Beyond social distancing: application of real-world coordinates in a multi-camera system with privacy protection
Ryan, Frances, Hu, FeiyanORCID: 0000-0001-7451-6438, Dietlmeier, JuliaORCID: 0000-0001-9980-0910, O'Connor, Noel E.ORCID: 0000-0002-4033-9135 and McGuinness, KevinORCID: 0000-0003-1336-6477
(2022)
Beyond social distancing: application of real-world coordinates in a multi-camera system with privacy protection.
In: 24th Irish Machine Vision and Image Processing Conference, 31 Aug - 2 Sept 2022, Belfast.
ISBN 978-0-9934207-7-1
In this paper, we develop a privacy-preserving framework to detect and track pedestrians and project to their real-world coordinates facilitating social distancing detection. The transform is calculated using social distancing markers or floor tiles visible in the camera view, without an extensive calibration process. We select a lightweight detection model to process CCTV videos and perform tracking within-camera. The features collected during within-camera tracking are then used to associate passenger trajectories across multiple cameras. We demonstrate and analyze results qualitatively for both social distancing detection and multi-camera tracking on real-world data captured in a busy airport in Dublin, Ireland.
Item Type:
Conference or Workshop Item (Paper)
Event Type:
Conference
Refereed:
Yes
Uncontrolled Keywords:
Social distancing; people detection; cross-camera tracking; coordinate calibration