Resolution enhancement of facial image using an error back-projection of example-based learning

Jeong Seon Park, Seong Whan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This paper proposes a new method of enhancing the resolution of facial image from a low-resolution facial image using a recursive error back-projection of example-based 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 a 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 obtained by using the optimal coefficients for linear combination of the high-resolution prototypes. In addition to, a recursive error back-projection is applied to improve the accuracy of resolution enhancement. The encouraging results of the proposed method show that our method can be used to improve the performance of the face recognition by applying our method to enhance the low-resolution facial images captured at visual surveillance systems.

Original languageEnglish
Title of host publicationProceedings - Sixth IEEE International Conference on Automatic Face and Gesture Recognition
Pages831-836
Number of pages6
Publication statusPublished - 2004 Sep 24
EventProceedings - Sixth IEEE International Conference on Automatic Face and Gesture Recognition FGR 2004 - Seoul, Korea, Republic of
Duration: 2004 May 172004 May 19

Other

OtherProceedings - Sixth IEEE International Conference on Automatic Face and Gesture Recognition FGR 2004
CountryKorea, Republic of
CitySeoul
Period04/5/1704/5/19

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Park, J. S., & Lee, S. W. (2004). Resolution enhancement of facial image using an error back-projection of example-based learning. In Proceedings - Sixth IEEE International Conference on Automatic Face and Gesture Recognition (pp. 831-836)