title: Image Segmentation via Probabilistic Graph Matching.
abstract: This paper presents an unsupervised and semi-automatic image segmentation approach where we formulate the segmentation as an inference problem based on unary and pairwise assignment probabilities computed using low-level image cues. The inference is solved via a probabilistic graph matching scheme, which allows rigorous incorporation of low-level image cues and automatic tuning of parameters. The proposed scheme is experimentally shown to compare favorably with contemporary semi-supervised and unsupervised image segmentation schemes, when applied to contemporary state-of-the-art image sets.
authors.forename: Ayelet
authors.initials: A
authors.lastname: Heimowitz
authors.forename: Yosi
authors.initials: Y
authors.lastname: Keller