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 ...
Abstract. We propose to tackle the optical flow problem by a combination of two recent advances in the computation of dense correspondences, namely the incorporation of image segme...
Michael Bleyer, Christoph Rhemann, Margrit Gelautz
A novel interactive segmentation framework comprising of a two stage s-t mincut is proposed. The framework has been designed keeping in mind the need to segment touching neuronal ...
We present a new image segmentation algorithm based on graph cuts. Our main tool is separation of each pixel from a special point outside the image by a cut of a minimum cost. Suc...