{"title":"点云MapReduce配准算法研究","authors":"Song Liu, Xiao Xie","doi":"10.1109/CCIS.2011.6045086","DOIUrl":null,"url":null,"abstract":"An improved algorithm of point cloud ICP registration base on MapReduce is proposed. This method applies parallel computing of MapReduce to registration of point cloud in order to reduce the requirements of computing and improve the efficiency of computing. At last, the results of three examples running on a Hadoop cluster show that the efficiency of registration has been improved and the results achieve the expectant target.","PeriodicalId":128504,"journal":{"name":"2011 IEEE International Conference on Cloud Computing and Intelligence Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Research on algorithm of point cloud MapReduce registration\",\"authors\":\"Song Liu, Xiao Xie\",\"doi\":\"10.1109/CCIS.2011.6045086\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An improved algorithm of point cloud ICP registration base on MapReduce is proposed. This method applies parallel computing of MapReduce to registration of point cloud in order to reduce the requirements of computing and improve the efficiency of computing. At last, the results of three examples running on a Hadoop cluster show that the efficiency of registration has been improved and the results achieve the expectant target.\",\"PeriodicalId\":128504,\"journal\":{\"name\":\"2011 IEEE International Conference on Cloud Computing and Intelligence Systems\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE International Conference on Cloud Computing and Intelligence Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCIS.2011.6045086\",\"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 IEEE International Conference on Cloud Computing and Intelligence Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCIS.2011.6045086","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on algorithm of point cloud MapReduce registration
An improved algorithm of point cloud ICP registration base on MapReduce is proposed. This method applies parallel computing of MapReduce to registration of point cloud in order to reduce the requirements of computing and improve the efficiency of computing. At last, the results of three examples running on a Hadoop cluster show that the efficiency of registration has been improved and the results achieve the expectant target.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
