Incremental Learning in the Energy Minimisation Framework for Interactive Segmentation

  • Denis Kirmizigül
  • Dmitrij Schlesinger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6376)


In this article we propose a method for parameter learning within the energy minimisation framework for segmentation. We do this in an incremental way where user input is required for resolving segmentation ambiguities. Whereas most other interactive learning approaches focus on learning appearance characteristics only, our approach is able to cope with learning prior terms; in particular the Potts terms in binary image segmentation. The artificial as well as real examples illustrate the applicability of the approach.


Ground Truth Incremental Learn Interactive Learning Parameter Learning Binary Segmentation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Denis Kirmizigül
    • 1
  • Dmitrij Schlesinger
    • 1
  1. 1.Dresden University of Technology 

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