Person authentication from neural activity of face-specific visual self-representation
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yeom, Seul-Ki | - |
dc.contributor.author | Suk, Heung-Il | - |
dc.contributor.author | Lee, Seong-Whan | - |
dc.date.accessioned | 2021-09-06T02:57:10Z | - |
dc.date.available | 2021-09-06T02:57:10Z | - |
dc.date.created | 2021-06-14 | - |
dc.date.issued | 2013-04 | - |
dc.identifier.issn | 0031-3203 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/103613 | - |
dc.description.abstract | In this paper, we propose a new biometric system based on the neurophysiological features of face-specific visual self representation in a human brain, which can be measured by ElectroEncephaloGraphy (EEG). First, we devise a novel stimulus presentation paradigm, using self-face and non-self-face images as stimuli for a person authentication system that can validate a person's identity by comparing the observed trait with those stored in the database (one-to-one matching). Unlike previous methods that considered the brain activities of the resting state, motor imagery, or visual evoked potentials, there are evidences that the proposed paradigm generates unique subject-specific brain-wave patterns in response to self- and non-self-face images from psychology and neurophysiology studies. Second, we devise a method for adaptive selection of EEG channels and time intervals for each subject in a discriminative manner. This makes the system immune to forgery since the selected EEG channels and time intervals for a client may not be consistent with those of imposters in terms of the latency and amplitude of the brain-waves. Based on our experimental results and analysis, it is believed that the proposed person authentication system can be considered as a new biometric authentication system. (C) 2012 Elsevier Ltd. All rights reserved. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER SCI LTD | - |
dc.subject | PATTERN-RECOGNITION | - |
dc.subject | EEG | - |
dc.subject | BRAIN | - |
dc.title | Person authentication from neural activity of face-specific visual self-representation | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Suk, Heung-Il | - |
dc.contributor.affiliatedAuthor | Lee, Seong-Whan | - |
dc.identifier.doi | 10.1016/j.patcog.2012.10.023 | - |
dc.identifier.scopusid | 2-s2.0-84871305036 | - |
dc.identifier.wosid | 000313858400006 | - |
dc.identifier.bibliographicCitation | PATTERN RECOGNITION, v.46, no.4, pp.1159 - 1169 | - |
dc.relation.isPartOf | PATTERN RECOGNITION | - |
dc.citation.title | PATTERN RECOGNITION | - |
dc.citation.volume | 46 | - |
dc.citation.number | 4 | - |
dc.citation.startPage | 1159 | - |
dc.citation.endPage | 1169 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.subject.keywordPlus | PATTERN-RECOGNITION | - |
dc.subject.keywordPlus | EEG | - |
dc.subject.keywordPlus | BRAIN | - |
dc.subject.keywordAuthor | Biometrics | - |
dc.subject.keywordAuthor | Person authentication | - |
dc.subject.keywordAuthor | Electroencephalography (EEG) | - |
dc.subject.keywordAuthor | Face-specific visual self representation | - |
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