Affiliation:
1. School of Computing, Engineering and Physical Sciences (CEPS), University of the West of Scotland (UWS), Paisley PA1 2BE, UK
Abstract
Face verification, crucial for identity authentication and access control in our digital society, faces significant challenges when comparing images taken in diverse environments, which vary in terms of distance, angle, and lighting conditions. These disparities often lead to decreased accuracy due to significant resolution changes. This paper introduces an adaptive face verification solution tailored for diverse conditions, particularly focusing on Unmanned Aerial Vehicle (UAV)-based public safety applications. Our approach features an innovative adaptive verification threshold algorithm and an optimised operation pipeline, specifically designed to accommodate varying distances between the UAV and the human subject. The proposed solution is implemented based on a UAV platform and empirically compared with several state-of-the-art solutions. Empirical results have shown that an improvement of 15% in accuracy can be achieved.
Funder
EU Horizon 2020 ARCADIAN-IoT project
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Reference39 articles.
1. Search and rescue operation using UAVs: A case study;Golcarenarenji;Expert Syst. Appl.,2021
2. Zakaria, A.H., Mustafah, Y.M., Hatta, M.M.M., and Azlan, M.N.N. (June, January 31). Development of load carrying and releasing system of hexacopter. Proceedings of the 2015 10th Asian Control Conference (ASCC), Kota Kinabalu, Malaysia.
3. Internet of drones security: Taxonomies, open issues, and future directions;Derhab;Veh. Commun.,2023
4. (2023, November 10). EU H2020 Project ARCADIAN-IoT. Autonomous Trust, Security and Privacy Management Framework for IoT. Available online: https://www.arcadian-iot.eu/.
5. Deng, J., Guo, J., Xue, N., and Zafeiriou, S. (2019, January 15–19). Arcface: Additive angular margin loss for deep face recognition. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA.
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献