This code release contains libraries for computing pairwise affinities with
the goal of segmenting natural images. There is also code which feeds the
computed affinities to an eigensolver (TRLan) and clusters the
resulting eigenvectors using k-means to yield an image segmentation.
The algorithms used are described in:
This codebase will likely undergo some major revisions as more segmentation
functionality is added. Please email me if you would like to recieve an
announcement of the next release.
- C. Fowlkes, D. Martin, J. Malik. "Learning Affinity Functions for
Image Segmentation: Combining Patch-based and Gradient-based
Approaches", CVPR, Madison, WI, (June 2003).
- D. Martin, C. Fowlkes, J. Malik. "Learning to Detect Natural Image
Boundaries Using Local Brightness, Color and Texture Cues", TPAMI 26 (5) p.530-549 [pdf]
- C. Fowlkes, J. Malik. "How Much Does Globalization Help Segmentation?",
Technical Report CSD-04-1340, Division of Computer Science,
University of California, Berkeley, (July 2004).