DocumentCode :
3588299
Title :
Face recognition based on sparse representation applied to mobile device
Author :
Kuan-Yu Chou ; Guan-Ming Huang ; Hao-Chien Tseng ; Yon-Ping Chen
Author_Institution :
Inst. of Electr. Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
fYear :
2014
Firstpage :
81
Lastpage :
86
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.
Keywords :
face recognition; image representation; learning (artificial intelligence); minimisation; real-time systems; smart phones; visual databases; Android face recognition application; Cohn-Kanade face database; L2 norm minimization; ORL face database; Samsung Galaxy SII smart phone; Sheffield face database; Viola-Jones face detection program; data training; face verification system; general learning methods; mobile device; real-time application; sparse representation; Databases; Dictionaries; Face; Face recognition; Feature extraction; Mobile handsets; Training; Adaboost; Android; Haar-like; eigenface; face recognition; face verification; sparse representation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automatic Control Conference (CACS), 2014 CACS International
Print_ISBN :
978-1-4799-4586-3
Type :
conf
DOI :
10.1109/CACS.2014.7097166
Filename :
7097166
Link To Document :
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