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Synthesis of high-resolution facial image based on top-down learning

Authors
Hwang, BWPark, JSLee, SW
Issue Date
2003
Publisher
SPRINGER-VERLAG BERLIN
Keywords
High-Resolution Facial Image; Top-down Learning
Citation
AUDIO-BASED AND VIDEO-BASED BIOMETRIC PERSON AUTHENTICATION, PROCEEDINGS, v.2688, pp.377 - 384
Indexed
SCIE
SCOPUS
Journal Title
AUDIO-BASED AND VIDEO-BASED BIOMETRIC PERSON AUTHENTICATION, PROCEEDINGS
Volume
2688
Start Page
377
End Page
384
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/124367
ISSN
0302-9743
Abstract
This paper proposes a method of synthesizing a high-resolution facial image from a low-resolution facial image based on top-down learning. A face is represented by a linear combination of prototypes of shape and texture. With the shape and texture information about the pixels in an given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those of texture by solving least square minimization. Then high-resolution facial image can be synthesized by using the optimal coefficients for linear combination of the high-resolution prototypes. The encouraging results of the proposed method show that our method can be used to increase the performance of the face recognition by applying our method to enhance the low-resolution facial images captured at surveillance systems.
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