Metaverse Airport Crowd Anomaly Detection Dataset

Published: 19 August 2026| Version 1 | DOI: 10.17632/wnwr4tthgs.1
Contributors:
Soha Mohamed,
,

Description

Video footage was collected from simulated surveillance cameras positioned throughout a virtual airport, capturing both normal and abnormal passenger behaviours. Two main areas were established: the Entrance Gate and the Departure Terminal, with three videos recorded for each area, resulting in a total of six videos. The cameras captured the movements and behaviours of virtual passengers from different viewpoints. At the Entrance Gate, the cameras provided frontal, rear, and side views of passenger activities and interactions with the security area. In the Departure Terminal, the cameras focused on passport checking, queues, and the waiting area, capturing a variety of passenger activities. Complete Extracted Frames: The complete set of 13,815 frames extracted from the six original surveillance videos is available through the associated Google Drive repository. The frames were extracted at a rate of 10 frames per second from the two simulated metaverse airport scenes: Entrance Gate and Departure Terminal.

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Categories

Computer Science Applications, Computer Vision, Object Detection, Artificial Intelligence Applications

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