NDLI: Reliable face recognition by random subspace Support Vector Machine ensemble

Content Provider	IEEE Xplore Digital Library
Author	Bailing Zhang
Copyright Year	2012
Description	Author affiliation: Xi'an Jiaotong-Liverpool University, Suzhou, China (Bailing Zhang)
Abstract	Though many progresses have been made, face recognition is still a challenging topic in computer vision. Most of the published works focused on accurate classifiers design to produce identity predictions for query faces without suggesting how reliable the predictions are. These classifiers may not be applicable in some critical situations where the incorrect predictions have serious consequences. Aiming to tackle this problem, this paper proposes a highly reliable face recognition scheme by Random Subspace Support Vector Machine (SVM) ensemble which provides a reject option. Being different with previous classifier ensembles which purpose to increase the classification accuracy only, the objective of the proposed SVM ensemble is to supply classification confidence to accommodate the situations where no decision should be made if the confidence is low. The ensemble is created using Random Subspace (RS) method, together with four different feature descriptions to comprehensively characterize face images, including Local Binary Pattern (LBP), Pyramid Histogram of Oriented Gradient (PHOG), Gabor filtering and wavelet transform. The consensus from the ensemble's voting conforms to the confidence measure and the rejection option is accomplished accordingly when the confidence falls below a threshold. The reliable recognition scheme is empirically evaluated using a realistic face database created by the author, showing that pre-defined 100% accuracy can be reached with a rejection rate 7%.
Starting Page	415
Ending Page	420
File Size	653426
Page Count	6
File Format	PDF
ISBN	9781467314848
ISSN	2160133X
e-ISBN	9781467314879
DOI	10.1109/ICMLC.2012.6358950
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Reliability Face Abstracts Random Subspace Reliable face recognition Classification confidence Rejection option SVM ensemble
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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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