1427 search results - page 166 / 286 » Markov Random Field Models in Computer Vision |
133
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ICML
2010
IEEE
15 years 2 months ago
2010
IEEE
Learning undirected graphical models such as Markov random fields is an important machine learning task with applications in many domains. Since it is usually intractable to learn...
106
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CVPR
2005
IEEE
16 years 3 months ago
2005
IEEE
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...
ICPR
2004
IEEE
16 years 2 months ago
2004
IEEE
Domains in which shapes of objects change rapidly and significantly are a challenge for existing representation techniques: sport is a good example of this. We present a texture-b...
109
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CVPR
2007
IEEE
16 years 3 months ago
2007
IEEE
We boost the efficiency and robustness of distributionbased matching by random subsampling which results in the minimum number of samples required to achieve a specified probabili...
121
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ICVS
1999
Springer
15 years 6 months ago
1999
Springer
Many modern computer vision systems are built by chaining together standard vision procedures, often in graphical programming environments such as Khoros, CVIPtools or IUE. Typical...