Skip to main content

Using Mutual Information for Multi-Anchor Tracking of Human Beings

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8897))

Abstract

Tracking of human beings represents a hot research topic in the field of video analysis. It is attracting an increasing attention among researchers thanks to its possible application in many challenging tasks. Among these, action recognition, human/human and human/computer interaction require body-part tracking. Most of the existing techniques in literature are model-based approaches, so despite their effectiveness, they are often unfit for the specific requirements of a body-part tracker. In this case it is very hard if not impossible to define a formal model of the target. This paper proposes a multi-anchor tracking system, which works on 8 bits color images and exploits the mutual information to track human body parts (head, hands, …) without performing any foreground/background segmentation. The proposed method has been designed as a component of a more general system aimed at human interaction analysis. It has been tested on a wide set of color video sequences and the very promising results show its high potential.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bregler, C., Malik, J.: Tracking people with twists and exponential maps. In: IEEE Computer Vision and Pattern Recognition, pp. 8–15 (1998)

    Google Scholar 

  2. Cernekova, Z., Pitas, I., Nikou, C.: Information theory-based shot cut/fade detection and video summarization. IEEE Transactions on Circuits and Systems for Video Technology 16(1), 82–91 (2006)

    Article  Google Scholar 

  3. Dame, A., Marchand, E.: Accurate real-time tracking using mutual information. In: 9th IEEE International Symposium on Mixed and Augmented Reality, pp. 47–56 (2010)

    Google Scholar 

  4. Haritaoglu, I., Harwood, D., Davis, L.S.: W4: real-time surveillance of people and their activities. IEEE Trans. on Pattern Analysis and Machine Intelligence 22(8), pp. 809–830 (2000)

    Google Scholar 

  5. Hogg, D.: Model based vision: A program to see a walking person. Image and Vision Computing 1(1), 5–20 (1983)

    Article  Google Scholar 

  6. Johansson, G.: Visual motion perception. Science American 232(6), 76–88 (1975)

    Article  Google Scholar 

  7. Loutas, E., Pitas, I., Nikou, C.: Probabilistic multiple face detection and tracking using entropy measures. IEEE Transactions on Circuits and Systems for Video Technology 14(1), 128–135 (2004)

    Article  Google Scholar 

  8. Okada, R., Shirai, Y., Miura, J.: Tracking a person with 3D motion by integrating optical flow and depth. In: 4th IEEE International Conference on Automatic Face and Gesture Recognition, France, pp. 336–341 (2000)

    Google Scholar 

  9. Qian, R.J., Huang, T.S.: Estimating articulated motion by decomposition, Time-Varying Image Processing and Moving Object Recognition, 3-V. Cappellini (Ed.), pp. 275–286 (1994)

    Google Scholar 

  10. Sato, K., Aggarwal, J.K.: Tracking and recognizing two-person interactions in outdoor image sequences. In: IEEE Workshop on Multi-Object Tracking, Canada, pp. 87–94. (2001)

    Google Scholar 

  11. Shannon, C.: A mathematical theory of communication. Bell System Technical Journal 27(3), 379–423 (1948)

    Article  MATH  MathSciNet  Google Scholar 

  12. Sidenbladh, H., Black, M.J., Fleet, D.J.: Stochastic Tracking of 3D Human Figures Using 2D Image Motion. In: Vernon, D. (ed.) ECCV 2000. LNCS, vol. 1843, pp. 702–718. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  13. Wren, C., Azarbayejani, A., Darrell, T., Pentland, A.: Pfinder: real-time tracking of the human body. IEEE Trans. on Pattern Analysis and Machine Intelligence 19(7), 780–785 (1997)

    Google Scholar 

  14. http://biplab.unisa.it/InterActions.zip

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Maria De Marsico .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Barra, S., De Marsico, M., Cantoni, V., Riccio, D. (2014). Using Mutual Information for Multi-Anchor Tracking of Human Beings. In: Cantoni, V., Dimov, D., Tistarelli, M. (eds) Biometric Authentication. BIOMET 2014. Lecture Notes in Computer Science(), vol 8897. Springer, Cham. https://doi.org/10.1007/978-3-319-13386-7_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-13386-7_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13385-0

  • Online ISBN: 978-3-319-13386-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics