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» Using Component Features for Face Recognition
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ECCV
2010
Springer
15 years 12 days ago
Coupled Gaussian Process Regression for Pose-Invariant Facial Expression Recognition
We present a novel framework for the recognition of facial expressions at arbitrary poses that is based on 2D geometric features. We address the problem by first mapping the 2D loc...
Ognjen Rudovic, Ioannis Patras, Maja Pantic
175
Voted
ICASSP
2011
IEEE
14 years 6 months ago
Automatic target classification in SAR images using MPCA
Multilinear analysis provides a powerful mathematical framework for analyzing synthetic aperture radar (SAR) images resulting from the interaction of multiple factors like sky lum...
Tristan Porges, Gérard Favier
CIARP
2007
Springer
15 years 8 months ago
Multi-class Binary Object Categorization Using Blurred Shape Models
The main difficulty in the binary object classification field lays in dealing with a high variability of symbol appearance. Rotation, partial occlusions, elastic deformations, or...
Sergio Escalera, Alicia Fornés, Oriol Pujol...
115
Voted
ICIP
2008
IEEE
15 years 8 months ago
Correlation Embedding Analysis
—Beyond conventional linear and kernel-based feature extraction, we present a more generalized formulation for feature extraction in this paper. Two representative algorithms usi...
Yun Fu, Thomas S. Huang
CVPR
2011
IEEE
14 years 10 months ago
Identifying Players in Broadcast Sports Videos using Conditional Random Fields
We are interested in the problem of automatic tracking and identification of players in broadcast sport videos shot with a moving camera from a medium distance. While there are m...
Wei-Lwun Lu, Jo-Anne Ting, Kevin Murphy, Jim Littl...