Shannon wavelet kernel based subspace LDA approach in face recognition

Wen Sheng Chen*, Bin Fang, Pong Chi YUEN, Jian Huang Lai

*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

It is well-known that the distribution of face images with different pose, illumination and face expression is complex and nonlinear. The traditional linear methods, such as linear discriminant analysis (LDA), will not give a satisfactory performance. In addition, LDA always suffers from small sample size (S3) problem, which always occurs when the sample size is smaller than the dimensionality of feature vector. To overcome these limitations, Shannon wavelet kernel combining with subspace LDA (SWKSLDA) algorithm is developed. Two databases, namely FERET and CMU PIE databases, are selected for evaluation. Comparing with the existing LDA-based methods, the proposed method gives superior results.

Original languageEnglish
Title of host publication2006 International Conference on Computational Intelligence and Security, ICCIAS 2006
PublisherIEEE Computer Society
Pages708-713
Number of pages6
ISBN (Print)1424406056, 9781424406050
DOIs
Publication statusPublished - 2006
Event2006 International Conference on Computational Intelligence and Security, CIS 2006 - Guangzhou, China
Duration: 3 Oct 20066 Oct 2006
https://ieeexplore.ieee.org/xpl/conhome/4072023/proceeding
https://link.springer.com/book/10.1007/978-3-540-74377-4

Publication series

Name2006 International Conference on Computational Intelligence and Security, ICCIAS 2006
Volume1

Conference

Conference2006 International Conference on Computational Intelligence and Security, CIS 2006
Country/TerritoryChina
CityGuangzhou
Period3/10/066/10/06
Internet address

Scopus Subject Areas

  • Computer Science(all)
  • Control and Systems Engineering

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