Face Recognition Under Turbulence and Environment Impacted Drone Surveillance (FR-Under-Drone 2023 Workshop)
(The topics covered by the workshop, with a description which specify the goals and the technical issues that the workshop aims to address.
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Face recognition has received a lot of attention due to surveillance needed across various security platforms ranging from border control to e-payments to secure office access. However, in the large crowd gathering in festivals or gaming events, identification of any possible suspects involving any avoidable mishappenings highly depends on facial information. The information might not be effectively captured using the traditional surveillance cameras due to their significant distance from the gathering event locations. For that, the use of drone sensors is an ideal solution. However, the acquired images generally suffer from poor quality. One probable reason for that is the effect of environmental factors such as turbulence. In this workshop coupled with the challenge session (accepted with the same title), we want to make the first step towards unconstrained surveillance using face recognition. The challenge and session will not only help the development of novel algorithms needed to improve face recognition performance but also disseminate the knowledge to the audience towards the possible future directions for real-world face recognition systems.
Face recognition in drone-shot videos has applicability in scenarios such as identifying individuals stuck at remote locations or in crowded places monitored via a drone. Recently, IARPA’s Biometric Recognition and Identification at Altitude and Range (BRIAR) program [1] also emphasizes the challenging problem of identifying individuals from long-range at elevated platforms. In brief, the goal of the workshop is to advance face recognition in challenging drone surveillance settings. The scope of the workshop includes but is not limited to the following topics:
Each paper needs to follow the official guidelines including the submission template (http://fg2023.ieee-biometrics.org/participate/submission)
Submission Link: https://cmt3.research.microsoft.com/FRDRONE2023/