Abstract:
Spectral segmentation has been shown to produce perceptually meaningful groupings. The underlying similarity matrices are usually very large. Several approximations - det...View moreMetadata
Abstract:
Spectral segmentation has been shown to produce perceptually meaningful groupings. The underlying similarity matrices are usually very large. Several approximations - deterministic and stochastic - are used in practice. The approximations usually use only local information. It has been shown recently that a few random long-range interactions facilitate emergence of structure in several domains like Ising models. We explore the use of longrange interactions in spectral segmentation.
Published in: Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.
Date of Conference: 26-26 August 2004
Date Added to IEEE Xplore: 20 September 2004
Print ISBN:0-7695-2128-2
Print ISSN: 1051-4651