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.
This work was supported by the project L.A.I.C.A. (Laboratorio di Ambient Intelligence per una Città Amica), funded by the Regione Emilia-Romagna, Italy.
Chapter PDF
Similar content being viewed by others
Keywords
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
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)
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)
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)
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)
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)
Dockstader, S., Tekalp, A.: Multiple camera tracking of interacting and occluded human motion. Proc. of the IEEE 89, 1441–1455 (2001)
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)
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)
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)
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)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Calderara, S., Prati, A., Vezzani, R., Cucchiara, R. (2005). Consistent Labeling for Multi-camera Object Tracking. In: Roli, F., Vitulano, S. (eds) Image Analysis and Processing – ICIAP 2005. ICIAP 2005. Lecture Notes in Computer Science, vol 3617. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553595_148
Download citation
DOI: https://doi.org/10.1007/11553595_148
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28869-5
Online ISBN: 978-3-540-31866-8
eBook Packages: Computer ScienceComputer Science (R0)