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» The development features of the face recognition system
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FGR
2004
IEEE
200views Biometrics» more  FGR 2004»
13 years 8 months ago
Using Random Subspace to Combine Multiple Features for Face Recognition
LDA is a popular subspace based face recognition approach. However, it often suffers from the small sample size problem. When dealing with the high dimensional face data, the LDA ...
Xiaogang Wang, Xiaoou Tang
IWANN
2005
Springer
13 years 10 months ago
Face Recognition System Based on PCA and Feedforward Neural Networks
Face recognition is one of the most important image processing research topics which is widely used in personal identification, verification and security applications. In this pape...
Alaa Eleyan, Hasan Demirel
KES
2007
Springer
13 years 10 months ago
Face Recognition Based on 2D and 3D Features
This paper presents a completly automated face recognition system integrating both two dimensional (texture) and three dimensional (shape) features. We introduce a novel fusion str...
Stefano Arca, Raffaella Lanzarotti, Giuseppe Lipor...
ICIP
2001
IEEE
14 years 6 months ago
A comparison of discrete and continuous output modeling techniques for a pseudo-2D hidden Markov model face recognition system
Face recognition has become an important topic within the field of pattern recognition and computer vision. In this field a number of different approaches to feature extraction, m...
Frank Wallhoff, Stefan Eickeler, Gerhard Rigoll
IJCV
2006
206views more  IJCV 2006»
13 years 4 months ago
Random Sampling for Subspace Face Recognition
Subspacefacerecognitionoftensuffersfromtwoproblems:(1)thetrainingsamplesetissmallcompared with the high dimensional feature vector; (2) the performance is sensitive to the subspace...
Xiaogang Wang, Xiaoou Tang