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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Universitas Indonesia
2002-08-01
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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 |
_version_ |
1725059114482008064 |