Probabilistic models have been adopted for many computer vision applications, however inference in highdimensional spaces remains problematic. As the statespace of a model grows, ...
— In this paper, a modified version of the complex directional pyramid (PDTDFB) is proposed. Unlike the previous approach, the new FB provides an approximately tight-frame decom...
The problem of selecting the best system from a finite set of alternatives is considered from a Bayesian decision-theoretic perspective. The framework presented is quite general,...
—This paper addresses the issue of matching rigid and articulated shapes through probabilistic point registration. The problem is recast into a missing data framework where unkno...
Radu Horaud, Florence Forbes, Manuel Yguel, Guilla...
A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribu...