75 search results - page 9 / 15 » Learning Probabilistic Models for Contour Completion in Natu... |
CVPR
2011
IEEE
13 years 3 months ago
2011
IEEE
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
ECCV
2006
Springer
14 years 8 months ago
2006
Springer
Abstract. This contribution proposes a compositional approach to visual object categorization of scenes. Compositions are learned from the Caltech 101 database1 intermediate abstra...
CVPR
2003
IEEE
14 years 8 months ago
2003
IEEE
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
CVPR
2012
IEEE
11 years 9 months ago
2012
IEEE
The automatic extraction and labeling of the rib centerlines is a useful yet challenging task in many clinical applications. In this paper, we propose a new approach integrating r...
ECCV
2002
Springer
14 years 8 months ago
2002
Springer
Abstract. This paper addresses the problem of probabilistically modeling 3D human motion for synthesis and tracking. Given the high dimensional nature of human motion, learning an ...