Cargando…
RAP3DF - One shoot 3D face dataset
Develop researches in the 3D biometrics field requires a large set of images, whether for training the algorithms or during the recognition test. Several datasets can be found in the literature. In an analysis of these datasets it was observed that a single dataset does not have the types of infrare...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7509182/ https://www.ncbi.nlm.nih.gov/pubmed/32995389 http://dx.doi.org/10.1016/j.dib.2020.106281 |
_version_ | 1783585553197826048 |
---|---|
author | Piemontez, Rafael Alexandre Comunello, Eros |
author_facet | Piemontez, Rafael Alexandre Comunello, Eros |
author_sort | Piemontez, Rafael Alexandre |
collection | PubMed |
description | Develop researches in the 3D biometrics field requires a large set of images, whether for training the algorithms or during the recognition test. Several datasets can be found in the literature. In an analysis of these datasets it was observed that a single dataset does not have the types of infrared images, visible and three-dimensional light, for the same sample. Given this context, the present work conceived this 3D facial dataset, with its respective visible light image and infrared spectrum, providing the entire image acquisition process from the Kinect One device. The work consists of 267 samples from 64 volunteers, where each volunteer has a frontal facial image and 3 images in arbitrary positions. |
format | Online Article Text |
id | pubmed-7509182 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-75091822020-09-28 RAP3DF - One shoot 3D face dataset Piemontez, Rafael Alexandre Comunello, Eros Data Brief Data Article Develop researches in the 3D biometrics field requires a large set of images, whether for training the algorithms or during the recognition test. Several datasets can be found in the literature. In an analysis of these datasets it was observed that a single dataset does not have the types of infrared images, visible and three-dimensional light, for the same sample. Given this context, the present work conceived this 3D facial dataset, with its respective visible light image and infrared spectrum, providing the entire image acquisition process from the Kinect One device. The work consists of 267 samples from 64 volunteers, where each volunteer has a frontal facial image and 3 images in arbitrary positions. Elsevier 2020-09-05 /pmc/articles/PMC7509182/ /pubmed/32995389 http://dx.doi.org/10.1016/j.dib.2020.106281 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Piemontez, Rafael Alexandre Comunello, Eros RAP3DF - One shoot 3D face dataset |
title | RAP3DF - One shoot 3D face dataset |
title_full | RAP3DF - One shoot 3D face dataset |
title_fullStr | RAP3DF - One shoot 3D face dataset |
title_full_unstemmed | RAP3DF - One shoot 3D face dataset |
title_short | RAP3DF - One shoot 3D face dataset |
title_sort | rap3df - one shoot 3d face dataset |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7509182/ https://www.ncbi.nlm.nih.gov/pubmed/32995389 http://dx.doi.org/10.1016/j.dib.2020.106281 |
work_keys_str_mv | AT piemontezrafaelalexandre rap3dfoneshoot3dfacedataset AT comunelloeros rap3dfoneshoot3dfacedataset |