NDLI: Face recognition based on sparse representation applied to mobile device

Content Provider	IEEE Xplore Digital Library
Author	Kuan-Yu Chou Guan-Ming Huang Hao-Chien Tseng Yon-Ping Chen
Copyright Year	2014
Description	Author affiliation: Inst. of Electr. Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan (Kuan-Yu Chou; Guan-Ming Huang; Hao-Chien Tseng; Yon-Ping Chen)
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.
Sponsorship	IEEE Syst., Man, Cybern. Soc.
Starting Page	81
Ending Page	86
File Size	1492134
Page Count	6
File Format	PDF
e-ISBN	9781479945849
DOI	10.1109/CACS.2014.7097166
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-11-26
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Dictionaries Face recognition Face verification Mobile handsets Android Eigenface Training Databases Haar-like Feature extraction Sparse representation Face Adaboost
Content Type	Text
Resource Type	Article

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