{"title":"具有密集运动目标的视频序列的有效背景估计方法","authors":"Hui Zhu, N. Mastorakis, X. Zhuang","doi":"10.1109/MCSI.2015.13","DOIUrl":null,"url":null,"abstract":"A method is proposed to estimate the background in video sequences with dense moving objects. The velocity field is estimated by optical flow to determine the image areas occupied by moving objects. The background is estimated by an efficient averaging process within the regions excluding the moving objects, which overcomes the foreground-occluding problem in common averaging method in a dynamic environment such as heavy traffic. The experimental results on traffic surveillance videos prove the effectiveness of the proposed method.","PeriodicalId":371635,"journal":{"name":"2015 Second International Conference on Mathematics and Computers in Sciences and in Industry (MCSI)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Method of Effective Background Estimation for Video Sequences with Dense Moving Objects\",\"authors\":\"Hui Zhu, N. Mastorakis, X. Zhuang\",\"doi\":\"10.1109/MCSI.2015.13\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A method is proposed to estimate the background in video sequences with dense moving objects. The velocity field is estimated by optical flow to determine the image areas occupied by moving objects. The background is estimated by an efficient averaging process within the regions excluding the moving objects, which overcomes the foreground-occluding problem in common averaging method in a dynamic environment such as heavy traffic. The experimental results on traffic surveillance videos prove the effectiveness of the proposed method.\",\"PeriodicalId\":371635,\"journal\":{\"name\":\"2015 Second International Conference on Mathematics and Computers in Sciences and in Industry (MCSI)\",\"volume\":\"70 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Second International Conference on Mathematics and Computers in Sciences and in Industry (MCSI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MCSI.2015.13\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Second International Conference on Mathematics and Computers in Sciences and in Industry (MCSI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MCSI.2015.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Method of Effective Background Estimation for Video Sequences with Dense Moving Objects
A method is proposed to estimate the background in video sequences with dense moving objects. The velocity field is estimated by optical flow to determine the image areas occupied by moving objects. The background is estimated by an efficient averaging process within the regions excluding the moving objects, which overcomes the foreground-occluding problem in common averaging method in a dynamic environment such as heavy traffic. The experimental results on traffic surveillance videos prove the effectiveness of the proposed method.
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