NDLI: Face recognition under partial occlusion and noise

Content Provider	IEEE Xplore Digital Library
Author	Jozer, B. Matej, F. Lubos, O. Milos, O. Jarmila, P.
Copyright Year	2013
Description	Author affiliation: Inst. of Comput. Sci. & Math., Slovak Univ. of Technol., Bratislava, Slovakia (Matej, F.; Lubos, O.; Milos, O.) \|\| Inst. of Telecommun., Slovak Univ. of Technol. Bratislava, Bratislava, Slovakia (Jozer, B.; Jarmila, P.)
Abstract	The human face is one of the most popular characteristic which can be used in the biometric security system to identify or verify a user. Face is an acceptable biometric modality because it can be captured from a distance, even without physical contact of the user being identified. Thus the identification or verification does not require cooperation of the user. Recognition systems based on human face are used for a wide variety of applications, due to these benefits. However, the crucial task is still to provide reliable recognition accuracy, but it is a challenging problem under real-world conditions. There have been proposed many methods, but only a few of them are being used in the real-world applications. Even the most recent face recognition algorithms are still facing problems when there is non-ideal imaging, varying illumination, occlusions in the scene or noise of used cameras. We solve these issues within The Next-Generation Hybrid Broadcast Broadband project (HBB-Next) [1]. In this project, we also deal with development of face recognition application, as part of multimodal interface, which will interact with HBB-TV user. In this paper we provide a comparative study of several conventional face recognition methods (PCA a.k.a. Eigenfaces, RBF) and novel kernel methods (KPCA, GDA and SVM) that are suitable to work properly under these conditions. We evaluate the influence of noise and partial occlusion on face recognition accuracy. We are focused on occlusions of eyes and eyebrows as these are the most significant features of a face. Face recognition rates achieved by machine learning methods with accuracy achieved by human perception only are compared. In addition we explore these methods for cases where only a few (up to 4) training samples is available.
Starting Page	2072
Ending Page	2079
File Size	753374
Page Count	8
File Format	PDF
ISBN	9781467322300
e-ISBN	9781467322324
DOI	10.1109/EUROCON.2013.6625266
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-01
Publisher Place	Croatia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Face recognition Noise Face Principal component analysis Kernel Support vector machines Eyebrows machine learning methods face recognition partial occlusion noise
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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