—We present a novel framework to generate and rank plausible hypotheses for the spatial extent of objects in images using bottom-up computational processes and mid-level selectio...
This paper proposes an approach to image segmentation using Iterated Graph Cuts based on local texture features of wavelet coefficient. Using Multiresolution Analysis based on Ha...
We present a generic framework for object segmentation using depth maps based on Random Forest and Graph-cuts theory, and apply it to the segmentation of human limbs in depth maps...
This paper addresses the problem of foreground extraction using active illumination and graph-cut optimization. Our approach starts by detecting image regions that are likely to b...
—This paper addresses the problem of self-validated labeling of Markov random fields (MRFs), namely to optimize an MRF with unknown number of labels. We present graduated graph c...