Weichen Sun, ZhanHua Yang, Bo Zhao, Y. Wang, Zhonglin Yang, Yutong Jiang, Haiping Song
{"title":"基于CNN和背景建模的复杂背景下区域监测目标检测研究","authors":"Weichen Sun, ZhanHua Yang, Bo Zhao, Y. Wang, Zhonglin Yang, Yutong Jiang, Haiping Song","doi":"10.1109/CMVIT57620.2023.00028","DOIUrl":null,"url":null,"abstract":"The regional monitoring systems aim to recognize and localize the target of interest in the region area. However, the target detection algorithm currently used in the regional monitoring system has problems such as low recognition probability under complex background conditions. The type of moving object recognized by the background modelling algorithm is difficult to judge. This paper proposes a monitoring area target detection method that fuses the detection results of the two YOLOv5 target detection algorithms and the Vibe background modelling method through Kalman filtering. Experiments show that the proposed method can improve the consistency and stability of target detection results in regional monitoring scenarios.","PeriodicalId":191655,"journal":{"name":"2023 7th International Conference on Machine Vision and Information Technology (CMVIT)","volume":"306 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Target Detection of Regional Monitoring with Complex Background using CNN and Background Modelling\",\"authors\":\"Weichen Sun, ZhanHua Yang, Bo Zhao, Y. Wang, Zhonglin Yang, Yutong Jiang, Haiping Song\",\"doi\":\"10.1109/CMVIT57620.2023.00028\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The regional monitoring systems aim to recognize and localize the target of interest in the region area. However, the target detection algorithm currently used in the regional monitoring system has problems such as low recognition probability under complex background conditions. The type of moving object recognized by the background modelling algorithm is difficult to judge. This paper proposes a monitoring area target detection method that fuses the detection results of the two YOLOv5 target detection algorithms and the Vibe background modelling method through Kalman filtering. Experiments show that the proposed method can improve the consistency and stability of target detection results in regional monitoring scenarios.\",\"PeriodicalId\":191655,\"journal\":{\"name\":\"2023 7th International Conference on Machine Vision and Information Technology (CMVIT)\",\"volume\":\"306 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 7th International Conference on Machine Vision and Information Technology (CMVIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CMVIT57620.2023.00028\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 7th International Conference on Machine Vision and Information Technology (CMVIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CMVIT57620.2023.00028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Target Detection of Regional Monitoring with Complex Background using CNN and Background Modelling
The regional monitoring systems aim to recognize and localize the target of interest in the region area. However, the target detection algorithm currently used in the regional monitoring system has problems such as low recognition probability under complex background conditions. The type of moving object recognized by the background modelling algorithm is difficult to judge. This paper proposes a monitoring area target detection method that fuses the detection results of the two YOLOv5 target detection algorithms and the Vibe background modelling method through Kalman filtering. Experiments show that the proposed method can improve the consistency and stability of target detection results in regional monitoring scenarios.