Skip to main content

Human Silhouette Extraction Method Using Region Based Background Subtraction

  • Conference paper
Computer Vision/Computer Graphics Collaboration Techniques (MIRAGE 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4418))

Abstract

Background subtraction methods have been used to obtain human silhouettes for gesture and gait recognition. However, background subtraction in pixel units is prone to error which decreases recognition performance significantly. In this paper we propose a novel background subtraction method that extracts foreground objects in region units. Together with the background model, an object’s color and movement information are used to obtain the effective region object likelihood. Then an adaptive region decision function determines the object regions. Also, the sequential version of Horprasert’s algorithm[2] is presented.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Comaniciu, D., Meer, P.: Mean shift: a robust approach toward feature space analysis. IEEE Trans. Pattern Anal. Mach. Intell. 24(5), 603–619 (2002)

    Article  Google Scholar 

  2. Horprasert, T., Harwood, D., Davis, L.S.: A statistical approach for real-time robust background subtraction and shadow detection. In: Proc. IEEE Frame Rate Workshop, pp. 1–19. IEEE Computer Society Press, Los Alamitos (1999)

    Google Scholar 

  3. Harville, M.: A framework for high-level feedback to adaptive, per-pixel, mixture-of-Gaussian background models. In: Heyden, A., et al. (eds.) ECCV 2002. LNCS, vol. 2352, pp. 543–560. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  4. Li, H., Greenspan, M.: Multi-scale gesture recognition from time-varying contours. In: IEEE Int. Conf. Computer Vision, pp. 236–243. IEEE Computer Society Press, Los Alamitos (2005)

    Google Scholar 

  5. Liu, Z., Sarkar, S.: Effect of silhouette quality on hard problems in gait recognition. IEEE Trans. Systems, Man, and Cybernetics-Part B 35(2), 170–183 (2005)

    Article  Google Scholar 

  6. Senior, A.: Tracking people with probabilistic appearance models. In: Proc. IEEE Int. Workshop on PETS, pp. 48–55. IEEE Computer Society Press, Los Alamitos (2002)

    Google Scholar 

  7. Stauffer, C., Grimson, W.E.L.: Learning patterns of activity using real-time tracking. IEEE Trans. Pattern Anal. Mach. Intell. 22, 747–757 (2000)

    Article  Google Scholar 

  8. Tian, Y.-L., Lu, M., Hampapur, A.: Robust and efficient foreground analysis for real-time video surveillance. In: Proc. IEEE Int. Conf. Computer Vision and Pattern Recognition, pp. 970–975. IEEE Computer Society Press, Los Alamitos (2005)

    Google Scholar 

  9. Tu, Z.: An integrated framework for image segmentation and perceptual grouping. In: IEEE Int. Conf. Computer Vision, pp. 670–677. IEEE Computer Society Press, Los Alamitos (2005)

    Google Scholar 

  10. Wang, L., et al.: Silhouette analysis-based gait recognition for human identification. IEEE Trans. Pattern Anal. Mach. Intell. 25, 1505–1518 (2003)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

André Gagalowicz Wilfried Philips

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer Berlin Heidelberg

About this paper

Cite this paper

Ahn, JH., Byun, H. (2007). Human Silhouette Extraction Method Using Region Based Background Subtraction. In: Gagalowicz, A., Philips, W. (eds) Computer Vision/Computer Graphics Collaboration Techniques. MIRAGE 2007. Lecture Notes in Computer Science, vol 4418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71457-6_37

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-71457-6_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71456-9

  • Online ISBN: 978-3-540-71457-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics