In Your Face: Person Identification Through Ratios of Distances Between Facial Features

Alsawwaf, M; Chaczko, Z; Kulbacki, M

In Your Face: Person Identification Through Ratios of Distances Between Facial Features

Alsawwaf, M

Chaczko, Z

Kulbacki, M

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Publisher:: Springer
Publication Type:: Conference Proceeding
Citation:: Intelligent Information and Database Systems, 2020, 12034 LNAI, pp. 527-536
Issue Date:: 2020-01-01

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Field	Value	Language
dc.contributor.author	Alsawwaf, M https://orcid.org/0000-0003-0359-9808
dc.contributor.author	Chaczko, Z https://orcid.org/0000-0002-2816-7510
dc.contributor.author	Kulbacki, M
dc.contributor.editor	Nguyen, NT
dc.contributor.editor	Jearanaitanakij, K
dc.contributor.editor	Selamat, A
dc.contributor.editor	Trawinski, B
dc.contributor.editor	Chittayasothorn, S
dc.date	2020-03-23
dc.date.accessioned	2021-04-29T06:20:36Z
dc.date.available	2021-04-29T06:20:36Z
dc.date.issued	2020-01-01
dc.identifier.citation	Intelligent Information and Database Systems, 2020, 12034 LNAI, pp. 527-536
dc.identifier.isbn	9783030420574
dc.identifier.issn	0302-9743
dc.identifier.issn	1611-3349
dc.identifier.uri	http://hdl.handle.net/10453/148540
dc.description.abstract	© 2020, Springer Nature Switzerland AG. These days identification of a person is an integral part of many computer-based solutions. It is a key characteristic for access control, customized services, and a proof of identity. Over the last couple of decades, many new techniques were introduced for how to identify human faces. The purpose of this paper is to introduce yet another innovative approach for face recognition. The human face consists of multiple features that when considered together produces a unique signature that identifies a single person. Building upon this premise, we are studying the identification of faces by producing ratios from the distances between the different features on the face and their locations in an explainable algorithm with the possibility of future inclusion of multiple spectrum and 3D images for data processing and analysis.
dc.language	en
dc.publisher	Springer
dc.relation.ispartof	Intelligent Information and Database Systems
dc.relation.ispartof	Asian Conference on Intelligent Information and Database Systems
dc.relation.ispartofseries	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.relation.isbasedon	10.1007/978-3-030-42058-1_44
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	In Your Face: Person Identification Through Ratios of Distances Between Facial Features
dc.type	Conference Proceeding
utslib.citation.volume	12034 LNAI
utslib.location.activity	Phuket, Thailand
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2021-04-29T06:20:35Z
pubs.finish-date	2020-03-25
pubs.place-of-publication	Singapore
pubs.publication-status	Published
pubs.start-date	2020-03-23
pubs.volume	12034 LNAI
dc.location	Singapore

Abstract:

© 2020, Springer Nature Switzerland AG. These days identification of a person is an integral part of many computer-based solutions. It is a key characteristic for access control, customized services, and a proof of identity. Over the last couple of decades, many new techniques were introduced for how to identify human faces. The purpose of this paper is to introduce yet another innovative approach for face recognition. The human face consists of multiple features that when considered together produces a unique signature that identifies a single person. Building upon this premise, we are studying the identification of faces by producing ratios from the distances between the different features on the face and their locations in an explainable algorithm with the possibility of future inclusion of multiple spectrum and 3D images for data processing and analysis.

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http://hdl.handle.net/10453/148540