Pengembangan Sistem Penentu Sudut Pandang Wajah 3-D dengan Menggunakan Perhitungan Jarak Terpendek pada Garis Ciri dalam Ruang Eigen

In this paper, we implemented a visual point estimation system using the nearest feature line method that is developed on human face’s eigenspace representation. This methodology is developed as a subsistim in a 3-D face recognition system using a neural networks, in order to develop a high accuracy...

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Main Authors: Rina Sripomo, Benyamin Kusumoputro
Format: Article
Language:English
Published: Universitas Indonesia 2002-08-01
Series:Makara Seri Sains
Subjects:
Online Access:http://journal.ui.ac.id/science/article/view/152/148
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spelling doaj-884e8cb9401b4fab9907c40f48bcf29d2020-11-25T01:37:12ZengUniversitas IndonesiaMakara Seri Sains1693-66712002-08-010628389Pengembangan Sistem Penentu Sudut Pandang Wajah 3-D dengan Menggunakan Perhitungan Jarak Terpendek pada Garis Ciri dalam Ruang EigenRina SripomoBenyamin KusumoputroIn this paper, we implemented a visual point estimation system using the nearest feature line method that is developed on human face’s eigenspace representation. This methodology is developed as a subsistim in a 3-D face recognition system using a neural networks, in order to develop a high accuracy Automatic Face Recognition (AFR) system with low computational cost. Several images of Indonesian human faces with various visual points and expressions are used as the input to the developed visual points estimation system, and another images, with their visual points is not used in the generating the feature lines, then used as the testing images. Results of experiments show that the visual points estimation system could determined the pose of the unknown position of 3-D face with its highest accuracy is about 90%. http://journal.ui.ac.id/science/article/view/152/1483D face recognition systemnearest feature line methodeigenspace representatiprincipal component analysis
collection DOAJ
language English
format Article
sources DOAJ
author Rina Sripomo
Benyamin Kusumoputro
spellingShingle Rina Sripomo
Benyamin Kusumoputro
Pengembangan Sistem Penentu Sudut Pandang Wajah 3-D dengan Menggunakan Perhitungan Jarak Terpendek pada Garis Ciri dalam Ruang Eigen
Makara Seri Sains
3D face recognition system
nearest feature line method
eigenspace representati
principal component analysis
author_facet Rina Sripomo
Benyamin Kusumoputro
author_sort Rina Sripomo
title Pengembangan Sistem Penentu Sudut Pandang Wajah 3-D dengan Menggunakan Perhitungan Jarak Terpendek pada Garis Ciri dalam Ruang Eigen
title_short Pengembangan Sistem Penentu Sudut Pandang Wajah 3-D dengan Menggunakan Perhitungan Jarak Terpendek pada Garis Ciri dalam Ruang Eigen
title_full Pengembangan Sistem Penentu Sudut Pandang Wajah 3-D dengan Menggunakan Perhitungan Jarak Terpendek pada Garis Ciri dalam Ruang Eigen
title_fullStr Pengembangan Sistem Penentu Sudut Pandang Wajah 3-D dengan Menggunakan Perhitungan Jarak Terpendek pada Garis Ciri dalam Ruang Eigen
title_full_unstemmed Pengembangan Sistem Penentu Sudut Pandang Wajah 3-D dengan Menggunakan Perhitungan Jarak Terpendek pada Garis Ciri dalam Ruang Eigen
title_sort pengembangan sistem penentu sudut pandang wajah 3-d dengan menggunakan perhitungan jarak terpendek pada garis ciri dalam ruang eigen
publisher Universitas Indonesia
series Makara Seri Sains
issn 1693-6671
publishDate 2002-08-01
description In this paper, we implemented a visual point estimation system using the nearest feature line method that is developed on human face’s eigenspace representation. This methodology is developed as a subsistim in a 3-D face recognition system using a neural networks, in order to develop a high accuracy Automatic Face Recognition (AFR) system with low computational cost. Several images of Indonesian human faces with various visual points and expressions are used as the input to the developed visual points estimation system, and another images, with their visual points is not used in the generating the feature lines, then used as the testing images. Results of experiments show that the visual points estimation system could determined the pose of the unknown position of 3-D face with its highest accuracy is about 90%.
topic 3D face recognition system
nearest feature line method
eigenspace representati
principal component analysis
url http://journal.ui.ac.id/science/article/view/152/148
work_keys_str_mv AT rinasripomo pengembangansistempenentusudutpandangwajah3ddenganmenggunakanperhitunganjarakterpendekpadagarisciridalamruangeigen
AT benyaminkusumoputro pengembangansistempenentusudutpandangwajah3ddenganmenggunakanperhitunganjarakterpendekpadagarisciridalamruangeigen
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