Cross-Domain Face Verification: Matching ID Document and Self-Portrait Photographs

Cross-domain biometrics has been emerging as a new necessity, which poses several additional challenges, including harsh illumination changes, noise, pose variation, among others. In this paper, we explore approaches to cross-domain face verification, comparing self-portrait photographs ("selfi...

Full description

Saved in:
Bibliographic Details
Main Authors Folego, Guilherme, Angeloni, Marcus A, Stuchi, José Augusto, Godoy, Alan, Rocha, Anderson
Format Journal Article
LanguageEnglish
Published 17.11.2016
Subjects
Computer Science - Computer Vision and Pattern Recognition
Online AccessGet full text

Cover

More Information
Summary:Cross-domain biometrics has been emerging as a new necessity, which poses several additional challenges, including harsh illumination changes, noise, pose variation, among others. In this paper, we explore approaches to cross-domain face verification, comparing self-portrait photographs ("selfies") to ID documents. We approach the problem with proper image photometric adjustment and data standardization techniques, along with deep learning methods to extract the most prominent features from the data, reducing the effects of domain shift in this problem. We validate the methods using a novel dataset comprising 50 individuals. The obtained results are promising and indicate that the adopted path is worth further investigation.
DOI:10.48550/arxiv.1611.05755