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...
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...
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...
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...
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...