NDLI: A simplified feature line approach for face recognition

Content Provider	IEEE Xplore Digital Library
Author	Zhen Wang Qian Tian Haiyan Xu Jianhui Wu
Copyright Year	2014
Description	Author affiliation: Nat. ASIC Syst. Eng. Res. Center, Southeast Univ., Nanjing, China (Zhen Wang; Qian Tian; Haiyan Xu; Jianhui Wu)
Abstract	For wireless terminals with the low memory, and limited computing performance, it is necessary to research face recognition strategies with low complexities and small memory requirements. The nearest feature line (NFL) classifier and its extended classifiers are effective for face recognition due to its improvement of the representational capacity of prototype. Therefore, this paper proposed a novel classifier-the simplified feature line (SFL). SFL not only keeps the advantages of NFL, but also significantly lowers the computational complexity by reducing the number of feature lines, and acquires better robustness. The experimental results based on real-world datasets show that SFL performs better than NFL in all experiment points, with the accuracy improved by about 5%-20% and its test duration cut down to 20%.
Starting Page	556
Ending Page	561
File Size	781483
Page Count	6
File Format	PDF
ISBN	9781479946129
ISSN	21653577
DOI	10.1109/ICDSP.2014.6900727
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Databases Training Face recognition Vectors Testing Digital signal processing Computational complexity Simplified feature line classifier Robustness Low computational complexity
Content Type	Text
Resource Type	Article

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