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A Multiscale Constraints Method Localization of 3D Facial Feature Points
It is an important task to locate facial feature points due to the widespread application of 3D human face models in medical fields. In this paper, we propose a 3D facial feature point localization method that combines the relative angle histograms with multiscale constraints. Firstly, the relative...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4620036/ https://www.ncbi.nlm.nih.gov/pubmed/26539244 http://dx.doi.org/10.1155/2015/178102 |
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author | Li, Hong-an Zhang, Yongxin Li, Zhanli Li, Huilin |
author_facet | Li, Hong-an Zhang, Yongxin Li, Zhanli Li, Huilin |
author_sort | Li, Hong-an |
collection | PubMed |
description | It is an important task to locate facial feature points due to the widespread application of 3D human face models in medical fields. In this paper, we propose a 3D facial feature point localization method that combines the relative angle histograms with multiscale constraints. Firstly, the relative angle histogram of each vertex in a 3D point distribution model is calculated; then the cluster set of the facial feature points is determined using the cluster algorithm. Finally, the feature points are located precisely according to multiscale integral features. The experimental results show that the feature point localization accuracy of this algorithm is better than that of the localization method using the relative angle histograms. |
format | Online Article Text |
id | pubmed-4620036 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-46200362015-11-04 A Multiscale Constraints Method Localization of 3D Facial Feature Points Li, Hong-an Zhang, Yongxin Li, Zhanli Li, Huilin Comput Math Methods Med Research Article It is an important task to locate facial feature points due to the widespread application of 3D human face models in medical fields. In this paper, we propose a 3D facial feature point localization method that combines the relative angle histograms with multiscale constraints. Firstly, the relative angle histogram of each vertex in a 3D point distribution model is calculated; then the cluster set of the facial feature points is determined using the cluster algorithm. Finally, the feature points are located precisely according to multiscale integral features. The experimental results show that the feature point localization accuracy of this algorithm is better than that of the localization method using the relative angle histograms. Hindawi Publishing Corporation 2015 2015-10-11 /pmc/articles/PMC4620036/ /pubmed/26539244 http://dx.doi.org/10.1155/2015/178102 Text en Copyright © 2015 Hong-an Li et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Li, Hong-an Zhang, Yongxin Li, Zhanli Li, Huilin A Multiscale Constraints Method Localization of 3D Facial Feature Points |
title | A Multiscale Constraints Method Localization of 3D Facial Feature Points |
title_full | A Multiscale Constraints Method Localization of 3D Facial Feature Points |
title_fullStr | A Multiscale Constraints Method Localization of 3D Facial Feature Points |
title_full_unstemmed | A Multiscale Constraints Method Localization of 3D Facial Feature Points |
title_short | A Multiscale Constraints Method Localization of 3D Facial Feature Points |
title_sort | multiscale constraints method localization of 3d facial feature points |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4620036/ https://www.ncbi.nlm.nih.gov/pubmed/26539244 http://dx.doi.org/10.1155/2015/178102 |
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