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An Associate-Predict Model for Face Recognition

8 years 2 months ago
An Associate-Predict Model for Face Recognition
Handling intra-personal variation is a major challenge in face recognition. It is difficult how to appropriately measure the similarity between human faces under significantly different settings (e.g., pose, illumination, and expression). In this paper, we propose a new model, called “Associate-Predict” (AP) model, to address this issue. The associate-predict model is built on an extra generic identity data set, in which each identity contains multiple images with large intra-personal variation. When considering two faces under significantly different settings (e.g., non-frontal and frontal), we first “associate” one input face with alike identities from the generic identity date set. Using the associated faces, we generatively “predict” the appearance of one input face under the setting of another input face, or discriminatively “predict” the likelihood whether two input faces are from the same person or not. We call the two proposed prediction methods as “appear...
Qi Yin, Jian Sun, Xiaoou Tang
Added 20 Aug 2011
Updated 20 Aug 2011
Type Journal
Year 2011
Where CVPR
Authors Qi Yin, Jian Sun, Xiaoou Tang
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