In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neig...
Abstract. Motivated by the analogies to statistical physics, the deterministic annealing (DA) method has successfully been demonstrated in a variety of application. In this paper, ...
Linear discriminant analysis (LDA) has been an active topic of research during the last century. However, the existing algorithms have several limitations when applied to visual d...
Traditional discriminate analysis treats all the involved classes equally in the computation of the between-class scatter matrix. However, we find that for many vision tasks, the...
Abstract. The "discriminative direction" has been proven useful to reveal the subtle difference between two anatomical shape classes. When a shape moves along this direct...
Luping Zhou, Richard I. Hartley, Lei Wang, Paulett...