Skip to main content
SpringerLink
Log in
SpringerLink
Log in

A Real-Time MRF Based Approach for Binary Segmentation

  • Conference paper
Pattern Recognition (DAGM/OAGM 2012)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7476))

Abstract

We present an MRF based approach for binary segmentation that is able to work in real time. As we are interested in processing of live video streams, fully unsupervised learning schemes are necessary. Therefore, we use generative models. Unlike many existing methods that use Energy Minimization techniques, we employ max-marginal decision. It leads to sampling algorithms that can be implemented for the proposed model in a very efficient manner.

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

Access this chapter

Log in via an institution
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. http://www1.inf.tu-dresden.de/~ds24/rtsegm/rtsegm.html

  2. Bleyer, M., Rother, C., Kohli, P., Scharstein, D., Sinha, S.: Object stereo – joint stereo matching and object segmentation. In: CVPR, pp. 3081–3088 (2011)

    Google Scholar 

  3. Boykov, Y., Jolly, M.P.: Interactive graph cuts for optimal boundary & region segmentation of objects in n-d images. In: ICCV, vol. 1, pp. 105–112 (2001)

    Google Scholar 

  4. Delong, A., Gorelick, L., Schmidt, F., Veksler, O., Boykov, Y.: Interactive Segmentation with Super-Labels. In: Boykov, Y., Kahl, F., Lempitsky, V., Schmidt, F.R. (eds.) EMMCVPR 2011. LNCS, vol. 6819, pp. 147–162. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  5. Flach, B., Schlesinger, D.: Combining Shape Priors and MRF-Segmentation. In: da Vitoria Lobo, N., Kasparis, T., Roli, F., Kwok, J.T., Georgiopoulos, M., Anagnostopoulos, G.C., Loog, M. (eds.) S+SSPR 2008. LNCS, vol. 5342, pp. 177–186. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  6. Gulshan, V., Rother, C., Criminisi, A., Blake, A., Zisserman, A.: Geodesic star convexity for interactive image segmentation. In: CVPR (2010)

    Google Scholar 

  7. Nowozin, S., Lampert, C.: Structured Learning and Prediction in Computer Vision. Foundations and Trends in Computer Graphics and Vision 6 (2010)

    Google Scholar 

  8. Rother, C., Kolmogorov, V., Blake, A.: “GrabCut”: interactive foreground extraction using iterated graph cuts. ACM Trans. Graph. 23(3), 309–314 (2004)

    Article  Google Scholar 

  9. Schlesinger, D.: Gibbs Probability Distributions for Stereo Reconstruction. In: Michaelis, B., Krell, G. (eds.) DAGM 2003. LNCS, vol. 2781, pp. 394–401. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  10. Schlesinger, D., Flach, B.: A Probabilistic Segmentation Scheme. In: Rigoll, G. (ed.) DAGM 2008. LNCS, vol. 5096, pp. 183–192. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  11. Schmidt, U., Gao, Q., Roth, S.: A generative perspective on MRFs in low-level vision. In: CVPR (June 2010)

    Google Scholar 

  12. Schmidt, U., Schelten, K., Roth, S.: Bayesian deblurring with integrated noise estimation. In: CVPR (June 2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dresden University of Technology, Germany

    Dmitrij Schlesinger

Authors
  1. Dmitrij Schlesinger
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Electrical Measurement and Measurement Signal Processing, Graz University of Technology, Kronesgasse 5, 8010, Graz, Austria

    Axel Pinz

  2. Institute for Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16, 8010, Graz, Austria

    Thomas Pock , Horst Bischof  & Franz Leberl ,  & 

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Schlesinger, D. (2012). A Real-Time MRF Based Approach for Binary Segmentation. In: Pinz, A., Pock, T., Bischof, H., Leberl, F. (eds) Pattern Recognition. DAGM/OAGM 2012. Lecture Notes in Computer Science, vol 7476. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32717-9_39

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-32717-9_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32716-2

  • Online ISBN: 978-3-642-32717-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation