Abstract
Variation in pose is one of the main obstacles confronting researchers in the area of face recognition. In this paper, a novel method is proposed to explicitly tackle this problem. Multi-color uniform local binary pattern (ULBP) is introduced for extracting salient features along with wavelet transform. Learning scheme is adopted to obtain a mapping coefficient vector between face in a pose and frontal face. Then expected frontal face view vector could be generated by inserting the posed face. Instead of using the entire face, some of its important regions are taken into account. The proposed method relies only on single frontal face image as a gallery image. Results have demonstrated that the proposed method operates well even under the low-resolution conditions.
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