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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...

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Detalles Bibliográficos
Autores principales: Piemontez, Rafael Alexandre, Comunello, Eros
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
Descripción
Sumario: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.