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115
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IJAR
2010
152views more  IJAR 2010»
14 years 11 months ago
Structural-EM for learning PDG models from incomplete data
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
Jens D. Nielsen, Rafael Rumí, Antonio Salme...
109
Voted
NIPS
2000
15 years 2 months ago
Feature Correspondence: A Markov Chain Monte Carlo Approach
When trying to recover 3D structure from a set of images, the most di cult problem is establishing the correspondence between the measurements. Most existing approaches assume tha...
Frank Dellaert, Steven M. Seitz, Sebastian Thrun, ...
108
Voted
CVPR
2008
IEEE
16 years 2 months ago
What can missing correspondences tell us about 3D structure and motion?
Practically all existing approaches to structure and motion computation use only positive image correspondences to verify the camera pose hypotheses. Incorrect epipolar geometries...
Christopher Zach, Arnold Irschara, Horst Bischof
113
Voted
ICIP
1999
IEEE
16 years 2 months ago
A Fast Algorithm for Rigid Structure from Image Sequences
The factorization method [1] is a feature-based approach to recover 3D rigid structure from motion. In [2], we extended their framework to recover a parametric description of the ...
Pedro M. Q. Aguiar, José M. F. Moura
ICDM
2003
IEEE
104views Data Mining» more  ICDM 2003»
15 years 6 months ago
Structure Search and Stability Enhancement of Bayesian Networks
Learning Bayesian network structure from large-scale data sets, without any expertspecified ordering of variables, remains a difficult problem. We propose systematic improvements ...
Hanchuan Peng, Chris H. Q. Ding