摘要
针对现有安全帽佩戴检测方法在施工人员复杂姿态下检测难度大、精度不高的问题,提出一种基于姿态估计的安全帽佩戴检测方法。该方法在OpenPose姿态估计模型中引入残差网络优化特征提取,获得施工人员的骨骼点信息,并提出三点定位法,通过骨骼点位置信息确定头部区域以缩小检测范围。使用RetinaNet检测头部区域安全帽的佩戴情况,以解决安全帽与施工背景之间类极不平衡的问题。实验表明,该方法在检测精度上较其他方法有明显提高,并且对环境的适应性更强。
The existing detection method of wearing safety helmet is difficult to detect in the complex posture of construction personnel,and its accuracy is not high.This paper proposed a detection method of wearing safety helmet based on posture estimation.This method used the residual network in the OpenPose pose estimation model to optimize feature extraction and obtained the skeleton point information of the constructor.This paper proposed a three-point positioning method to determine the head area through the position information of bone points to reduce the detection range.This method used RetinaNet to detect the wearing of the helmet in the head area to solve the problem of extreme imbalance between the helmet and the construction background.The experimental results show that this method has significantly improved detection accuracy than other methods,and is more adaptable to the environment.
作者
王雨生
顾玉宛
封晓晨
符心宇
庄丽华
徐守坤
Wang Yusheng;Gu Yuwan;Feng Xiaochen;Fu Xinyu;Zhuang Lihua;Xu Shoukun(School of Information Science&Engineering,School of Mathematics&Physics,Changzhou University,Changzhou Jiangsu 213164,China)
出处
《计算机应用研究》
CSCD
北大核心
2021年第3期937-940,945,共5页
Application Research of Computers
基金
国家自然科学基金资助项目(61906021)。
