{"title":"基于区域邻接树的基准检测与设计","authors":"E. Costanza, J. Robinson","doi":"10.2312/vvg.20031009","DOIUrl":null,"url":null,"abstract":"We report a topological approach to fiducial recognition for real-time applications. Independence from geometry makes the system tolerant to severe distortion, and allows encoding of extra information. The method is based on region adjacency trees. After describing the mathematical foundations, we present a set of simulations to evaluate the algorithm and optimise the fiducial design.","PeriodicalId":137668,"journal":{"name":"International Conference on Vision, Video and Graphics","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"75","resultStr":"{\"title\":\"A Region Adjacency Tree Approach to the Detection and Design of Fiducials\",\"authors\":\"E. Costanza, J. Robinson\",\"doi\":\"10.2312/vvg.20031009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We report a topological approach to fiducial recognition for real-time applications. Independence from geometry makes the system tolerant to severe distortion, and allows encoding of extra information. The method is based on region adjacency trees. After describing the mathematical foundations, we present a set of simulations to evaluate the algorithm and optimise the fiducial design.\",\"PeriodicalId\":137668,\"journal\":{\"name\":\"International Conference on Vision, Video and Graphics\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"75\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Vision, Video and Graphics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2312/vvg.20031009\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Vision, Video and Graphics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2312/vvg.20031009","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Region Adjacency Tree Approach to the Detection and Design of Fiducials
We report a topological approach to fiducial recognition for real-time applications. Independence from geometry makes the system tolerant to severe distortion, and allows encoding of extra information. The method is based on region adjacency trees. After describing the mathematical foundations, we present a set of simulations to evaluate the algorithm and optimise the fiducial design.