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» Improvement on PCA and 2DPCA Algorithms for Face Recognition
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AVSS
2006
IEEE
14 years 1 months ago
Feature Modelling of PCA Difference Vectors for 2D and 3D Face Recognition
This paper examines the the effectiveness of feature modelling to conduct 2D and 3D face recognition. In particular, PCA difference vectors are modelled using Gaussian Mixture Mod...
Chris McCool, Jamie Cook, Vinod Chandran, Sridha S...
IPCV
2008
13 years 8 months ago
Face Recognition using PCA and LDA with Singular Value Decomposition (SVD)
Linear Discriminant Analysis(LDA) is well-known scheme for feature extraction and dimension reduction. It has been used widely in many applications involving high-dimensional data,...
Neeta Nain, Nitish Agarwal, Prashant Gour, Rakesh ...
ICPR
2010
IEEE
14 years 4 days ago
On the Dimensionality Reduction for Sparse Representation Based Face Recognition
Face recognition (FR) is an active yet challenging topic in computer vision applications. As a powerful tool to represent high dimensional data, recently sparse representation bas...
Lei Zhang, Meng Yang, Zhizhao Feng, David Zhang
WACV
2002
IEEE
14 years 8 days ago
A PDA-based Face Recognition System
In this paper, we present a PDA-based face recognition system as well as some of the associated challenges of developing a PDAbased face recognition system. We describe a prototyp...
Jie Yang, Xilin Chen, William Kunz
ACII
2005
Springer
14 years 25 days ago
Facial Expression Recognition Using HLAC Features and WPCA
This paper proposes a new facial expression recognition method which combines Higher Order Local Autocorrelation (HLAC) features with Weighted PCA. HLAC features are computed at ea...
Fang Liu, Zhiliang Wang, Li Wang, Xiuyan Meng