Learning the relationship between high and low resolution images in kernel space for face super resolution

Wilman W.W. Zou, Pong Chi YUEN

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

13 Citations (Scopus)

Abstract

This paper proposes a new nonlinear face super resolution algorithm to address an important issue in face recognition from surveillance video namely, recognition of low resolution face image with nonlinear variations. The proposed method learns the nonlinear relationship between low resolution face image and high resolution face image in (nonlinear) kernel feature space. Moreover, the discriminative term can be easily included in the proposed framework. Experimental results on CMU-PIE and FRGC v2.0 databases show that proposed method outperforms existing methods as well as the recognition based on high resolution images.

Original languageEnglish
Title of host publicationProceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010
Pages1152-1155
Number of pages4
DOIs
Publication statusPublished - 2010
Event2010 20th International Conference on Pattern Recognition, ICPR 2010 - Istanbul, Turkey
Duration: 23 Aug 201026 Aug 2010

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Conference

Conference2010 20th International Conference on Pattern Recognition, ICPR 2010
Country/TerritoryTurkey
CityIstanbul
Period23/08/1026/08/10

Scopus Subject Areas

  • Computer Vision and Pattern Recognition

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