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)


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.
Number of pages16
ISBN (Electronic)9789812775320
ISBN (Print)9812561056, 9789812561053
Publication statusPublished - 2005 Jan 1

ASJC Scopus subject areas

  • General Computer Science


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