{"title":"基于三帧差分和背景相减的车辆检测算法","authors":"Haiying Zhang, Kun Wu","doi":"10.1109/ISCID.2012.45","DOIUrl":null,"url":null,"abstract":"A vehicle detection algorithm based on three-frame differencing and background subtraction is presented in this paper. Firstly, improved GMM is for background subtraction, then the moving object region is gained using background subtraction, and then the background subtraction is combined with three-frame differencing to detect the motion information. The simulation results show that the proposed algorithm runs veraciously and can lower the false detection rate, and fits for real time detection.","PeriodicalId":246432,"journal":{"name":"2012 Fifth International Symposium on Computational Intelligence and Design","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"45","resultStr":"{\"title\":\"A Vehicle Detection Algorithm Based on Three-Frame Differencing and Background Subtraction\",\"authors\":\"Haiying Zhang, Kun Wu\",\"doi\":\"10.1109/ISCID.2012.45\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A vehicle detection algorithm based on three-frame differencing and background subtraction is presented in this paper. Firstly, improved GMM is for background subtraction, then the moving object region is gained using background subtraction, and then the background subtraction is combined with three-frame differencing to detect the motion information. The simulation results show that the proposed algorithm runs veraciously and can lower the false detection rate, and fits for real time detection.\",\"PeriodicalId\":246432,\"journal\":{\"name\":\"2012 Fifth International Symposium on Computational Intelligence and Design\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"45\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Fifth International Symposium on Computational Intelligence and Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCID.2012.45\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Fifth International Symposium on Computational Intelligence and Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCID.2012.45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Vehicle Detection Algorithm Based on Three-Frame Differencing and Background Subtraction
A vehicle detection algorithm based on three-frame differencing and background subtraction is presented in this paper. Firstly, improved GMM is for background subtraction, then the moving object region is gained using background subtraction, and then the background subtraction is combined with three-frame differencing to detect the motion information. The simulation results show that the proposed algorithm runs veraciously and can lower the false detection rate, and fits for real time detection.
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