Kernel Cuts: MRF meets Kernel & Spectral Clustering

24 Jun 2015Meng TangDmitrii MarinIsmail Ben AyedYuri Boykov

We propose a new segmentation model combining common regularization energies, e.g. Markov Random Field (MRF) potentials, and standard pairwise clustering criteria like Normalized Cut (NC), average association (AA), etc. These clustering and regularization models are widely used in machine learning and computer vision, but they were not combined before due to significant differences in the corresponding optimization, e.g. spectral relaxation and combinatorial max-flow techniques... (read more)

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