Abstract. We propose a novel method for unsupervised class segmentation on a set of images. It alternates between segmenting object instances and learning a class model. The method...
Abstract. Graph-based algorithms have become increasingly popular for medical image segmentation. The fundamental process for each of these algorithms is to use the image content t...
: Planar patch detection aims at simplifying data from 3-D imaging sensors to a more compact scene description. We propose a fusion of intensity and depth information using Graph-C...
We present a stochastic clustering algorithm which uses pairwise similarity of elements, based on a new graph theoretical algorithm for the sampling of cuts in graphs. The stochas...
Fundamental to any graph cut segmentation methods is the assignment of edge weights. The existing solutions typically use gaussian, exponential or rectangular cost functions with ...