Face recognition based on sparse representation applied to mobile device

Kuan Yu Chou, Guan Ming Huang, Hao Chien Tseng, Yon-Ping Chen

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

2 Scopus citations

Abstract

This paper develops an Android face recognition application for users on mobile device, and applies it in the face verification system of Samsung Galaxy SII smart phone. The developed face recognition application includes three parts, the face detection using the Viola-Jones face detection program, the feature extraction implemented by the eigenface features, and the face recognition based on the sparse representation of L2 norm minimization. Different to general learning methods, the developed application does not require a tremendous amount of time in data training and can achieve a high recognition rate even higher than 99%, for examples 99.2% for the Sheffield face database, 99.4% for the Cohn-Kanade face database and 96.5% for ORL face database. Finally, the face verification application proposed for the Samsung Galaxy SII smart phone indeed successfully verifies a face just in one second which makes it a real-time application.

Original languageEnglish
Title of host publicationCACS 2014 - 2014 International Automatic Control Conference, Conference Digest
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages81-86
Number of pages6
ISBN (Electronic)9781479945849
DOIs
StatePublished - 28 Apr 2014
Event2014 International Automatic Control Conference, CACS 2014 - Kaohsiung, Taiwan
Duration: 26 Nov 201428 Nov 2014

Publication series

NameCACS 2014 - 2014 International Automatic Control Conference, Conference Digest

Conference

Conference2014 International Automatic Control Conference, CACS 2014
CountryTaiwan
CityKaohsiung
Period26/11/1428/11/14

Keywords

  • Adaboost
  • Android
  • eigenface
  • face recognition
  • face verification
  • Haar-like
  • sparse representation

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