Linear Laplacian discrimination for feature extraction
Discriminant feature extraction plays a fundamental role in pattern recognition. In this paper,
we propose the linear Laplacian discrimination (LLD) algorithm/or discriminant feature …
we propose the linear Laplacian discrimination (LLD) algorithm/or discriminant feature …
Facial expression recognition based on tensor local linear discriminant analysis
Z Wang, Q Ruan, G An - 2012 IEEE 11th International …, 2012 - ieeexplore.ieee.org
Linear discriminant analysis (LDA) is an effective method for solving the classification
problems. Many based-discriminant analysis approaches have been proposed to extract …
problems. Many based-discriminant analysis approaches have been proposed to extract …
A new LDA-based method for face recognition
Y Bing, J Lianfu, C Ping - 2002 International Conference on …, 2002 - ieeexplore.ieee.org
Linear discriminant analysis (LDA) is a feature extraction technique for classification. In this
paper, we propose a new LDA-based method that can overcome the drawback existed in …
paper, we propose a new LDA-based method that can overcome the drawback existed in …
Facial expression recognition based orthogonal local fisher discriminant analysis
Z Wang, Q Ruan - IEEE 10th International Conference on …, 2010 - ieeexplore.ieee.org
In recent years, feature extraction method make an achievement in pattern recognition. It
extracts not only useful feature for classification, but also reduces the dimension of pattern …
extracts not only useful feature for classification, but also reduces the dimension of pattern …
Dual-space linear discriminant analysis for face recognition
Linear discriminant analysis (LDA) is a popular feature extraction technique for face
recognition. However, it often suffers from the small sample size problem when dealing with …
recognition. However, it often suffers from the small sample size problem when dealing with …
Random sampling LDA for face recognition
Linear discriminant analysis (LDA) is a popular feature extraction technique for face
recognition. However, It often suffers from the small sample size problem when dealing with …
recognition. However, It often suffers from the small sample size problem when dealing with …
Face recognition by stepwise nonparametric margin maximum criterion
X Qiu, L Wu - … Conference on Computer Vision (ICCV'05) …, 2005 - ieeexplore.ieee.org
Linear discriminant analysis (LDA) is a popular feature extraction technique in face
recognition. However, it often suffers from the small sample size problem when dealing with …
recognition. However, it often suffers from the small sample size problem when dealing with …
A new direct LDA (D-LDA) algorithm for feature extraction in face recognition
W Xiao-Jun, J Kittler, Y Jing-Yu… - Proceedings of the …, 2004 - ieeexplore.ieee.org
The problem of determining the optimal set of discriminant vectors for feature extraction in
pattern recognition is investigated. We propose a new direct LDA (D-LDA) method that is …
pattern recognition is investigated. We propose a new direct LDA (D-LDA) method that is …
2D direct LDA algorithm for face recognition
DU Cho, UD Chang, BH Kim, SH Lee… - Fourth International …, 2006 - ieeexplore.ieee.org
A new low-dimensional feature representation technique is presented in this paper. Linear
discriminant analysis is a popular feature extraction method. However, in the case of high …
discriminant analysis is a popular feature extraction method. However, in the case of high …
Face recognition using complete fuzzy LDA
In this paper, we propose a novel method for feature extraction and recognition, namely,
complete fuzzy LDA (CFLDA). CFLDA combines the complete LDA and fuzzy set theory …
complete fuzzy LDA (CFLDA). CFLDA combines the complete LDA and fuzzy set theory …