A System for Real-Time Detection of Abandoned Luggage

In this paper, we propose a system for the real-time automatic detection of abandoned luggage in an airport recorded by surveillance cameras. To do this, we use an adapted YOLOv11-s model and a proposed algorithm for detecting unattended luggage. The system uses the OpenCV library for the video proc...

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Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 25; H. 9; S. 2872
Hauptverfasser:	Vrsalovic, Ivan, Lerga, Jonatan, Ivasic-Kos, Marina
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 02.05.2025 MDPI
Schlagworte:	Accuracy Airports Algorithms Analysis Automation Cameras Computer vision Datasets deep learning DETR encoder–decoder transformer Luggage object detection Security systems Surveillance YOLOv11 YOLOv8 Germany Croatia United States > US deep learning DETR encoder–decoder transformer YOLOv11 OpenCV YOLOv8 computer vision object detection surveillance luggage detection
ISSN:	1424-8220, 1424-8220
Online-Zugang:	Volltext
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