A linear programming technique is introduced that jointly performs feature selection and classifier training so that a subset of features is optimally selected together with the c...
Abstract. This paper proposes a new approach to learning a discriminative model of object classes, incorporating appearance, shape and context information efficiently. The learned ...
Jamie Shotton, John M. Winn, Carsten Rother, Anton...
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 introduces the new color face recognition (FR) method that makes effective use of boosting learning as color-component feature selection framework. The proposed boost...
Jae Young Choi, Yong Man Ro, Konstantinos N. Plata...
Recently, we developed NIR based face recognition for highly accurate face recognition under illumination variations [10]. In this paper, we present a part-based method for improv...
Ke Pan, ShengCai Liao, Zhijian Zhang, Stan Z. Li, ...