Spatial Feature Based Recognition of Human Dynamics in Video Sequences | SpringerLink
Skip to main content
Springer Nature Link
Log in

Spatial Feature Based Recognition of Human Dynamics in Video Sequences

  • Conference paper
Pattern Recognition and Image Analysis (ICAPR 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3687))

Included in the following conference series:

  • 1926 Accesses

Abstract

The reliable identification of human activities in video, for example whether a person is walking, clapping, waving, etc. is extremely important for video interpretations. Since different people could perform the same action across different number of frames, matching two different sequences of the same actions is not a trivial task. In this paper we discuss a new technique for video sequence matching where the matched sequences are of different sizes. The proposed technique is based on frequency domain analysis of feature data. The experiments are shown to achieve high recognition accuracy of 95.4% on recognizing 8 different human actions, and out-perform two baseline methods of comparison.

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. Agrawal, R., Faloutsos, C., Swami, A.: Efficiet Similarity Search In Sequence Databases. In: Proceedings of the 4th International Conference of Foundations of Data Organization and Algorithms (FODO), Chicago, October 1993, pp. 69–84 (1993)

    Google Scholar 

  2. Beckmann, N., Kriegel, H.-P., Schneider, R., Seeger, B.: The R* -tree: An Efficient and Robust Access Method for Points and Rectangles. In: Proc. Int’l Conf. On Management of Data, ACM SIGMOD, Atlantic City, New Jersey, May 1990, pp. 322–331 (1990)

    Google Scholar 

  3. Ben-Arie, J., Wang, Z., Pandit, P., Rajaram, S.: Human Activity Recognition Using Multidimensional Indexing. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(8), 1091–1104 (2002)

    Article  Google Scholar 

  4. Chan, K.-P., Fu, A.W.-C.: Efficient Time Series Matching by Wavelets. In: 15th IEEE International Conference on Data Engineering, Sydney, Australia, March 1999, pp. 126–133 (1999)

    Google Scholar 

  5. Duda, R., Hart, P.E., Stork, D.: Pattern Classification, 2nd edn. John Wiley and Sons, New York (2001)

    MATH  Google Scholar 

  6. Faloutsos, C., Ranganathan, M., Manolopoulos, Y.: Fast subsequence matching in Time-series Databases. In: Proceedings 1994 ACM SIGMOD Conference, Minneapolis, MN, pp. 419–429 (1994)

    Google Scholar 

  7. Horprasert, T., Harwood, D., Davis, L.S.: A statistical App. roach for Real-time Robust Background Subtraction and Shadow Detection. In: Proceeding of IEEE ICCV 1999, pp. 1–19 (1999)

    Google Scholar 

  8. Kim, S.H., Park, R.-H.: An Efficient Algorithm For Video Sequence Matching Using The Modified Hausdorff Distance and the Directed Divergence. IEEE Transactions on Circuits and Systems for Video Technology 12(7), 592–296 (2002)

    Google Scholar 

  9. Moon, Y.-S., Whang, K.-Y., Loh, W.-K.: Efficient Time-Series Subsequence Matching using Duality in Constructing Windows. Information Systems 26(4), 279–293 (2001)

    Article  MATH  Google Scholar 

  10. Moon, Y.-S., Whang, K.-Y., Loh, W.-K.: Dual Match: Duality-Based Subsequence Matching in Time-series Databases. In: Proceedings of the 17th International Conference on Data Engineering, pp. 263–272 (April 2001)

    Google Scholar 

  11. Rafiei, D., Mendelzon, A.: Similarity-based Queries for Time series Data. In: Proc. Int’l Conf. On Management of Data, ACM SIGMOD, Tucson, Arizona, pp. 13–25 (May 1997)

    Google Scholar 

  12. Rafiei, D.: On similarity-based queries for time series data. In: Proc. The 15th Int’l Conf. On Data Engineering, Sydney, Australia, pp. 410–417 (February 1999)

    Google Scholar 

  13. Rangarajan, K., Allen, B., Shah, M.: Matching Motion Trajectories. Pattern Recognition 26(4), 595–610 (1993)

    Article  Google Scholar 

  14. Savnik, I., Lausen, G., Kahle, H.-P., Spiecker, H., Hein, S.: Algorithm for Matching Sets of Time Series. In: Principles of Data Mining and Knowledge Discovery, Lyon, France, pp. 277–288 (September 2000)

    Google Scholar 

  15. Sonka, M., Hlavac, V., Boyle, R.: Image Processing, Analysis and Machine Vision, ch. 6. Brooks/Cole Publishing (1999)

    Google Scholar 

  16. Tolba, A.: Arabic Glove Talk: A Communication Aid for Vocally Impaired. Pattern Analysis and Applications 1(4), 218–230 (1998)

    Article  Google Scholar 

  17. Tsai, P.-S., Shah, M., Keiter, K., Kasparis, T.: Cyclic Motion Detection. Department of Computer Science Technical Report, University of Central Florida, Orlando (1993)

    Google Scholar 

  18. Wang, J., Singh, S.: Video Based Human Dynamics: A Review. Real Time Imaging 9(5), 321–346 (2003)

    Article  Google Scholar 

  19. Wang, J., Singh, S.: Video Based Human Behavior Identification using Frequency Domain Analysis. In: Yang, Z.R., Yin, H., Everson, R.M. (eds.) IDEAL 2004. LNCS, vol. 3177, pp. 218–224. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Research School of Informatics, Loughborough University, Loughborough, LW11 3TU, United Kingdom

    Jessica JunLin Wang & Sameer Singh

Authors
  1. Jessica JunLin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sameer Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Research School of Infomatics, Loughborough, UK

    Sameer Singh

  2. ATR Lab, Research School of Informatics, University of Loughborough, Loughborough, UK

    Maneesha Singh

  3. IBM Corporation, 1133 Wetchester Avenue, White Plains, 10604, New York, United States

    Chid Apte

  4. Institute of Computer Vision and applied Computer Sciences, IBaI, Germany

    Petra Perner

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Wang, J.J., Singh, S. (2005). Spatial Feature Based Recognition of Human Dynamics in Video Sequences. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds) Pattern Recognition and Image Analysis. ICAPR 2005. Lecture Notes in Computer Science, vol 3687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552499_10

Download citation

  • DOI: https://doi.org/10.1007/11552499_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28833-6

  • Online ISBN: 978-3-540-31999-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation