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SIBGRAPI
2005
IEEE
15 years 3 months ago
A Maximum Uncertainty LDA-Based Approach for Limited Sample Size Problems : With Application to Face Recognition
A critical issue of applying Linear Discriminant Analysis (LDA) is both the singularity and instability of the within-class scatter matrix. In practice, particularly in image recog...
Carlos E. Thomaz, Duncan Fyfe Gillies
ICCV
2011
IEEE
13 years 9 months ago
A Linear Subspace Learning Approach via Sparse Coding
Linear subspace learning (LSL) is a popular approach to image recognition and it aims to reveal the essential features of high dimensional data, e.g., facial images, in a lower di...
Lei Zhang, Pengfei Zhu, Qinghu Hu, David Zhang
ICCV
2007
IEEE
16 years 4 months ago
 A Component Based Deformable Model for Generalized Face Alignment
This paper presents a component based deformable model for generalized face alignment, in which a novel bistage statistical framework is proposed to account for both local and g...
Yuchi Huang, Qingshan Liu, Dimitris Metaxas
ICNC
2005
Springer
15 years 3 months ago
Line-Based PCA and LDA Approaches for Face Recognition
Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) techniques are important and well-developed area of image recognition and to date many linear discriminati...
Vo Dinh Minh Nhat, Sungyoung Lee
ICIP
2006
IEEE
15 years 11 months ago
Facial Expression Recognition using Advanced Local Binary Patterns, Tsallis Entropies and Global Appearance Features
This paper proposes a novel facial expression recognition approach based on two sets of features extracted from the face images: texture features and global appearance features. T...
Shu Liao, Wei Fan, Albert C. S. Chung, Dit-Yan Yeu...