eprintid: 3361
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/33/61
datestamp: 2023-11-09 15:51:37
lastmod: 2023-11-09 15:51:37
status_changed: 2023-11-09 15:46:39
type: article
metadata_visibility: show
creators_name: Ali, A.S.O.
creators_name: Asirvadam, V.S.A.
creators_name: Malik, A.S.
creators_name: Aziz, A.
title: A geometrical approach for age-invariant face recognition
ispublished: pub
keywords: age-invariant; clustering; fgnet; frvt; Geometrical modeling; similarity proportion ratios; triangular features, Geometry; Information science; Mathematical models, Face recognition
note: cited By 5; Conference of 3rd International Visual Informatics Conference, IVIC 2013 ; Conference Date: 13 November 2013 Through 15 November 2013; Conference Code:100560
abstract: Human faces undergo considerable amounts of variations with aging. While face recognition systems have proven to be sensitive to factors such as illumination and pose, their sensitivity to facial aging effects is yet to be studied. The FRVT (Face Recognition Vendor Test) report estimated a decrease in performance by approximately 5 for each year of age difference. Therefore, the development of age-invariant capability remains an important issue for robust face recognition. This research study proposed a geometrical model based on multiple triangular features for the purpose of handling the challenge of face age variations that affect the process of face recognition. The system is aimed to serve in real time applications where the test images are usually taken in random scales that may not be of the same scale as the probe image, along with orientation, lighting ,illumination, and pose variations. Multiple mathematical equations were developed and used in the process of forming distinct subject clusters. These clusters hold the results of applying the developed mathematical models over the FGNET face aging database. The system was able to achieve a maximum classification accuracy of above 99 when the system was tested over the entire FGNET database. © 2013 Springer International Publishing.
date: 2013
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84887037132&doi=10.1007%2f978-3-319-02958-0_8&partnerID=40&md5=2ce7bb1479e56342f58a609c4133633a
id_number: 10.1007/978-3-319-02958-0₈
full_text_status: none
publication: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
volume: 8237 L
place_of_pub: Selangor
pagerange: 81-96
refereed: TRUE
isbn: 9783319029573
issn: 03029743
citation:   Ali, A.S.O. and Asirvadam, V.S.A. and Malik, A.S. and Aziz, A.  (2013) A geometrical approach for age-invariant face recognition.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8237 L.  pp. 81-96.  ISSN 03029743