NDLI: Face recognizability evaluation for ATM applications with exceptional occlusion handling

Content Provider	IEEE Xplore Digital Library
Author	Sungmin Eum Jae Kyu Suhr Jaihie Kim
Copyright Year	2011
Description	Author affiliation: School of Electrical and Electronic Engineering, Yonsei University, Republic of Korea (Sungmin Eum; Jae Kyu Suhr; Jaihie Kim)
Abstract	Biometrics has been extensively utilized to lessen the ATM-related crimes. One of the most widely used methods is to capture the facial images of the users for follow-up criminal investigations. However, this method is vulnerable to attacks made by the criminals with heavy facial occlusions. To overcome this drawback, this paper proposes a novel method for face recognizability evaluation with exceptional occlusion handling (EOH). The proposed method conducts a recognizability evaluation based on local regions of the facial components. Subsequently, the resulting decisions are reaffirmed by the EOH exploiting the global aspect of the frequently occurring facial occlusions. The EOH can be divided into two separate approaches: 1) accepting the falsely rejected cases, 2) rejecting the falsely accepted cases. In this paper, two typical facial occlusions, eyeglasses and sunglasses, are chosen to prove the validity of the EOH. To evaluate the proposed method in the most realistic environment, an ATM database was constructed by using an off-the-shelf ATM while the users were asked to make withdrawals as they would in real situations. The proposed method was evaluated by the ATM database which includes 480 video sequences with 20 subjects. The results showed the feasibility of the face recognizability evaluation with the EOH in practical ATM environments.
Starting Page	82
Ending Page	89
File Size	2576204
Page Count	8
File Format	PDF
ISBN	9781457705298
ISSN	21607516
e-ISBN	9781457705304
DOI	10.1109/CVPRW.2011.5981883
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image recognition Databases Face recognition Mouth Detectors Face Asynchronous transfer mode
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
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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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