Morphable model space based face super-resolution reconstruction and recognition

Authors:
Di Zhang;Jiazhong He;Minghui Du
Affiliations:
School of Electronic and Information Engineering, South China University of Technology, Guangzhou, Guangdong 510641, China and Department of Computer Science, Shaoguan University, Shaoguan, Guangd ...;Department of Physics, Shaoguan University, Shaoguan, Guangdong 512005, China;School of Electronic and Information Engineering, South China University of Technology, Guangzhou, Guangdong 510641, China
Venue:
Image and Vision Computing
Year:
2012

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Abstract

Super-resolution image reconstruction is the process of producing a high-resolution image from a set of low-resolution images of the same scene. For the applications of performing face evaluation and/or recognition from low-resolution video surveillance, in the past, super-resolution image reconstruction was mainly used as a separate preprocessing step to obtain a high-resolution image in the pixel domain that is later passed to a face feature extraction and recognition algorithm. Such three-stage approach suffers a high degree of computational complexity. A low-dimensional morphable model space based face super-resolution reconstruction and recognition algorithm is proposed in this paper. The approach tries to construct the high-resolution information both required by reconstruction and recognition directly in the low dimensional feature space. We show that comparing with generic pixel domain algorithms, the proposed approach is more robust and more computationally efficient.