大型机场不停航施工人员危险行为的图像识别方法

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI:10.1117/12.3014586

Zhenyu Zhao, Liangsui Geng

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引用次数: 0

摘要

在大型机场的不停航施工区域，确保人员安全和防止非法入侵至关重要。本研究提出了一种基于红外成像技术的大型机场不停航施工人员危险行为图像识别方法。利用红外成像技术采集大型机场不停航施工人员图像的视觉信息，利用结构化相似特征对图像进行分析；基于监督比较学习，采用提取骨干特征的方法，实现动态特征分割与重构处理；基于模糊性分析，提取人员边缘边界轮廓特征，识别人员危险入侵行为。通过实验验证，该方法对人员危险入侵行为的检测具有较高的准确性。

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Image recognition method for dangerous behavior of non-stop construction personnel in large airports

It is crucial to ensure the safety of personnel and prevent unauthorized intrusion in the non-stop construction area of large airports. This study proposes an image recognition method for dangerous behavior of non-stop construction personnel in large airports based on infrared imaging technology. Using infrared imaging technology to collect visual information of images of non-stop construction personnel in large airports, and analyzing images using structured similarity features; Based on supervised comparative learning, the method of extracting backbone features is adopted to achieve dynamic feature segmentation and reconstruction processing; Based on ambiguity analysis, extract the edge bounding contour features of personnel and identify dangerous intrusion behaviors of personnel. Through experimental verification, this method has high accuracy in detecting personnel's dangerous intrusion behavior.

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International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)

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