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