BUILDING A NORMALITY SPACE OF EVENTS - A PCA Approach to Event Detection

Angelo Cenedese, Ruggero Frezza, Enrico Campana, Giambattista Gennari, Giorgio Raccanelli

Abstract

The detection of events in video streams is a central task in the automatic vision paradigm, and spans heterogeneous fields of application from the surveillance of the environment, to the analysis of scientific data. Actually, although well captured by intuition, the definition itself of event is somewhat hazy and depending on the specific application of interest. In this work, the approach to the problem of event detection is different in nature. Instead of defining the event and searching for it within the data, a normality space of the scene is built from a chosen learning sequence The event detection algorithm works by projecting any newly acquired image onto the normality space so as to calculate a distance from it that represents the innovation of the new frame, and defines the metric for triggering an event alert.

References

  1. Clarkson, B. and Pentland, A. (2000). Framing through peripheral perception. In Proceedings of the IEEE international conference on image processing (ICIP 2000), Vancouver, Canada, pages 38-41.
  2. CogViSys (2007). [online].
  3. Collins, R. T., Lipton, A. J., and Kanade, T. (2000). Special issue on video surveillance. IEEE Trans. On Pattern Analysis and Machine Intelligence, 22(8).
  4. ECCV06 (2006). 6th ieee international workshop on visual surveillance. In conjunction with the 9th European Conference on Computer Vision 2006, Graz, Austria.
  5. Friedman, N. and Russell, S. (1997). Image segmentation in video sequences: A probabilistic approach. In Annual Conference on Uncertainty in Artificial Intelligence, volume 2, pages 175-181.
  6. Golub, G. and VanLoan, C. (1996). Matrix Computations. Johns Hopkins University Press, Baltimore.
  7. Hu, W., Tan., T., Wang, L., and Maybank, S. (2004). A survey on visual surveillance of object motion and behaviours. IEEE Trans. On Systems, Man and Cybernetics Part C, Applications and Reviews, 34(3):334- 352.
  8. ICML06 (2006). Machine learning algorithms for surveillance and event detection. In conjunction with the International Conference on Machine Learning 2006, Carnegie Mellon University, Pittsburgh, PA.
  9. Jain, R., Militzer, D., and Nagel, H. (1977). Separating nonstationary from stationary scene components in a sequence of real world tv-images. In International Joint Conference on Artificial Intelligence, pages 612-618.
  10. Medioni, G. G., Cohen, I., Bremond, F., Hongeng, S., and Nevatia, R. (2001). Event detection and analysis from video streams. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(8):873-889.
  11. Monnet, A., Mittal, A., Paragios, N., and Ramesh, V. (2003). Background modeling and subtraction of dynamic scenes.
  12. Radke, R. J., Andra, S., Al-Kofahi, O., and Roysam, B. (2005). Image change detection algorithms: A systematic survey. IEEE Transactions on Image Processing, 14(3):294-307.
  13. Regazzoni, C., Ramesh, V., and Foresti, G. L. (2001). Special issue on video communication, processing and understanding for third generation surveillance systems. Proceedings of the IEEE, 89(10).
  14. Satoh, Y., Tanahashi, H., Wang, C., Kaneko, S., Niwa, Y., and Yamamoto, K. (2002). Robust event detection by radial reach filter. In 16th ICPR, International Conference on Pattern Recognition, volume 2, pages 623- 626.
  15. VSAM (2007). http://www.cs.cmu.edu/ vsam/. [online].
  16. Zelnik-Manor, L. and Irani, M. (2001). Event-based analysis of video. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR 2001), Kauai, Hawaii, December 2001, pages 123- 130.
Download


Paper Citation


in Harvard Style

Cenedese A., Frezza R., Campana E., Gennari G. and Raccanelli G. (2008). BUILDING A NORMALITY SPACE OF EVENTS - A PCA Approach to Event Detection . In Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008) ISBN 978-989-8111-21-0, pages 551-554. DOI: 10.5220/0001085905510554


in Bibtex Style

@conference{visapp08,
author={Angelo Cenedese and Ruggero Frezza and Enrico Campana and Giambattista Gennari and Giorgio Raccanelli},
title={BUILDING A NORMALITY SPACE OF EVENTS - A PCA Approach to Event Detection},
booktitle={Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)},
year={2008},
pages={551-554},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001085905510554},
isbn={978-989-8111-21-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)
TI - BUILDING A NORMALITY SPACE OF EVENTS - A PCA Approach to Event Detection
SN - 978-989-8111-21-0
AU - Cenedese A.
AU - Frezza R.
AU - Campana E.
AU - Gennari G.
AU - Raccanelli G.
PY - 2008
SP - 551
EP - 554
DO - 10.5220/0001085905510554