Over the last years many statistical models have been proposed to restore tomographical images. However, their use in medical environment has been limited due to several factors. ...
We introduce a new causal hierarchical belief network for image segmentation. Contrary to classical tree structured (or pyramidal) models, the factor graph of the network contains...
We view the task of change detection as a problem of object recognition from learning. The object is defined in a 3D space where the time is the 3rd dimension. We propose two com...
Actions in real world applications typically take place in cluttered environments with large variations in the orientation and scale of the actor. We present an approach to simult...
We propose a novel MRF-based model for deformable image matching (also known as registration). The deformation is described by a field of discrete variables, representing displace...