Reconstruction of high-resolution facial images for visual surveillance

Jeong Seon Park, Seong Whan Lee

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

In this chapter we provide a summary of our previous works concerning the reconstruction of high-resolution facial images for visual surveillance. Specifically we present our methods of reconstructing high-resolution facial image from a low-resolution facial image based on example-based learning and iterative error back-projection. In our method, 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. Moreover iterative error back-projection is applied to improve the result of high-resolution reconstruction. The encouraging results of our methods show that our high-resolution reconstruction methods can be used to improve the performance of the face recognition by enhancing the resolution of low-resolution facial images captured in visual surveillance systems.

Original languageEnglish
Title of host publicationHandbook of Pattern Recognition and Computer Vision, 3rd Edition
PublisherWorld Scientific Publishing Co.
Pages445-460
Number of pages16
ISBN (Electronic)9789812775320
ISBN (Print)9812561056, 9789812561053
DOIs
Publication statusPublished - 2005 Jan 1

ASJC Scopus subject areas

  • Computer Science(all)

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