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Hardhat-Wearing Detection for Enhancing On-Site Safety of Construction Workers

机译:安全帽佩戴检测可增强建筑工人的现场安全

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Construction is one of the most dangerous job sectors, which annually reports tens of thousands of time-loss injuries and deaths. These injuries and deaths do not only bring suffering to the workers and their families, but also incur delays and costs to the projects. Therefore, safety is an important issue that a general contractor must monitor and control. One of the fundamental safety regulations is wearing a hardhat, which should not be violated anytime on the sites. In this paper, a novel vision-based method is proposed to automate the monitoring of whether people are wearing hardhats on the construction sites. Under the method, human bodies and hardhats are first detected in the video frames captured by on-site construction cameras. Then, the matching between the detected human bodies and hardhats is performed using their geometric and spatial relationship. This way, the people who are not wearing hardhats could be automatically identified and safety alerts could be issued correspondingly. The method has been tested with real site videos. The high safety alert precision and recall of the method demonstrate its potential to facilitate the site safety monitoring work. (C) 2015 American Society of Civil Engineers.
机译:建筑是最危险的工作部门之一,每年报告成千上万的时间损失的伤亡。这些伤害和死亡不仅给工人及其家人带来痛苦,而且给项目造成延误和成本。因此,安全是总承包商必须监视和控制的重要问题。基本安全法规之一是戴安全帽,在现场任何时候都不应违反安全帽。在本文中,提出了一种新颖的基于视觉的方法来自动监视建筑工地上的人是否戴着安全帽。在该方法下,首先在现场施工摄像机捕获的视频帧中检测到人体和安全帽。然后,使用检测到的人体和安全帽之间的几何和空间关系进行匹配。这样,可以自动识别不戴安全帽的人员,并相应地发出安全警报。该方法已经过真实站点视频的测试。该方法具有很高的安全警报精度和召回率,证明了其潜在的便利现场安全监控工作的潜力。 (C)2015年美国土木工程师学会。

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