Título:
Differential 3D facial recognition : Adding 3D to your state-of-the-art 2D method
Otros títulos:
Coordinador:
Director:
Compilador:
Autor:
Di Martino, Matías
Suzacq, Fernando
Delbracio, Mauricio
Qiu, Qiang
Sapiro, Guillermo
Suzacq, Fernando
Delbracio, Mauricio
Qiu, Qiang
Sapiro, Guillermo
Tutor:
Tipo de documento:
Preprint
Editor:
Palabras clave:
Differential 3D
Active stereo
Face recognition
Spoofing detection
3D facial analysis
Three-dimensional displays
Two dimensional displays
Feature extraction
Facial features
Image resolution
Data mining
Active stereo
Face recognition
Spoofing detection
3D facial analysis
Three-dimensional displays
Two dimensional displays
Feature extraction
Facial features
Image resolution
Data mining
Descriptores:
Año de publicación:
2020
Contenido:
Resumen:
Active illumination is a prominent complement to enhance 2D face recognition and make it more robust, e.g., to spoofing attacks and low-light conditions. In the present work we show that it is possible to adopt active illumination to enhance state-of-the-art 2D face recognition approaches with 3D features, while bypassing the complicated task of 3D reconstruction. The key idea is to project over the test face a high spatial frequency pattern, which allows us to simultaneously recover real 3D information plus a standard 2D facial image. Therefore, state-of-the-art 2D face recognition solution can be transparently applied, while from the high frequency component of the input image, complementary 3D facial features are extracted. Experimental results on ND-2006 dataset show that the proposed ideas can significantly boost face recognition performance and dramatically improve the robustness to spoofing attacks.
Descripción:
metadata.articulos.dc.description.uri:
Editorial:
EN:
Financiadores:
Citación:
Di Martino, M., Suzacq, F., Delbracio, M. y otros. Differential 3D facial recognition : Adding 3D to your state-of-the-art 2D method [Preprint]. Publicado en : IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 42, no 7, jul. 2020, pp. 1582-1593. DOI: 10.1109/TPAMI.2020.2986951.
Citación:
metadata.articulos.cc.license.name:
ISBN:
e-ISBN:
ISSN:
ISMN:
Otros identificadores:
Cobertura geográfica:
Cobertura temporal:
Departamento académico:
Grupo de investigación:
Licencia:
Licencia Creative Commons Atribución (CC - By 4.0)
Colecciones:
| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| DSDQS20.pdf | Preprint | 2.17 MB | Adobe PDF |