Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
Springer Nature Link
Log in

Unusual Activity Analysis in Video Sequences

  • Conference paper
Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4482))

Abstract

We present a unique representation scheme for events in an area under surveillance, which provides a mechanism to analyze videos from multiple perspectives for unusual activity analysis. We propose clustering in event component spaces and define algebraic operations on these clusters to find co-occurrences of event components. A usualness measure for clusters is proposed that not only gives a measure on how usual or unusual an activity is, but also a basis for analyzing and predicting the possibly usual or unusual activities that can occur in the surveillance region.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Hongeng, S., Bremond, F., Nevatia, R.: Representation and optimal recognition of human activities. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1818–1825 (2000)

    Google Scholar 

  2. Zelnik-Manor, L., Irani, M.: Event-based analysis of video. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 123–130 (2001)

    Google Scholar 

  3. Kettnaker, V.: Time-dependent HMMs for visual intrusion detection. In: IEEE Workshop on Event Mining: Detection and Recognition of Events in Video (2003)

    Google Scholar 

  4. Medioni, G., et al.: Event detection and analysis from video stream. IEEE Trans. on Pattern Analysis and Machine Intelligence 23(8), 873–889 (2001)

    Article  Google Scholar 

  5. Moore, D., Essa, I., Hayes, M.: Exploiting human actions and object context for recognition tasks. In: International Conference on Computer Vision, pp. 80–86 (1999)

    Google Scholar 

  6. Starner, T., Pentland, A.: Real-time american sign language recognition from video using hidden Markov models. In: SCV, pp. 265–270 (1995)

    Google Scholar 

  7. Brand, M., Oliver, N., Pentland, A.: Coupled hidden Markov models for complex action recognition. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 994–999 (1997)

    Google Scholar 

  8. Oliver, N., Rosario, B., Pentland, A.: A Bayesian computer vision system for modeling human interactions. In: International Conference on Computer Vision Systems, pp. 255–272 (1999)

    Google Scholar 

  9. Yamato, J., Ohya, J., Ishii, K.: Recognizing human action in time-sequential images using hidden Markov model. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 379–385 (1992)

    Google Scholar 

  10. Wilson, A., Bobick, A.: Recognition and interpretation of parametric gesture. In: International Conference on Computer Vision, pp. 329–336 (1996)

    Google Scholar 

  11. Ivanov, Y., Bobick, A.: Recognition of visual activities and interactions by stochastic parsing. IEEE Trans. on Pattern Analysis and Machine Intelligence 22(8), 852–872 (2000)

    Article  Google Scholar 

  12. Moore, D., Essa, I.: Recognizing multitasked activities from video using stochastic context-free grammar. In: AAAI (2002)

    Google Scholar 

  13. Shi, Y., Bobick, A.: Representation and recognition of activity using propagation nets. In: 16th International Conference on Vision Interface (2003)

    Google Scholar 

  14. Buxton, H., Gong, S.: Advanced visual surveillance using Bayesian networks. In: International Conference on Computer Vision, pp. 111–123 (1995)

    Google Scholar 

  15. Madabhushi, A., Aggarwal, J.: A Bayesian approach to human activity recognition. In: 2nd International Workshop on Visual Surveillance, pp. 25–30 (1999)

    Google Scholar 

  16. Hongeng, S., Nevatia, R.: Multi-agent event recognition. In: International Conference on Computer Vision, pp. 84–93 (2001)

    Google Scholar 

  17. Mahajan, D., et al.: A framework for activity recognition and detection of unusual activities. In: Indian Conference on Computer Vision, Graphics and Image Processing (2004)

    Google Scholar 

  18. Zhong, H., Shi, J., Visontai, M.: Detecting unusual activity in video. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 819–826 (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Delhi, New Delhi, India

    Ayesha Choudhary & Subhashis Banerjee

  2. Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, India

    Santanu Chaudhury

Authors
  1. Ayesha Choudhary
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Santanu Chaudhury
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Subhashis Banerjee
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Dept. of Computer Science and Engineering, York University, M3J 1P3, Toronto, Ontario, Canada

    Aijun An

  2. Institute of Computing Sciences, Poznań University of Technology, ul. Piotrowo 2, 60–965, Poznań, Poland

    Jerzy Stefanowski

  3. Department of Applied Computer Science, University of Winnipeg, R3B 2E9, Winnipeg, Manitoba, Canada

    Sheela Ramanna

  4. Department of Computer Science, University of Regina, S4S 0A2, Regina, Saskatchewan, Canada

    Cory J. Butz

  5. Department of Electrical and Computer Engineering, University of Alberta, T6G 2V4, Edmonton, Alberta, Canada

    Witold Pedrycz

  6. Institute of Compuer Science and Technology, Chongqing University of Posts and Telecommunications, 40065, Chongqing, P.R. China

    Guoyin Wang

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Choudhary, A., Chaudhury, S., Banerjee, S. (2007). Unusual Activity Analysis in Video Sequences. In: An, A., Stefanowski, J., Ramanna, S., Butz, C.J., Pedrycz, W., Wang, G. (eds) Rough Sets, Fuzzy Sets, Data Mining and Granular Computing. RSFDGrC 2007. Lecture Notes in Computer Science(), vol 4482. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72530-5_53

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-72530-5_53

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72529-9

  • Online ISBN: 978-3-540-72530-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation