Abstract
This chapter discusses a human tracking method using multiple non-synchronous camera observations. In vision-based human tracking, self-occlusions and human-human occlusions are significant problems. Employing multiple viewpoints reduces these problems. Furthermore, the use of the non-synchronous observation approach eliminates the scalability problem inherent in synchronous systems. In the system described in this chapter, each camera independently observes a scene and thus does not require any special synchronization mechanism. The multiple observations are integrated with a Kalman-filter-based algorithm. With its non-synchronous approach, the system can obtain dense observations for the temporal axis, and the total performance is not affected by increasing the number of cameras. We developed the experimental system to accommodate five or more cameras. The system can track human positions in both single-person and multiple-person situations. Experimental results show the effectiveness of the non-synchronous multiple-camera system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Azarbayejani, A. and Pentland, A. (1996). Real-time self-calibrating stereo person tracking using 3-d shape estimation from blob features. In Proceedings of 13th International Conference on Pattern Recognition, pages 627–632.
Cai, Q. and Aggarwal, J. K. (1996). Tracking human motion using multiple cameras. In Proceedings of 13th International Conference on Pattern Recognition, pages 68–72.
Cox, I. J. (1993). A review of statical data association techniques for motion correspondence. International Journal of Computer Vision, 10:1:53–66.
Gavrila, D. M. and Davis, L. S. (1996). 3-d model-based tracking of humans in action: a multi-view approach. In Proc. of Computer Vision and Pattern Recognition, pages 73–80.
Johnson, M. P., Maes, P., and Darreil, T. (1994). Evolving visual routines. In Proc, of Artificial Life IV, pages 198–209.
Kalman, R. E. (1960). A new approach to linear filtering and prediction problems. Trans. ASME, J. Basic Eng., 82D(1):34–45.
Khan, S. and Shah, M. (2000). Tracking people in presence of occlusion. In Proceedings of 4th Asian Conference on Computer Vision, pages 1132–1137.
Matthies, L. and Shafer, S. A. (1987). Error modeling in stereo navigation. IEEE Robotics and Automation, RA-3(3):239–248.
Nakazawa, A., Kato, H., and Inokuchi, S. (1998). Human tracking using distributed vision systems. In Proc. of 14th International Conference on Pattern Recognition, pages 593–596.
O’Rourke, J. and Badler, N. J. (1980). Model-based image analysis of human motion using constraint propagation. IEEE Pattern Analysis and Machine Intelligence, 2(6):522–536.
Rohr, K. (1994). Towards model-based recognition of human movements in image sequences. CVGIP: Image Understanding, 59(1):94–115.
Segen, J. and Pingali, S. (1996). A camera-based system for tracking people in real time. In Proceedings of 13th International Conference on Pattern Recognition, pages 63–67.
Utsumi, A., Miyasato, T., Kishino, F., and Nakatsu, R. (1995). Real-time hand gesture recognition system. In Proc. of 2nd Asian Conference on Computer Vision, volume II, pages 667–671.
Utsumi, A., Miyasato, T., Kishino, F., and Nakatsu, R. (1996). Hand gesture recognition system using multiple cameras. In 13th International Conference on Pattern Recognition, pages 219–224.
Utsumi, A., Mori, H., Ohya, J., and Yachida, M. (1998). Multiple-view-based tracking of multiple humans. In Proc. of 14th International Conference on Pattern Recognition, pages 597–601.
Utsumi, A. and Ohya, J. (1997). Hand image segmentation using sequential-image-based hierarchical adaptation. In International Conference on Image Processing, pages 208–211.
Utsumi, A. and Ohya, J. (2000). Multiple-camera-based human tracking using non-synchronous observations. In Proceedings of Fourth Asian Conference on Computer Vision, pages 1034–1039.
Utsumi, A., Yang, H., and Tetsutani, N. (2001). Vision-based human tracking using a top-view approach with non-synchronous multiple observations. In Proceedings of International Workshop on Advanced Image Technology, pages 193–198.
Wren, C., Azarbayejani, A., Darrell, T., and Pentland, A. (1996). Pfinder: Real-time tracking of the human body. In SPIE proceeding vol 2615, pages 89–98.
Yamamoto, M. and Koshikawa, K. (1991). Human motion analysis based on a robot arm model. In Proc. of Computer Vision and Pattern Recognition, pages 664–665.
Yi, J.-W. and Oh, J.-H. (1997). Recursive resolving algorithm for multiple stereo and motion matches. Image and Vision Computing, 15:181–196.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer Science+Business Media New York
About this chapter
Cite this chapter
Utsumi, A. (2002). Tracking Multiple Persons from Multiple Camera Images. In: Analyzing Video Sequences of Multiple Humans. The Kluwer International Series in Video Computing, vol 3. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-1003-1_2
Download citation
DOI: https://doi.org/10.1007/978-1-4615-1003-1_2
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-5346-1
Online ISBN: 978-1-4615-1003-1
eBook Packages: Springer Book Archive