Multiview angle UAV infrared image simulation with segmented model and object detection for traffic surveillance

Abstract With the rapid development of infrared (IR) imaging UAV technology, infrared aerial image processing technology has been applied in different fields. But it is not very convenient to obtain real aerial images in some cases because of flight limitations, acquisition costs and other factors....

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Main Authors: Tuerniyazi Aibibu, Jinhui Lan, Yiliang Zeng, Jinghao Hu, Zhuo Yong
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-025-89585-x
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author Tuerniyazi Aibibu
Jinhui Lan
Yiliang Zeng
Jinghao Hu
Zhuo Yong
author_facet Tuerniyazi Aibibu
Jinhui Lan
Yiliang Zeng
Jinghao Hu
Zhuo Yong
author_sort Tuerniyazi Aibibu
collection DOAJ
description Abstract With the rapid development of infrared (IR) imaging UAV technology, infrared aerial image processing technology has been applied in different fields. But it is not very convenient to obtain real aerial images in some cases because of flight limitations, acquisition costs and other factors. So, it is necessary to simulate UAV infrared images by computer. This paper proposed an improved infrared aerial image simulation method based on open source AirSim. By improving the original AirSim infrared image simulation method, the simulation quality of the infrared image is improved via 3-dimensional segmented model processing. The infrared aerial images of the traffic scene with different viewing angles are simulated via the proposed method in this paper and we constructed infrared traffic scene simulation dataset (IR-TSS) containing seven types of objects. We propose the efficient EfficientNCSP-Net net for the IR-TSS dataset and use popular methods for comparative experiments. The experimental results show that the proposed EfficientNCSP-Net has an mAP50 greater than 96% for object detection on IR-TSS dataset, which is better than those of the existing methods. This paper not only contributes to research on infrared image simulations of traffic scenes, but also has referential significance in other aerial image simulation fields.
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institution DOAJ
issn 2045-2322
language English
publishDate 2025-02-01
publisher Nature Portfolio
record_format Article
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spelling doaj-art-8b558df33bd74e12a528c76e4651523a2025-08-20T02:43:15ZengNature PortfolioScientific Reports2045-23222025-02-0115111810.1038/s41598-025-89585-xMultiview angle UAV infrared image simulation with segmented model and object detection for traffic surveillanceTuerniyazi Aibibu0Jinhui Lan1Yiliang Zeng2Jinghao Hu3Zhuo Yong4Department of Instrument Science and Technology, School of Automation and Electrical Engineering, University of Science and Technology BeijingDepartment of Instrument Science and Technology, School of Automation and Electrical Engineering, University of Science and Technology BeijingDepartment of Instrument Science and Technology, School of Automation and Electrical Engineering, University of Science and Technology BeijingDepartment of Instrument Science and Technology, School of Automation and Electrical Engineering, University of Science and Technology BeijingDepartment of Instrument Science and Technology, School of Automation and Electrical Engineering, University of Science and Technology BeijingAbstract With the rapid development of infrared (IR) imaging UAV technology, infrared aerial image processing technology has been applied in different fields. But it is not very convenient to obtain real aerial images in some cases because of flight limitations, acquisition costs and other factors. So, it is necessary to simulate UAV infrared images by computer. This paper proposed an improved infrared aerial image simulation method based on open source AirSim. By improving the original AirSim infrared image simulation method, the simulation quality of the infrared image is improved via 3-dimensional segmented model processing. The infrared aerial images of the traffic scene with different viewing angles are simulated via the proposed method in this paper and we constructed infrared traffic scene simulation dataset (IR-TSS) containing seven types of objects. We propose the efficient EfficientNCSP-Net net for the IR-TSS dataset and use popular methods for comparative experiments. The experimental results show that the proposed EfficientNCSP-Net has an mAP50 greater than 96% for object detection on IR-TSS dataset, which is better than those of the existing methods. This paper not only contributes to research on infrared image simulations of traffic scenes, but also has referential significance in other aerial image simulation fields.https://doi.org/10.1038/s41598-025-89585-x
spellingShingle Tuerniyazi Aibibu
Jinhui Lan
Yiliang Zeng
Jinghao Hu
Zhuo Yong
Multiview angle UAV infrared image simulation with segmented model and object detection for traffic surveillance
Scientific Reports
title Multiview angle UAV infrared image simulation with segmented model and object detection for traffic surveillance
title_full Multiview angle UAV infrared image simulation with segmented model and object detection for traffic surveillance
title_fullStr Multiview angle UAV infrared image simulation with segmented model and object detection for traffic surveillance
title_full_unstemmed Multiview angle UAV infrared image simulation with segmented model and object detection for traffic surveillance
title_short Multiview angle UAV infrared image simulation with segmented model and object detection for traffic surveillance
title_sort multiview angle uav infrared image simulation with segmented model and object detection for traffic surveillance
url https://doi.org/10.1038/s41598-025-89585-x
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