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Automatic detection of safety helmet wearing based on head region location

التفاصيل البيبلوغرافية
العنوان: Automatic detection of safety helmet wearing based on head region location
المؤلفون: Yuwan Gu, Yusheng Wang, Lin Shi, Ning Li, Lihua Zhuang, Shoukun Xu
المصدر: IET Image Processing, Vol 15, Iss 11, Pp 2441-2453 (2021)
بيانات النشر: Wiley, 2021.
سنة النشر: 2021
المجموعة: LCC:Computer software
مصطلحات موضوعية: Photography, TR1-1050, Computer software, QA76.75-76.765
الوصف: Abstract In order to solve the problem of difficult and low precision in the detection of safety helmet wearing in the complex pose of construction worker, a detection method of safety helmet wearing based on pose estimation is proposed. In the pose estimation model of OpenPose, the residual network optimized feature extraction is introduced to obtain the skeletal point information of the construction worker, and then the pose of the construction worker is estimated based on the skeletal point information, three‐point localization method is proposed for the front and back pose, and skin colour detection method is proposed for the side pose, and then to determine the head region. The YOLO v4 is used to detect the safety helmet region, and then the construction worker's safety helmet wearing is judged according to whether the head region intersects the safety helmet region or not. Experimental results show that the detection accuracy of the method is higher than other methods, and the adaptability to the environment is stronger.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1751-9667
1751-9659
Relation: https://doaj.org/toc/1751-9659; https://doaj.org/toc/1751-9667
DOI: 10.1049/ipr2.12231
URL الوصول: https://doaj.org/article/de1d1f86de3f4c799a445d8138403d71
رقم الأكسشن: edsdoj.1d1f86de3f4c799a445d8138403d71
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:17519667
17519659
DOI:10.1049/ipr2.12231