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» Face recognition using mixtures of principal components
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CORR
2010
Springer
221views Education» more  CORR 2010»
14 years 7 months ago
Reduction of Feature Vectors Using Rough Set Theory for Human Face Recognition
In this paper we describe a procedure to reduce the size of the input feature vector. A complex pattern recognition problem like face recognition involves huge dimension of input ...
Debotosh Bhattacharjee, Dipak Kumar Basu, Mita Nas...
CVPR
1999
IEEE
15 years 11 months ago
Face Recognition Using Shape and Texture
We introduce in this paper a new face coding and recognition method which employs the Enhanced FLD (Fisher Linear Discrimimant) Model (EFM)on integrated shape (vector) and texture...
Chengjun Liu, Harry Wechsler
82
Voted
ICPR
2008
IEEE
15 years 4 months ago
Face recognition using curvelet based PCA
This paper identifies a novel feature space to address the problem of human face recognition from still images. This is based on the PCA space of the features extracted by a new m...
Tanaya Mandal, Q. M. Jonathan Wu
104
Voted
JACM
2011
152views more  JACM 2011»
14 years 16 days ago
Robust principal component analysis?
This paper is about a curious phenomenon. Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Can we recover each component i...
Emmanuel J. Candès, Xiaodong Li, Yi Ma, Joh...
77
Voted
ICIAR
2004
Springer
15 years 3 months ago
Three-Dimensional Face Recognition: A Fishersurface Approach
Previous work has shown that principal component analysis (PCA) of three-dimensional face models can be used to perform recognition to a high degree of accuracy. However, experimen...
Thomas Heseltine, Nick Pears, Jim Austin