Method and Research of Real-time Video Hidden Danger Detection Platform Based on Offshore Oil Construction Scene
-
摘要: 本文根据施工现场管理特点,引入实时视频分析中海油施工场景隐患方面的应用以及模型的优化。为解决海洋工程现场工作人员不佩戴安全帽,未正确穿着服装,进入禁止区域等情况,避免因违规操作或违反规定,造成不必要的伤亡或损失,提出一套基于海油施工现场的视频识别告警系统,设计一套综合利用安全帽颜色、轮廓,服装特点以及多层神经网络分类建立的统计模型,对是否佩戴安全帽,是否正确穿着服装,是否进入禁行区域进行检测识别。从而在一定程度上杜绝了安全隐患。Abstract: According to the characteristics of construction site management, this paper introduces real-time video analysis of the application of cnooc construction scene hidden dangers and model optimization. To solve the problem of Marine engineering field workers without wearing helmet, not wearing clothes, right into the forbidden area, etc., avoid because of irregularities or in violation of regulations, unnecessary casualties or damage, based on a set of cnooc video identification of the alarm system on the construction site, design a set of comprehensive utilization of helmet color, outline, characteristics of clothing and multi-layer neural network classification statistical model is set up, whether to wear safety helmet and correctly wear clothing, whether into no-go area for testing. Thus, to a certain extent, put an end to safety hazards.
-
Key words:
- illegal operation /
- hidden dangers /
- detection and identification
-
[1] 郑世宝.智能视频监控技术与应用[J].电视技术,2009,33(1):94-96. [5] 肖东晖,林立.电力系统统一视频监控平台解决方案[J].电力系统自动化,2013,37(5):74-79. [2] 范亚男,葛卫丽.智能视频监控系统发展及应用[J].价值工程,2010,29(17):97-98. [3] 王素玉,沈兰荪.智能视觉监控技术研究进展[J].中国图象图形学报,2007,12(9):1 505-1 514. [4] 宫世杰,王薇,郭乔进,等.视频监控系统发展现状与趋势[J].科技技术创新,2018(29):81-82.
点击查看大图
计量
- 文章访问数: 10
- HTML全文浏览量: 2
- PDF下载量: 0
- 被引次数: 0