Incremental Learning in the Energy Minimisation Framework for Interactive Segmentation

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.