Face Recognition using Tridiagonal Matrix Enhanced Multivariance Products Representation

Basit Öğe Kaydı
dc.contributor.authorOzay, Evrim Korkmaz
dc.date.accessioned2024-03-13T10:30:19Z
dc.date.available2024-03-13T10:30:19Z
dc.date.issued2017
dc.departmentİstanbul Beykent Üniversitesien_US
dc.description11th International Conference on Mathematical Problems in Engineering, Aerospace and Sciences (ICNPAA) -- JUL 04-08, 2016 -- Univ La Rochelle, La Rochelle, FRANCEen_US
dc.description.abstractThis study aims to retrieve face images from a database according to a target face image. For this purpose, Tridiagonal Matrix Enhanced Multivariance Products Representation (TMEMPR) is taken into consideration. TMEMPR is a recursive algorithm based on Enhanced Multivariance Products Representation (EMPR). TMEMPR decomposes a matrix into three components which are a matrix of left support terms, a tridiagonal matrix of weight parameters for each recursion, and a matrix of right support terms, respectively. In this sense, there is an analogy between Singular Value Decomposition (SVD) and TMEMPR. However TMEMPR is a more flexible algorithm since its initial support terms (or vectors) can be chosen as desired. Low computational complexity is another advantage of TMEMPR because the algorithm has been constructed with recursions of certain arithmetic operations without requiring any iteration. The algorithm has been trained and tested with ORL face image database with 400 different grayscale images of 40 different people. TMEMPR's performance has been compared with SVD's performance as a result.en_US
dc.description.sponsorshipAmer Inst Aeronaut & Astronaut,Int Federat Nonlinear Analysts,Int Federat Informat Proc,Assoc Francaise Mecanique,Aquitaine Limousin PoitouCharente Reg,Charente Maritime Dept,Lab Sci Ingenieur Environnementen_US
dc.identifier.doi10.1063/1.4972675
dc.identifier.isbn978-0-7354-1464-8
dc.identifier.issn0094-243X
dc.identifier.scopus2-s2.0-85013663654en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1063/1.4972675
dc.identifier.urihttps://hdl.handle.net/20.500.12662/3253
dc.identifier.volume1798en_US
dc.identifier.wosWOS:000399203000083en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherAmer Inst Physicsen_US
dc.relation.ispartofIcnpaa 2016 World Congress: 11th International Conference On Mathematical Problems In Engineering, Aerospace And Sciencesen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleFace Recognition using Tridiagonal Matrix Enhanced Multivariance Products Representationen_US
dc.typeConference Objecten_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu