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. This paper presents a new Bayesian approach to hyperspectral image segmentation that boosts the performance of the discriminative classifiers. This is achieved by combin...
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
Abstract. This paper presents an approach based on graph cuts initially used for motion segmentation that is being applied to the nonrigid registration problem. The main contributi...
In this paper we propose a novel framework for efficiently extracting foreground objects in so called shortbaseline image sequences. We apply the obtained segmentation to improve...