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Recent research has demonstrated the negative impact of makeup on automated face recognition. In this work, we introduce a patch-based ensemble learning method, which uses multiple subspaces generated by sampling patches from before-makeup and after-makeup face images, to address this problem. In the proposed scheme, each face image is tessellated into patches and each patch is represented by a set...
Recent research has established the negative impact of facial cosmetics on the matching accuracy of automated face recognition systems. In this paper, we analyze the impact of cosmetics on automated gender and age estimation algorithms. In this regard, we consider the use of facial cosmetics for (a) gender spoofing where male subjects attempt to look like females and vice versa, and (b) age alteration...
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