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AVBPA
2001
Springer
145views Biometrics» more  AVBPA 2001»
15 years 9 months ago
Using Mixture Covariance Matrices to Improve Face and Facial Expression Recognitions
In several pattern recognition problems, particularly in image recognition ones, there are often a large number of features available, but the number of training samples for each p...
Carlos E. Thomaz, Duncan Fyfe Gillies, Raul Queiro...
ICPR
2008
IEEE
15 years 11 months ago
Multilinear analysis based on image texture for face recognition
In this paper, a multilinear approach based on image texture for face recognition is present. First, we extract the texture features of the facial images using the Local Binary Pa...
Hu-chuan Lu, Hao Chen, Yen-wei Chen
ICMCS
2006
IEEE
160views Multimedia» more  ICMCS 2006»
15 years 11 months ago
Selecting Kernel Eigenfaces for Face Recognition with One Training Sample Per Subject
It is well-known that supervised learning techniques such as linear discriminant analysis (LDA) often suffer from the so called small sample size problem when apply to solve face ...
Jie Wang, Konstantinos N. Plataniotis, Anastasios ...
ICPR
2006
IEEE
15 years 11 months ago
A Unified System for Segmentation and Tracking of Face and Hands in Sign Language Recognition
This paper presents a unified system for segmentation and tracking of face and hands in a sign language recognition using a single camera. Unlike much related work that uses colou...
George Awad, Junwei Han, Alistair Sutherland
ICANN
2005
Springer
15 years 10 months ago
Discriminative Common Images for Face Recognition
Linear discrimination analysis (LDA) technique is an important and well-developed area of image recognition and to date many linear discrimination methods have been put forward. Ba...
Vo Dinh Minh Nhat, Sungyoung Lee