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MLDM
2005
Springer
14 years 2 months ago
Unsupervised Learning of Visual Feature Hierarchies
We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...
Fabien Scalzo, Justus H. Piater
ICIP
2004
IEEE
14 years 10 months ago
Statistical transformations of frontal models for non-frontal face verification
In the framework of a face verification system using local features and a Gaussian Mixture Model based classifier, we address the problem of non-frontal face verification (when on...
Conrad Sanderson, Samy Bengio
CVPR
2005
IEEE
14 years 11 months ago
Subspace Analysis Using Random Mixture Models
In [1], three popular subspace face recognition methods, PCA, Bayes, and LDA were analyzed under the same framework and an unified subspace analysis was proposed. However, since t...
Xiaogang Wang, Xiaoou Tang
FGR
2011
IEEE
354views Biometrics» more  FGR 2011»
13 years 10 days ago
Hierarchical ranking of facial attributes
Abstract— We propose a novel hierarchical structured prediction approach for ranking images of faces based on attributes. We view ranking as a bipartite graph matching problem; l...
Ankur Datta, Rogerio Feris, Daniel A. Vaquero
ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
13 years 6 months ago
Learning Markov Network Structure with Decision Trees
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Daniel Lowd, Jesse Davis