Efficient Facial and Facial Expression Recognition Using Canonical Correlation Analysis for Transform Domain Features Fusion and Classification

Ehab H. El-Shazly, Moataz M. Abdelwahab, Rin Ichiro Taniguchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In this paper, an efficient facial and facial expression recognition algorithm employing Canonical Correlation Analysis (CCA) for features fusion and classification is presented. Multiplefeaturesareextracted, transformedtodifferenttransformdomainsandfusedtogether. TwoDimensionalPrincipal Component Analysis (2DPCA) is used to maintain only the principal features representing different faces. 2DPCA also maintainsthespatialrelationbetweenadjacentpixelsimproving the overall recognition accuracy. CCA is being used for features fusion as well as classification. Experimental results on four different data sets showed that our algorithm outperform all most recent published state of the art techniques and reached 100 % recognition accuracy in most data sets.

Original languageEnglish
Title of host publicationProceedings - 11th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2015
EditorsKokou Yetongnon, Albert Dipanda, Richard Chbeir
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages639-644
Number of pages6
ISBN (Electronic)9781467397216
DOIs
Publication statusPublished - Feb 5 2016
Event11th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2015 - Bangkok, Thailand
Duration: Nov 23 2015Nov 27 2015

Publication series

NameProceedings - 11th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2015

Other

Other11th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2015
Country/TerritoryThailand
CityBangkok
Period11/23/1511/27/15

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications
  • Information Systems

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