This paper proposes two modifications to the geometrically deformable template model. First, the optimization stage originally based on simulated annealing is replaced with a meta...
We recall the basic idea of an algebraic approach to learning Bayesian network (BN) structures, namely to represent every BN structure by a certain (uniquely determined) vector, c...
This paper presents a method for learning 3D object templates from view labeled object images. The 3D template is defined in a joint appearance and geometry space, and is compose...
The shape of a population of geometric entities is characterized by both the common geometry of the population and the variability among instances. In the deformable model approach...
Conglin Lu, Stephen M. Pizer, Sarang C. Joshi, Ja-...
The purpose of this paper is to measure the variability of a population of white matter fiber bundles without imposing unrealistic geometrical priors. In this respect, modeling fib...
Stanley Durrleman, Pierre Fillard, Xavier Pennec, ...