Skin-Based Identification From Multispectral Image Data Using CNNs
Takeshi Uemori, Atsushi Ito, Yusuke Moriuchi, Alexander Gatto, Jun Murayama
Abstract
User identification from hand images only is still a challenging task. In this paper, we propose a new biometric identification system based solely on a skin patch from a multispectral image. The system is utilizing a novel modified 3D CNN architecture which is taking advantage of multispectral data. We demonstrate the application of our system for the example of human identification from multispectral images of hands. To the best of our knowledge, this paper is the first to describe a pose-invariant and robust to overlapping real-time human identification system using hands. Additionally, we provide a framework to optimize the required spectral bands for the given spatial resolution limitations.
BibTeX
@inproceedings{cvpr2019_skinbasedidentif,
title = {Skin-Based Identification From Multispectral Image Data Using CNNs},
author = {Takeshi Uemori and Atsushi Ito and Yusuke Moriuchi and Alexander Gatto and Jun Murayama},
booktitle = {CVPR 2019},
year = {2019}
}