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» A New Discriminative Kernel From Probabilistic Models
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ECCV
2004
Springer
15 years 11 months ago
Dimensionality Reduction by Canonical Contextual Correlation Projections
A linear, discriminative, supervised technique for reducing feature vectors extracted from image data to a lower-dimensional representation is proposed. It is derived from classica...
Marco Loog, Bram van Ginneken, Robert P. W. Duin
ICML
1997
IEEE
15 years 10 months ago
Learning Belief Networks in the Presence of Missing Values and Hidden Variables
In recent years there has been a flurry of works on learning probabilistic belief networks. Current state of the art methods have been shown to be successful for two learning scen...
Nir Friedman
PAMI
2002
112views more  PAMI 2002»
14 years 9 months ago
Feature Space Trajectory Methods for Active Computer Vision
We advance new active object recognition algorithms that classify rigid objects and estimate their pose from intensity images. Our algorithms automatically detect if the class or p...
Michael A. Sipe, David Casasent
ICPR
2006
IEEE
15 years 11 months ago
Simultaneous Inference of View and Body Pose using Torus Manifolds
Inferring 3D body pose as well as viewpoint from a single silhouette image is a challenging problem. We present a new generative model to represent shape deformations according to...
Ahmed M. Elgammal, Chan-Su Lee
ECSQARU
2009
Springer
15 years 1 months ago
Different Representations of Fuzzy Vectors
Fuzzy vectors were introduced as a description of imprecise quantities whose uncertainty originates from vagueness, not from a probabilistic model. Support functions are a classica...
Jiuzhen Liang, Mirko Navara, Thomas Vetterlein