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» Graph-Theoretical Methods in Computer Vision
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CVPR
2005
IEEE
16 years 9 months ago
A Semi-Supervised Active Learning Framework for Image Retrieval
Although recent studies have shown that unlabeled data are beneficial to boosting the image retrieval performance, very few approaches for image retrieval can learn with labeled a...
Steven C. H. Hoi, Michael R. Lyu
CVPR
2005
IEEE
16 years 9 months ago
Tracking Multiple Objects through Occlusions
We present an approach for tracking varying number of objects through both temporally and spatially significant occlusions. Our method builds on the idea of object permanence to r...
Yan Huang, Irfan A. Essa
CVPR
2005
IEEE
16 years 9 months ago
Full Body Tracking from Multiple Views Using Stochastic Sampling
We present a novel approach for full body pose tracking using stochastic sampling. A volumetric reconstruction of a person is extracted from silhouettes in multiple video images. ...
Roland Kehl, Matthieu Bray, Luc J. Van Gool
CVPR
2005
IEEE
16 years 9 months ago
A Bayesian Hierarchical Model for Learning Natural Scene Categories
We propose a novel approach to learn and recognize natural scene categories. Unlike previous work [9, 17], it does not require experts to annotate the training set. We represent t...
Fei-Fei Li 0002, Pietro Perona, California Institu...
CVPR
2005
IEEE
16 years 9 months ago
Using Particles to Track Varying Numbers of Interacting People
In this paper, we present a Bayesian framework for the fully automatic tracking of a variable number of interacting targets using a fixed camera. This framework uses a joint multi...
Kevin Smith, Daniel Gatica-Perez, Jean-Marc Odobez