基于人脸检测与回归的安全帽检测

Yating Huang, Lingrui Zhu
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引用次数: 0

摘要

戴安全帽可以有效减少或防止施工现场危险物质对工人头部的伤害。然而,由于监管不力,经常发生工人不戴安全帽的安全事故。本文提出了一种基于人脸检测和脊回归的安全帽检测算法。首先通过人脸检测算法得到人脸盒的位置信息和人脸的五个关键点,然后通过脊回归模型得到人脸对应的头盔检测盒。我们收集了4000张戴头盔的人的图像,用于训练和测试脊回归模型。与一些最先进的方法相比,我们在测试集中取得了很好的效果。结果表明,mIoU达到70.118%,提高了检测率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Safety helmet detection based on face detection and regression
Wearing a safety helmet can effectively reduce or prevent injury to the worker's head caused by hazardous materials in the construction site. However, due to poor supervision, safety accidents often occur when workers don't wear safety helmets. In this paper, we propose a safety helmet detection algorithm based on face detection and ridge regression. Firstly, we get the location information of the face box and the five key points of the face through face detection algorithm, and then get the helmet detection box corresponding to face through ridge regression model. We collected 4000 images of people wearing helmets for training and testing of ridge regression models. Compared with some of the most advanced methods, we have achieved very good results in the test set. The results show that mIoU reaches 70.118% and the detection rate is improved.
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