This paper presents a probabilistic information retrieval framework in which the retrieval problem is formally treated as a statistical decision problem. In this framework, querie...
We consider the problem of predicting a sequence of real-valued multivariate states from a given measurement sequence. Its typical application in computer vision is the task of mo...
In this work we present Discriminative Random Fields (DRFs), a discriminative framework for the classification of image regions by incorporating neighborhood interactions in the l...
Map matching is a fundamental operation in many applications such as traffic analysis and location-aware services, the killer apps for ubiquitous computing. In the past, several m...
—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...