[1]JIN Yi,RUAN Qiu-qi.A partially weighted twodimensional PCA for face recognition[J].CAAI Transactions on Intelligent Systems,2007,2(3):25-29.
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A partially weighted twodimensional PCA for face recognition

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 2 Number of periods: 2007 3 Page number: 25-29 Column: 学术论文—机器感知与模式识别 Public date: 2007-06-25
Title:
A partially weighted twodimensional PCA for face recognition
Author(s):
JIN Yi;  RUAN Qiu-qi
College of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
Keywords:
twodimensional principal component analysis;  partiallyweighted;  face recognition;  weighted feature extraction
CLC:
TP391.4
DOI:
-
Abstract:
This paper proposes face recognition software that uses twodimensional principal component analysis (2DPCA) in conjunction with partial feature weighting by applying twodimensional partialweighting to the characteristic subspace. First faces are mapped onto this partially weighted 2DPCA subspace, then the samples are classified by calculating the distance from the samples to the partially weighted 2DPCA subspace. To test this new method, ORL face databases were used and it was found that the recognition rate was higher than with either 2DPCA or PCA and the computational complexity did not increase significantly.
References:
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