DocumentCode :
2691813
Title :
Simplified Nearest Feature Line Space for Face Recognition
Author :
Yan, Lijun ; Feng, Qingxiang ; Pan, Jeng-Shyang
Author_Institution :
Dept. of Autom. Test & Control, Harbin Inst. of Technol., Harbin, China
fYear :
2012
fDate :
7-9 July 2012
Firstpage :
269
Lastpage :
272
Abstract :
In this paper, a novel subspace algorithm entitled Simplified Nearest Feature Line Space (SNFLS) is proposed based on Nearest Feature Line (NFL). NFL space (NFLS) is a subspace learning method and has desirable discriminant power. However, the computational complexity of NFLS is too high because all the feature lines are used. In SNFLS algorithm, some feature lines will be chosen for learning. SNFLS has the same discriminant power as NFLS. At the same time, SNFLS has a lower NFLS. Experimental results confirm its efficiency.
Keywords :
computational complexity; face recognition; feature extraction; learning (artificial intelligence); SNFLS algorithm; computational complexity; discriminant power; face recognition; simplified nearest feature line space; subspace learning method; Algorithm design and analysis; Computational complexity; Databases; Face; Face recognition; Feature extraction; Training; Face Recognition; Nearest Feature Line; Nearest Feature Line Space;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing, Measurement, Control and Sensor Network (CMCSN), 2012 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4673-2033-7
Type :
conf
DOI :
10.1109/CMCSN.2012.65
Filename :
6245864
Link To Document :
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