{"title":"修改Mean-Shift头部跟踪","authors":"Daeha Lee, Jaehong Kim, J. Sohn","doi":"10.1109/URAI.2011.6146040","DOIUrl":null,"url":null,"abstract":"Mean-Shift algorithm has been applied mode seeking, image segmentation and object tracking. It is famous for fast convergence within limited boundary. But once exit that boundary, it fails to find correct region and position. We applied mean-shift algorithm in object tracking, and we suggest modified mean-shift tracking method. Using this modified version, we can track object without failing.","PeriodicalId":385925,"journal":{"name":"2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)","volume":"184 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Modified Mean-Shift for head tracking\",\"authors\":\"Daeha Lee, Jaehong Kim, J. Sohn\",\"doi\":\"10.1109/URAI.2011.6146040\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mean-Shift algorithm has been applied mode seeking, image segmentation and object tracking. It is famous for fast convergence within limited boundary. But once exit that boundary, it fails to find correct region and position. We applied mean-shift algorithm in object tracking, and we suggest modified mean-shift tracking method. Using this modified version, we can track object without failing.\",\"PeriodicalId\":385925,\"journal\":{\"name\":\"2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)\",\"volume\":\"184 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/URAI.2011.6146040\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/URAI.2011.6146040","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mean-Shift algorithm has been applied mode seeking, image segmentation and object tracking. It is famous for fast convergence within limited boundary. But once exit that boundary, it fails to find correct region and position. We applied mean-shift algorithm in object tracking, and we suggest modified mean-shift tracking method. Using this modified version, we can track object without failing.
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