煤炭工程 ›› 2016, Vol. 48 ›› Issue (4): 111-113.doi: 10.11799/ce201604033

• 研究探讨 • 上一篇    下一篇

基于视频的煤矿安全监控行为识别系统研究

杨超宇1,李策1,苏剑臣1,王向前2,何叶荣3   

  1. 1. 中国矿业大学(北京)机电与信息工程学院
    2. 安徽理工大学
    3. 淮南师范学院经济与管理学院
  • 收稿日期:2015-12-03 修回日期:2016-01-27 出版日期:2016-04-10 发布日期:2016-04-18
  • 通讯作者: 杨超宇 E-mail:yangchy@aust.edu.cn

Research on video-based system of activity recognition for coal mine safety surveillance

  • Received:2015-12-03 Revised:2016-01-27 Online:2016-04-10 Published:2016-04-18

摘要: 提出了基于视频的煤矿安全监控行为识别系统的应用解决方案,分析了煤矿安全监控行为识别系统实际需求,实现了目标检测、特征提取、行为分类与行为识别、监控信息管理等功能。使用GMM模型提取前景运动目标,融合LBP作为目标描述特征、结合SVM实现了特征行为分类。基于Spring MVC框架实现了煤矿安全监控行为识别系统完整框架,为煤矿智能监控管理信息化提供了解决方案,提高了煤矿智能监控管理的效率、及时有效地发现煤矿安全生产隐患,降低了煤矿安全事故发生的概率。

关键词: 煤矿安全, 视频智能监控, 行为识别, 目标检测, 特征提取

Abstract: This paper proposed the application solutions of coal mine safety surveillance and activity recognition system based on video. The paper analyzed the practical requirement of coal mine safety surveillance, realized the functional modules for object detection, feature extraction, activity classification and activity identification, surveillance information management. By using GMM technology, the paper extract the moving target in foreground, applied LBP feature for object description and classified the activity with SVM. Based on Spring MVC, the paper implemented a complete framework of management system providing a solution for coal mine safety surveillance management information to improve the efficiency of the surveillance management. This management system could be used for timely discovery of coal mine safety emergencis and reduction the probability of occurrence of coal mine safety accidents.

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