@inproceedings{7b93597e82bb4fe89428494ce298b4ab,
title = "An Image Processing Based Classifier to Support Safe Dropping for Delivery-by-Drone",
abstract = "Autonomous delivery-by-drone of packages is an active area of research and commercial development. However, the assessment of safe dropping/delivery zones has received limited attention. Ensuring that the dropping zone is a safe area for dropping, and continues to stay safe during the dropping process is key to safe delivery. This paper proposes a simple and fast classifier to assess the safety of a designated dropping zone before and during the dropping operation, using a single onboard camera. This classifier is, as far as we can tell, the first to address the problem of safety assessment at the point of delivery-by-drone. Experimental results on recorded drone videos show that the proposed classifier provides both average precision and average recall of 97\% in our test scenarios.",
keywords = "Autonomous drone, Drone delivery, Image processing, Segmentation, UAV, Unmanned Aerial Vehicles",
author = "Assem Alsawy and Alan Hicks and Dan Moss and Susan McKeever",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 5th IEEE International Image Processing, Applications and Systems Conference, IPAS 2022 ; Conference date: 05-12-2022 Through 07-12-2022",
year = "2022",
doi = "10.1109/IPAS55744.2022.10052868",
language = "English",
series = "5th IEEE International Image Processing, Applications and Systems Conference, IPAS 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "5th IEEE International Image Processing, Applications and Systems Conference, IPAS 2022",
address = "United States",
}