Towards automatic waste containers management in cities via computer vision containers localization and geo-positioning in city maps

Towards automatic waste containers management in cities via computer vision : containers localization and geo-positioning in city maps

Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.

Bibliographische Detailangaben
Veröffentlicht in:Waste management (New York, N.Y.). - 1999. - 152(2022) vom: 16. Okt., Seite 59-68
1. Verfasser: Moral, Paula (VerfasserIn)
Weitere Verfasser: García-Martín, Álvaro, Escudero-Viñolo, Marcos, Martínez, José M, Bescós, Jesús, Peñuela, Jesús, Martínez, Juan Carlos, Alvis, Gonzalo
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2022
Zugriff auf das übergeordnete Werk:Waste management (New York, N.Y.)
Schlagworte:Journal Article Computer Vision Deep Learning Object detection Waste container localization Plastics
Beschreibung
Zusammenfassung:Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.
This paper describes the scientific achievements of a collaboration between a research group and the waste management division of a company. While these results might be the basis for several practical or commercial developments, we here focus on a novel scientific contribution: a methodology to automatically generate geo-located waste container maps. It is based on the use of Computer Vision algorithms to detect waste containers and identify their geographic location and dimensions. Algorithms analyze a video sequence and provide an automatic discrimination between images with and without containers. More precisely, two state-of-the-art object detectors based on deep learning techniques have been selected for testing, according to their performance and to their adaptability to an on-board real-time environment: EfficientDet and YOLOv5. Experimental results indicate that the proposed visual model for waste container detection is able to effectively operate with consistent performance disregarding the container type (organic waste, plastic, glass and paper recycling,…) and the city layout, which has been assessed by evaluating it on eleven different Spanish cities that vary in terms of size, climate, urban layout and containers' appearance
Beschreibung:Date Completed 07.09.2022
Date Revised 07.09.2022
published: Print-Electronic
Citation Status MEDLINE
ISSN:1879-2456
DOI:10.1016/j.wasman.2022.08.007