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...
Abstract. We investigate a number of approaches to pose invariant face recognition. Basically, the methods involve three sequential functions for capturing nonlinear manifolds of f...
LDA is a popular subspace based face recognition approach. However, it often suffers from the small sample size problem. When dealing with the high dimensional face data, the LDA ...
A novel face recognition approach is proposed, based on the use of compressed discriminative features and recurrent neural classifiers. Low-dimensional feature vectors are extract...
We present an approach for object recognition that combines detection and segmentation within a efficient hypothesize/test framework. Scanning-window template classifiers are the ...