Hyperspectral face recognition using 3D Gabor wavelets

Linlin Shen, Songhao Zheng

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

45 Citations (Scopus)

Abstract

Compared to the fruitful research outputs in 2D face recognition, the research in hyperspectral face recognition is quite limited in literature. When most available works process 2D slices of hyperspectral data separately, a 3D Gabor wavelet based approach is proposed in this paper to extract features in spatial and spectrum domain simultaneously. As a result, the information contained in the 3D data can be fully exploited. Experimental results show that the proposed approach substantially outperforms the methods available in literature such as spectrum feature, PCA and 2D-PCA on the HK-PolyU Hyperspectral Face Database under the same testing protocol. When only one sample per subject is available for training, our method also achieves very robust performance.

Original languageEnglish
Title of host publicationICPR 2012 - 21st International Conference on Pattern Recognition
Pages1574-1577
Number of pages4
Publication statusPublished - 2012
Externally publishedYes
Event21st International Conference on Pattern Recognition, ICPR 2012 - Tsukuba, Japan
Duration: 11 Nov 201215 Nov 2012

Publication series

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

Conference

Conference21st International Conference on Pattern Recognition, ICPR 2012
Country/TerritoryJapan
CityTsukuba
Period11/11/1215/11/12

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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