A Discriminative Model for Age Invariant Face Recognition

A Discriminative Model for Age Invariant Face Recognition

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The discriminative model is developed to address face matching in the presence of age variation. In this approach, each face is represented by designing a densely sampled local feature description scheme, in which Scale Invariant Feature Transform (SIFT) and Multi-scale Local Binary Patterns (MLBP) serve as local descriptors. Since both SIFT-based local features and MLBP-based local features span a high- dimensional feature space, an algorithm called multi-feature discriminant analysis (MFDA) is used to process these two local feature spaces in a unified framework. The new proposed method is d...