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» Learning structurally discriminant features in 3D faces
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ICCV
2007
IEEE
14 years 9 months ago
Semi-supervised Discriminant Analysis
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. The projection vectors are commonly obtained by maximizing ...
Deng Cai, Xiaofei He, Jiawei Han
NIPS
2004
13 years 9 months ago
Surface Reconstruction using Learned Shape Models
We consider the problem of geometrical surface reconstruction from one or several images using learned shape models. While humans can effortlessly retrieve 3D shape information, t...
Jan Erik Solem, Fredrik Kahl
ICIP
2009
IEEE
14 years 8 months ago
Scale-robust Feature Extraction For Face Recognition
In video surveillance, the sizes of face images are very small. However, few works have been done to investigate scalerobust face recognition. Our experiments on appearancebased m...
AVBPA
2005
Springer
226views Biometrics» more  AVBPA 2005»
14 years 1 months ago
Discriminant Analysis Based on Kernelized Decision Boundary for Face Recognition
A novel nonlinear discriminant analysis method, Kernelized Decision Boundary Analysis (KDBA), is proposed in our paper, whose Decision Boundary feature vectors are the normal vecto...
Baochang Zhang, Xilin Chen, Wen Gao
ICPR
2008
IEEE
14 years 2 months ago
Semi-supervised discriminant analysis based on UDP regularization
We propose a semi-supervised learning algorithm for discriminant analysis, which uses the geometric structure of both labeled and unlabeled samples and perform a manifold regulari...
Huining Qiu, Jian-Huang Lai, Jian Huang, Yu Chen