NDLI: Face recognition using average example image

Content Provider	IET Digital Library
Author	Hwang, Wonjun Kim, Wonjun Suh, Sungjoo Han, Jae joon Kim, Junmo
Abstract	A novel face recognition approach by the use of a bundle of example images is presented, in which a combination of useful examples for face recognition is selected, and multiple augmented example images are made using those images. For this purpose, first, example images are divided into multiple groups using unsupervised methods such as the K-means method, and then clustering them into several groups according to their image variations. In each group, the most similar example images to an input image are found and they independently make an example average image from both the retrieved examples and their rank orders. When comparing similarities between two images, now local distance information can be utilised, which are calculated via corresponding average example images, as well as global distance information, the traditional direct comparison. The proposed approach is compared with the traditional direct comparison method on a multi-PIE database, and the generalisation ability of the proposed method across different features, such as local binary pattern, histogram of oriented gradients and Gabor features, is demonstrated.
Starting Page	1921
Ending Page	1923
Page Count	3
ISSN	00135194
Volume Number	50
e-ISSN	1350911X
Issue Number	Issue 25, Dec (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/50/25
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2014.2966
Journal	Electronics Letters
Publisher Date	2014-12-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Average Example Image Computer Vision And Image Processing Technique Face Recognition Gabor Feature Global Distance Information Histogram of Oriented Gradient HOG Image Recognition K-means Method LBP Local Binary Pattern Pattern Clustering Rank Order Unsupervised Learning Unsupervised Method
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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