A novel multiregion graph cut image partitioning method combined with kernel mapping is presented. A kernel function transforms implicitly the image data into data of a higher dim...
Abstract. Graph cuts have become very popular in many areas of computer vision including segmentation, energy minimization, and 3D reconstruction. Their ability to find optimal res...
We propose a novel Markovian segmentation
model which takes into account edge information. By construction,
the model uses only pairwise interactions and its
energy is submodula...
Milán Leskó, Zoltan Kato, Antal Nagy, Imre Gombo...
There is a growing need to extract features from point sets for purposes like model classification, matching, and exploration. We introduce a technique for segmenting a point-sam...
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...
Graph cut image segmentation with intensity information alone is prone to fail for objects with weak edges, in clutter, or under occlusion. Existing methods to incorporate shape a...
This paper presents the design and implementation of a multi-resolution graph cuts (MRGC) for stereo-motion framework that produces dense disparity maps. Both stereo and motion ar...
This paper presents a novel graph cut based segmentation approach with shape priors. The model incorporates statistical shape prior information with the active contour without edg...
Graph cut algorithms (i.e., min s-t cuts) [3][10][15] are useful in many computer vision applications. In this paper we develop a formulation that allows the addition of side cons...
In this paper, we propose a novel method for the automatic segmentation of a foreground layer from a natural scene in real time by fusing infrared, color and edge information. Thi...