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This paper discusses the semi-supervised marginal projection problems learning from partial constrained data. Two effective multimodal dimensionality reduction (DR) algorithms, which we call semi-supervised marginal projections (SSMP) and orthogonal SSMP (OSSMP), are proposed. By specifying the types of similarity pairs with the pairwise constraints (PC), our techniques can preserve the global structures...
A generalized neural reflectance (GNR) model for enhancing face recognition under variations in illumination and posture is presented in this paper. Our work is based on training a number of synthesis images of each face taken at single lighting direction with frontal/posture view. This way of synthesizing images can be used to build training cases for each face under different known illumination...
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