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SCIA
2009
Springer
195views Image Analysis» more  SCIA 2009»
13 years 10 months ago
Multi-band Gradient Component Pattern (MGCP): A New Statistical Feature for Face Recognition
A feature extraction method using multi-frequency bands is proposed for face recognition, named as the Multi-band Gradient Component Pattern (MGCP). The MGCP captures discriminativ...
Yimo Guo, Jie Chen, Guoying Zhao, Matti Pietik&aum...
BMVC
2000
13 years 7 months ago
Recognising the Dynamics of Faces across Multiple Views
We present an integrated framework for dynamic face detection and recognition, where head pose is estimated using Support Vector Regression, face detection is performed by Support...
Yongmin Li, Shaogang Gong, Heather M. Liddell
AUSAI
2005
Springer
13 years 11 months ago
New Feature Extraction Approaches for Face Recognition
All the traditional PCA-based and LDA-based methods are based on the analysis of vectors. So, it is difficult to evaluate the covariance matrices in such a high-dimensional vector ...
Vo Dinh Minh Nhat, Sungyoung Lee
ICCV
2007
IEEE
14 years 8 months ago
Spectral Regression for Efficient Regularized Subspace Learning
Subspace learning based face recognition methods have attracted considerable interests in recent years, including Principal Component Analysis (PCA), Linear Discriminant Analysis ...
Deng Cai, Xiaofei He, Jiawei Han
PR
2008
161views more  PR 2008»
13 years 6 months ago
A study on three linear discriminant analysis based methods in small sample size problem
In this paper, we make a study on three Linear Discriminant Analysis (LDA) based methods: Regularized Discriminant Analysis (RDA), Discriminant Common Vectors (DCV) and Maximal Ma...
Jun Liu, Songcan Chen, Xiaoyang Tan