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Large Scale 3D Morphable Models
We present large scale facial model (LSFM)—a 3D Morphable Model (3DMM) automatically constructed from 9663 distinct facial identities. To the best of our knowledge LSFM is the largest-scale Morphable Model ever constructed, containing statistical information from a huge variety of the human populati...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6953995/ https://www.ncbi.nlm.nih.gov/pubmed/31983806 http://dx.doi.org/10.1007/s11263-017-1009-7 |
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author | Booth, James Roussos, Anastasios Ponniah, Allan Dunaway, David Zafeiriou, Stefanos |
author_facet | Booth, James Roussos, Anastasios Ponniah, Allan Dunaway, David Zafeiriou, Stefanos |
author_sort | Booth, James |
collection | PubMed |
description | We present large scale facial model (LSFM)—a 3D Morphable Model (3DMM) automatically constructed from 9663 distinct facial identities. To the best of our knowledge LSFM is the largest-scale Morphable Model ever constructed, containing statistical information from a huge variety of the human population. To build such a large model we introduce a novel fully automated and robust Morphable Model construction pipeline, informed by an evaluation of state-of-the-art dense correspondence techniques. The dataset that LSFM is trained on includes rich demographic information about each subject, allowing for the construction of not only a global 3DMM model but also models tailored for specific age, gender or ethnicity groups. We utilize the proposed model to perform age classification from 3D shape alone and to reconstruct noisy out-of-sample data in the low-dimensional model space. Furthermore, we perform a systematic analysis of the constructed 3DMM models that showcases their quality and descriptive power. The presented extensive qualitative and quantitative evaluations reveal that the proposed 3DMM achieves state-of-the-art results, outperforming existing models by a large margin. Finally, for the benefit of the research community, we make publicly available the source code of the proposed automatic 3DMM construction pipeline, as well as the constructed global 3DMM and a variety of bespoke models tailored by age, gender and ethnicity. |
format | Online Article Text |
id | pubmed-6953995 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-69539952020-01-23 Large Scale 3D Morphable Models Booth, James Roussos, Anastasios Ponniah, Allan Dunaway, David Zafeiriou, Stefanos Int J Comput Vis Article We present large scale facial model (LSFM)—a 3D Morphable Model (3DMM) automatically constructed from 9663 distinct facial identities. To the best of our knowledge LSFM is the largest-scale Morphable Model ever constructed, containing statistical information from a huge variety of the human population. To build such a large model we introduce a novel fully automated and robust Morphable Model construction pipeline, informed by an evaluation of state-of-the-art dense correspondence techniques. The dataset that LSFM is trained on includes rich demographic information about each subject, allowing for the construction of not only a global 3DMM model but also models tailored for specific age, gender or ethnicity groups. We utilize the proposed model to perform age classification from 3D shape alone and to reconstruct noisy out-of-sample data in the low-dimensional model space. Furthermore, we perform a systematic analysis of the constructed 3DMM models that showcases their quality and descriptive power. The presented extensive qualitative and quantitative evaluations reveal that the proposed 3DMM achieves state-of-the-art results, outperforming existing models by a large margin. Finally, for the benefit of the research community, we make publicly available the source code of the proposed automatic 3DMM construction pipeline, as well as the constructed global 3DMM and a variety of bespoke models tailored by age, gender and ethnicity. Springer US 2017-04-08 2018 /pmc/articles/PMC6953995/ /pubmed/31983806 http://dx.doi.org/10.1007/s11263-017-1009-7 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Booth, James Roussos, Anastasios Ponniah, Allan Dunaway, David Zafeiriou, Stefanos Large Scale 3D Morphable Models |
title | Large Scale 3D Morphable Models |
title_full | Large Scale 3D Morphable Models |
title_fullStr | Large Scale 3D Morphable Models |
title_full_unstemmed | Large Scale 3D Morphable Models |
title_short | Large Scale 3D Morphable Models |
title_sort | large scale 3d morphable models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6953995/ https://www.ncbi.nlm.nih.gov/pubmed/31983806 http://dx.doi.org/10.1007/s11263-017-1009-7 |
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