Wang Xiaoyan, Chai Pei, Li Rui, Yang Bo, Nie Wenzhao
{"title":"Research on Intelligent Analysis Technology of Power Monitoring Video Data Based on Convolutional Neural Network","authors":"Wang Xiaoyan, Chai Pei, Li Rui, Yang Bo, Nie Wenzhao","doi":"10.1109/ICMCCE51767.2020.00531","DOIUrl":null,"url":null,"abstract":"With the rapid increase of on-site monitoring objects and technological development, the power on-site image monitoring data has increased geometrically. For security managers, it is necessary to efficiently and quickly identify valid data and conduct intelligent early warning. Therefore, this paper proposes an intelligent analysis method of power field surveillance video data based on convolutional neural network. Firstly, the original surveillance video material is extracted. Secondly, the video cloud storage platform is used for storage and data cleaning. At the same time, the hidden danger behaviors are classified and analyzed and marked. Finally, the proposed method is used for feature extraction, model training and field verification to realize intelligent early warning analysis of video big data. The field application effect shows that the method proposed in this paper can realize the functions of video image data feature extraction, model training, and improve the effect of image processing. Eventually, it can meet the needs of on-site video data intelligent analysis and has a certain promotion prospect.","PeriodicalId":6712,"journal":{"name":"2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)","volume":"88 1","pages":"2461-2464"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMCCE51767.2020.00531","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the rapid increase of on-site monitoring objects and technological development, the power on-site image monitoring data has increased geometrically. For security managers, it is necessary to efficiently and quickly identify valid data and conduct intelligent early warning. Therefore, this paper proposes an intelligent analysis method of power field surveillance video data based on convolutional neural network. Firstly, the original surveillance video material is extracted. Secondly, the video cloud storage platform is used for storage and data cleaning. At the same time, the hidden danger behaviors are classified and analyzed and marked. Finally, the proposed method is used for feature extraction, model training and field verification to realize intelligent early warning analysis of video big data. The field application effect shows that the method proposed in this paper can realize the functions of video image data feature extraction, model training, and improve the effect of image processing. Eventually, it can meet the needs of on-site video data intelligent analysis and has a certain promotion prospect.