Irregular luggage classification experiments using data from Tromsø airport

This paper examines the current state-of-the-art in object tracking and detection in the context of baggage handling systems using a variety of technologies, with special interest in image classification. Data collection at Tromsø Airport using simple and inexpensive equipment in order to capture im...

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Bibliographic Details
Main Authors: Jansson, Andreas Dyroy, Bremdal, Bernt Arild, Remman, Espen
Format: Conference Proceeding
Language:English
Subjects:
Airports
baggage handling
convolutional neural network
Data collection
data collection and preprocessing
Forestry
Image classification
Mechatronics
Object tracking
random forest
support vector machine
Support vector machine classification
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Summary:This paper examines the current state-of-the-art in object tracking and detection in the context of baggage handling systems using a variety of technologies, with special interest in image classification. Data collection at Tromsø Airport using simple and inexpensive equipment in order to capture images of different types of luggage will be described. Furthermore, a selection of three relevant techniques for image classification will be investigated, and experiments will be conducted to detect irregular and potentially problematic bags in the collected dataset. Finally, recommendations for use cases and an interface to an intelligent baggage handling system will be proposed.
DOI:10.1109/ICECCME57830.2023.10252185