{"title":"图像序列中运动检测的统计方法","authors":"S. Guetari, J. Devars","doi":"10.1109/CCECE.1995.526407","DOIUrl":null,"url":null,"abstract":"This paper presents a new statistical method based on the theory of large numbers for detection of objects in motion in a sequence of images. The method, relying on the occurrence of images as a function of time, combines a grey-level background construction and a discussion of the gradients calculated on the current image by comparison with a reference image.","PeriodicalId":158581,"journal":{"name":"Proceedings 1995 Canadian Conference on Electrical and Computer Engineering","volume":"179 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Statistical method for motion detection in an image sequence\",\"authors\":\"S. Guetari, J. Devars\",\"doi\":\"10.1109/CCECE.1995.526407\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a new statistical method based on the theory of large numbers for detection of objects in motion in a sequence of images. The method, relying on the occurrence of images as a function of time, combines a grey-level background construction and a discussion of the gradients calculated on the current image by comparison with a reference image.\",\"PeriodicalId\":158581,\"journal\":{\"name\":\"Proceedings 1995 Canadian Conference on Electrical and Computer Engineering\",\"volume\":\"179 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 1995 Canadian Conference on Electrical and Computer Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCECE.1995.526407\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 1995 Canadian Conference on Electrical and Computer Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCECE.1995.526407","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Statistical method for motion detection in an image sequence
This paper presents a new statistical method based on the theory of large numbers for detection of objects in motion in a sequence of images. The method, relying on the occurrence of images as a function of time, combines a grey-level background construction and a discussion of the gradients calculated on the current image by comparison with a reference image.
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