现代电子技术2024，Vol.47Issue(10)：47-51,5.DOI:10.16652/j.issn.1004-373x.2024.10.009
电子监控部分遮挡目标单模态自监督信息挖掘技术
Single mode self supervised information mining technology for partially occluded targets in electronic monitoring
摘要
Abstract
In allusion to the difficulty of identifying occlusive targets in electronic surveillance video,the single-mode self-supervised information mining technology for partially occlusive targets in electronic monitoring is researched.In order to obtain the state information of the target,the occlusion detection method is used to judge whether there is a partially occluded target in the surveillance video.When there are partially occluded targets in surveillance video,subtraction clustering method is used to identify,track or describe specific targets,and provide more accurate and detailed target feature information.On this basis,the supervised occlusion target feature learning discrimination loss function constructed by cross entropy loss function and soft interval triplet loss function is used as the objective function for partially occluded target information mining.In each batch of electronic monitoring samples,the minimum distance negative sample pair and the maximum distance positive sample pair are mined,and the parameters are optimized by the backpropagation.From this,the sample of electronic monitoring image is input,and the results of self-supervised information mining are obtained by means of the forward propagation.The experimental results show that this technology can effectively mine the partially occluded targets of electronic monitoring,and the mAP value of target mining is higher than 0.9,which can provide a reliable basis for improving the recognition accuracy of monitoring targets.关键词
电子监控/遮挡检测/单模态自监督/信息挖掘/交叉熵损失函数/三元组损失函数Key words
electronic monitoring/occlusion detection/single-mode self-supervision/information mining/cross entropy loss function/triplet loss funtion分类
电子信息工程引用本文复制引用
周艳秋,高宏伟,何婷,辛春花..电子监控部分遮挡目标单模态自监督信息挖掘技术[J].现代电子技术,2024,47(10):47-51,5.基金项目
内蒙古自治区科技计划项目(2020GG0033) （2020GG0033）
内蒙古农业大学职业技术学院项目(TDS202311) （TDS202311）
