179 search results - page 19 / 36 » Probabilistic Scene Models for Image Interpretation |
CVPR
2003
IEEE
15 years 11 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...
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CVPR
2011
IEEE
14 years 6 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...
DAGM
2006
Springer
15 years 1 months ago
2006
Springer
Dense depth maps can be estimated in a Bayesian sense from multiple calibrated still images of a rigid scene relative to a reference view [1]. This well-established probabilistic f...
CVPR
2010
IEEE
15 years 6 months ago
2010
IEEE
Detecting objects in complex scenes while recovering the scene layout is a critical functionality in many vision-based applications. Inspired by the work of [18], we advocate the ...
EMMCVPR
2005
Springer
15 years 3 months ago
2005
Springer
We present a novel approach to the matching of subgraphs for object recognition in computer vision. Feature similarities between object model and scene graph are complemented with ...