We address the problem of segmenting 3D scan data into objects or object classes. Our segmentation framework is based on a subclass of Markov Random Fields (MRFs) which support ef...
Dragomir Anguelov, Benjamin Taskar, Vassil Chatalb...
We present a novel approach for fast object class recognition incorporating contextual information into boosting. The object is represented as a constellation of generalized corre...
We develop an object classification method that can learn a novel class from a single training example. In this method, experience with already learned classes is used to facilita...
To compare spatial patterns of gene expression, one must analyze a large number of images as current methods are only able to measure a small number of genes at a time. Bringing i...
Parvez Ahammad, Cyrus L. Harmon, Ann Hammonds, Sha...
Vessel enhancement in volumetric data is a necessary prerequisite in various medical imaging applications with particular importance for automated nodule detection. Ideally, vesse...
We consider the problem of clustering in domains where the affinity relations are not dyadic (pairwise), but rather triadic, tetradic or higher. The problem is an instance of the ...
The goal of motion segmentation and layer extraction can be viewed as the detection and localization of occluding surfaces. A feature that has been shown to be a particularly stro...