Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
We address the problem of unsupervised learning of complex articulated object models from 3D range data. We describe an algorithm whose input is a set of meshes corresponding to d...
This paper describes a novel approach for obtaining semantic interoperability among data sources in a bottom-up, semiautomatic manner without relying on pre-existing, global seman...
Karl Aberer, Manfred Hauswirth, Philippe Cudr&eacu...
Abstract. Automatic delineation of anatomical structures in 3-D volumetric data is a challenging task due to the complexity of the object appearance as well as the quantity of info...
Wei Hong, Bogdan Georgescu, Xiang Sean Zhou, Srira...
Abstract. Multi-sampled imaging is a general framework for using pixels on an image detector to simultaneously sample multiple dimensions of imaging (space, time, spectrum, brightn...