This paper presents a novel framework for recognition of facial action unit (AU) combinations by viewing the classification as a sparse representation problem. Based on this framew...
Mohammad H. Mahoor, Mu Zhou, Kevin L. Veon, Seyed ...
This paper describes an improved boosting algorithm, the MutualBoost algorithm, and its application in developing a fast and robust Gabor feature based face recognition system. Th...
Gabor feature has been widely recognized as one of the best representations for face recognition. However, traditionally, it has to be reduced in dimension due to curse of dimensi...
Face representation based on Gabor features has attracted much attention and achieved great success in face recognition area for the advantages of the Gabor features. However, Gab...
Peng Yang, Shiguang Shan, Wen Gao, Stan Z. Li, Don...
Gabor-based Face representation has achieved great success in face recognition, while whether and how it can be applied to face detection is rarely studied. This paper originally i...
Jie Chen, Shiguang Shan, Peng Yang, Shengye Yan, X...
Though AdaBoost has been widely used for feature selection and classifier learning, many of the selected features, or weak classifiers, are redundant. By incorporating mutual infor...
LinLin Shen, Li Bai, Daniel Bardsley, Yangsheng Wa...
This paper proposes the AdaBoost Gabor Fisher Classifier (AGFC) for robust face recognition, in which a chain AdaBoost learning method based on Bootstrap re-sampling is proposed an...
Directional features extracted from Gabor responses are used as primitives for perceptual grouping. In previous work, we extracted Gabor features in 8 directions and then applied ...
Face representations based on Gabor features have achieved great success in face recognition, such as Elastic Graph Matching, Gabor Fisher Classifier (GFC), and AdaBoosted Gabor F...
This paper proposes a novel method for texture segmentation using independent component analysis (ICA) of Gabor features (called ICAG). It has three distinguished aspects. (1) Gab...