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

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

3 被引用数 (Scopus)

抄録

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.

本文言語英語
ホスト出版物のタイトルProceedings - 11th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2015
編集者Kokou Yetongnon, Albert Dipanda, Richard Chbeir
出版社Institute of Electrical and Electronics Engineers Inc.
ページ639-644
ページ数6
ISBN(電子版)9781467397216
DOI
出版ステータス出版済み - 2月 5 2016
イベント11th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2015 - Bangkok, タイ
継続期間: 11月 23 201511月 27 2015

出版物シリーズ

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

その他

その他11th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2015
国/地域タイ
CityBangkok
Period11/23/1511/27/15

!!!All Science Journal Classification (ASJC) codes

  • 信号処理
  • コンピュータ ネットワークおよび通信
  • 情報システム

フィンガープリント

「Efficient Facial and Facial Expression Recognition Using Canonical Correlation Analysis for Transform Domain Features Fusion and Classification」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル