Shape Priors for Image Segmentation

Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)


The goal of image segmentation is to partition the image plane into a set of meaningful regions. While generic low-level segmentation algorithms often impose a prior which favors shorter boundaries, for segmenting familiar structures in images it may be advantageous to impose a more object-specific shape prior. Over the years, researchers have proposed different algorithms to impose prior shape knowledge based on either explicit or implicit representations of shape. In the following, I will provide a brief review of several approaches.


Image Segmentation Segmentation Process Implicit Representation Statistical Shape Shape Representation 
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.



The work described here was done in collaboration with numerous researchers. The author would like to thank T. Schoenemann, F.R. Schmidt, C. Schnoerr, S. Soatto, N. Sochen, T. Kohlberger, M. Rousson and S.J. Osher for their support.


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Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  1. 1.Departments of Computer Science & MathematicsTU MunichGarchingGermany

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