An Experimental Consideration on Gait Spoofing

Yuki Hirose, Kazuaki Nakamura, Naoko Nitta, Noboru Babaguchi

2023

Abstract

Deep learning technologies have improved the performance of biometric systems as well as increased the risk of spoofing attacks against them. So far, lots of spoofing and anti-spoofing methods were proposed for face and voice. However, for gait, there are a limited number of studies focusing on the spoofing risk. To examine the executability of gait spoofing, in this paper, we attempt to generate a sequence of fake gait silhouettes that mimics a certain target person’s walking style only from his/her single photo. A feature vector extracted from such a single photo does not have full information about the target person’s gait characteristics. To complement the information, we update the extracted feature so that it simultaneously contains various people’s characteristics like a wolf sample. Inspired by a wolf sample or also called “master” sample, which can simultaneously pass two or more verification systems like a master key, we call the proposed process “masterization”. After the masterization, we decode its resultant feature vector to a gait silhouette sequence. In our experiment, the gait recognition accuracy with the generated fake silhouette sequences is increased from 69% to 78% by the masterization, which indicates an unignorable risk of gait spoofing.

Paper Citation

in Harvard Style

Hirose Y., Nakamura K., Nitta N. and Babaguchi N. (2023). An Experimental Consideration on Gait Spoofing. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP; ISBN 978-989-758-634-7, SciTePress, pages 559-566. DOI: 10.5220/0011661200003417

in Bibtex Style

@conference{visapp23,
author={Yuki Hirose and Kazuaki Nakamura and Naoko Nitta and Noboru Babaguchi},
title={An Experimental Consideration on Gait Spoofing},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP},
year={2023},
pages={559-566},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011661200003417},
isbn={978-989-758-634-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP
TI - An Experimental Consideration on Gait Spoofing
SN - 978-989-758-634-7
AU - Hirose Y.
AU - Nakamura K.
AU - Nitta N.
AU - Babaguchi N.
PY - 2023
SP - 559
EP - 566
DO - 10.5220/0011661200003417
PB - SciTePress