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...
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
In this paper, we propose a random network ensemble for face recognition problem, particularly for images with a large appearance variation and with a limited number of training se...
In this paper, we propose volume based local Gabor binary patterns (V-LGBP) for face representation and recognition. In our method, the Gabor feature set of each gray image is reg...
A completely automatic face recognition system is presented. The method works on color and gray level images: after having localized the face and the facial features, it determine...
Paola Campadelli, Raffaella Lanzarotti, C. Savazzi