Improvements in Pose Invariance and Local Description for Gabor-based 2D Face Recognition (2008)
Abstract / truncated to 115 words
Automatic face recognition has attracted a lot of attention not only because of the large number of practical applications where human identification is needed but also due to the technical challenges involved in this problem: large variability in facial appearance, non-linearity of face manifolds and high dimensionality are some the most critical handicaps. In order to deal with the above mentioned challenges, there are two possible strategies: the first is to construct a “good” feature space in which the manifolds become simpler (more linear and more convex). This scheme usually comprises two levels of processing: (1) normalize images geometrically and photometrically and (2) extract features that are stable with respect to these variations (such as ... toggle 5 keywordsface recognition – gabor – pose invariant-face recognition – statistical feature modeling – intramodal fusion
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