计算机与现代化Issue(3)：41-46,6.DOI:10.3969/j.issn.1006-2475.2024.03.007
面向摄像头视频监控的泥石流发生场景智能识别方法
Intelligent Identification Method of Debris Flow Scene Based on Camera Video Surveillance
摘要
Abstract
Camera video surveillance is widely used in debris flow disaster prevention and mitigation,but the existing video de-tection technology has limited functions and can not automatically judge the occurrence of debris flow disaster events.To solve this problem,using transfer learning strategy,this paper improves a video classification method based on convolutional neural network.Firstly,with the help of TSN model framework,the underlying network architecture is changed to ResNet-50,which is utilized for motion feature extraction and debris flow scene identification.Then,the model is pre-trained with ImageNet and Ki-netics 400 datasets to make the model have strong generalization ability.Finally,the model is trained and fine-tuned with the pre-processed geological disaster video dataset,so that it can accurately identify debris flow events.The model is tested by a large number of moving scene videos,and the experimental results show that the identification accuracy of the method for debris flow movement video can reach 87.73%.Therefore,the research results of this paper can to the play a full role of video surveil-lance in debris flow monitoring and warning.关键词
泥石流/视频监控/运动场景/迁移学习/智能识别Key words
debris flow/video surveillance/motion scene/transfer learning/intelligent recognition分类
信息技术与安全科学引用本文复制引用
胡美辰,刘敦龙,桑学佳,张少杰,陈乔..面向摄像头视频监控的泥石流发生场景智能识别方法[J].计算机与现代化,2024,(3):41-46,6.基金项目
国家自然科学基金青年项目(42001100) （42001100）
四川省自然科学基金资助项目(2023NSFSC0751) （2023NSFSC0751）
四川省信息化应用支撑软件工程技术研究中心开放课题(760115027) （760115027）
