Izvorni znanstveni članak
https://doi.org/10.24138/jcomss-2023-0165
Face Verification Algorithms for UAV Applications: An Empirical Comparative Analysis
Julio Diez-Tomillo
orcid.org/0000-0003-1979-3592
; University of the West of Scotland (UWS), Paisley, United Kingdom
Jose M. Alcaraz-Calero
; University of the West of Scotland (UWS), Paisley, United Kingdom
Qi Wang
orcid.org/0000-0002-7764-9858
; University of the West of Scotland (UWS), Paisley, United Kingdom
Sažetak
Unmanned Aerial Vehicles (UAVs) are revolutionising diverse computer vision use case domains, from public safety surveillance to Search and Rescue (SAR), and other emergency management and disaster relief operations. The growing need for accurate face verification algorithms has prompted an exploration of synergies between UAVs and face verification. This promises cost-effective, wide-area, non-intrusive person verification. Real-world human-centric use cases such as a ”Drone Guard Angel” for vulnerable people can contribute to public safety management and offload significant police resources. These scenarios demand efficient face verification to distinguish correctly the end users for authentication, authorisation and customised services. This paper investigates the suitability of existing solutions, and analyses five state-of-the-art candidate face verification algorithms. Informed by the advantages and disadvantages of existing solutions, the paper proposes an extended dataset and a refined face verification pipeline. Subsequently, it conducts empirical evaluation of these algorithms using the proposed pipeline and dataset in terms of inference times and the distribution of the similarity indexes. Furthermore, this paper provides essential guidance for algorithm selection and deployment in UAV-based applications. Two candidate algorithms, ArcFace and FaceNet512, have emerged as the top performers. The choice between them will depend on the specific use case requirements.
Ključne riječi
Face verification; UAV; Drone; Similarity index; Inference speed
Hrčak ID:
314237
URI
Datum izdavanja:
12.1.2024.
Posjeta: 137 *