tracking for easyliving. In: Proc. of IEEE Intl Workshop on Visual Surveillance, pp. 3–10 (2000)Google Scholar
  4. 4.
    Kang, J., Cohen, I., Medioni, G.: Continuous tracking within and across camera streams. In: Proc. of IEEE Int’l Conference on Computer Vision and Pattern Recognition., vol. 1, pp. I-267–I-272 (2003)Google Scholar
  5. 5.
    Chang, S., Gong, T.H.: Tracking multiple people with a multi-camera system. In: Proc. of IEEE Workshop on Multi-Object Tracking, pp. 19–26 (2001)Google Scholar
  6. 6.
    Dockstader, S., Tekalp, A.: Multiple camera tracking of interacting and occluded human motion. Proc. of the IEEE 89, 1441–1455 (2001)CrossRefGoogle Scholar
  7. 7.
    Chang, T., Gong, S., Ong, E.: Tracking multiple people under occlusion using multiple cameras. In: Proc. of British Machine Vision Conf., vol. 2, pp. 566–576 (2000)Google Scholar
  8. 8.
    Mittal, A., Davis, L.: Unified multi-camera detection and tracking using region-matching. In: Proc. of IEEE Workshop on Multi-Object Tracking, pp. 3–10 (2001)Google Scholar
  9. 9.
    Yue, Z., Zhou, S., Chellappa, R.: Robust two-camera tracking using homography. In: Proc. of IEEE Intl Conf. on Acoustics, Speech, and Signal Processing, vol. 3, pp. 1–4 (2004)Google Scholar
  10. 10.
    Cucchiara, R., Grana, C., Tardini, G.: Track-based and object-based occlusion for people tracking refinement in indoor surveillance. In: Proc. of ACM 2nd International Workshop on Video Surveillance & Sensor Networks, pp. 81–87 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Simone Calderara
    • 1
  • Andrea Prati
    • 2
  • Roberto Vezzani
    • 1
  • Rita Cucchiara
    • 1
  1. 1.Dipartimento di Ingegneria dell’InformazioneUniversity of Modena and Reggio EmiliaModenaItaly
  2. 2.Dipartimento di Scienze e Metodi dell’IngegneriaUniversity of Modena and Reggio EmiliaReggio EmiliaItaly

Personalised recommendations