NDLI: Scarce face recognition via two-layer collaborative representation

Content Provider	IET Digital Library
Author	Xia, Zhaoqiang Peng, Xianlin Feng, Xiaoyi Hadid, Abdenour
Abstract	The recent significant progress in face recognition is mainly achieved using learning-based (LE) techniques via an exhaustive training involving a huge number of face samples. However, in many applications, the number of face images available for training may be very limited. This makes LE techniques impractical for learning discriminative features and models. Thus, limited number of face samples (i.e. scarce data) degrades the recognition performance of most existing methods. To overcome this problem, the authors propose a novel approach based on two-layer collaborative representation to exploit the abundance of samples in some classes to enrich the scarce data in other classes. The first-layer collaborative representation uses the abundance of samples to construct representations for the scarce data. Then, a new face sample is recognised by computing residuals with the second-layer collaborative representation. Extensive experiments on four benchmark face databases demonstrate the effectiveness of their proposed approach which compares favourably against state-of-the-art methods.
Starting Page	56
Ending Page	62
Page Count	7
ISSN	20474938
Volume Number	7
e-ISSN	20474946
Issue Number	Issue 1, Jan (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-bmt/7/1
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-bmt.2017.0193
Journal	IET Biometrics
Publisher Date	2017-10-10
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Benchmark Face Databases Computer Vision And Image Processing Technique Discriminative Feature Learning Exhaustive Training Face Image Face Recognition Face Sample Feature Extraction First-layer Collaborative Representation Image Recognition Image Representation Knowledge Engineering Technique LE Technique Learning in AI Learning-based Technique Scarce Face Recognition Spatial And Pictorial Database Two-layer Collaborative Representation Visual Database
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Vision and Pattern Recognition Software

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