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首页 > 过刊浏览>2022年第31卷第4期 >346-351. DOI:10.15888/j.cnki.csa.008423
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基于Faster RCNN的穿越围栏违规行为检测
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基金项目:

国家自然科学基金(62072469); 国家重点科研计划(2018YFE0116700); 山东省自然科学基金(ZR2019MF049); 中央高校基础研究基金(2015020031); 西海岸人工智能技术创新中心建设专项(2019-1-5、2019-1-6); 上海可信工业控制平台开放项目(TICPSH202003015-ZC).


Faster RCNN-Based Detection Method for Violations of Crossing Fences
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    摘要:

    安全围栏在电力施工现场扮演着重要的角色, 但穿越围栏的违规行为普遍存在, 给施工现场造成了极大的安全隐患. 为了实现智能化监管, 本文利用目标检测算法, 结合帧差法的思想提出了一种基于Faster RCNN的穿越围栏违规行为检测方法. 该方法通过读取视频监控信息, 利用目标检测方法获取围栏的位置信息以及人体关键点的信息, 通过帧差判断法识别施工现场的违规动作. 经过实验验证, 该方法可以有效的检测出施工现场的穿越围栏违规行为, 并可以满足实时性的要求.

    Abstract:

    Safety fences play an important role in power construction sites. However, violations of crossing the fence are widespread, causing great safety hazards to the construction sites. To intelligently supervise, this study proposes a Faster RCNN-based detection method for crossing fence that combines the object detection and the ideas of frame difference method. The proposed method first obtains the information of the fence location and human keypoints by object detection from the captured frames in the video and then recognizes the violations at the construction site with the frame difference method. The experiment results show that the method can effectively detect violations of crossing fences at construction sites and meet the real-time requirements.

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王志鹏,王涛.基于Faster RCNN的穿越围栏违规行为检测.计算机系统应用,2022,31(4):346-351

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  • 收稿日期:2021-06-28
  • 最后修改日期:2021-07-30
  • 在线发布日期: 2022-03-22
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