{"title":"基于径向基函数的表面重构散射数据约简算法","authors":"Xinping Ji, Xiaojun Wu, M. Wang","doi":"10.1109/ICAT.2006.33","DOIUrl":null,"url":null,"abstract":"This paper concerns a method to reduce centers progressively for radial basis function surface reconstruction from scattered point set to decrease the computational complexity, which belongs to the category of data filtering. In the procedure of the algorithm, we use kd tree to reduce the computational complexity and make it practical for large number of points, then use the radial basis function to approximate, the good performance of the proposed filtering scheme is finally shown by some experimental examples","PeriodicalId":133842,"journal":{"name":"16th International Conference on Artificial Reality and Telexistence--Workshops (ICAT'06)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Algorithm of Scattered Data Reduction for Surface Reconstruction using Radial Basis Function\",\"authors\":\"Xinping Ji, Xiaojun Wu, M. Wang\",\"doi\":\"10.1109/ICAT.2006.33\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper concerns a method to reduce centers progressively for radial basis function surface reconstruction from scattered point set to decrease the computational complexity, which belongs to the category of data filtering. In the procedure of the algorithm, we use kd tree to reduce the computational complexity and make it practical for large number of points, then use the radial basis function to approximate, the good performance of the proposed filtering scheme is finally shown by some experimental examples\",\"PeriodicalId\":133842,\"journal\":{\"name\":\"16th International Conference on Artificial Reality and Telexistence--Workshops (ICAT'06)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"16th International Conference on Artificial Reality and Telexistence--Workshops (ICAT'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAT.2006.33\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"16th International Conference on Artificial Reality and Telexistence--Workshops (ICAT'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAT.2006.33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Algorithm of Scattered Data Reduction for Surface Reconstruction using Radial Basis Function
This paper concerns a method to reduce centers progressively for radial basis function surface reconstruction from scattered point set to decrease the computational complexity, which belongs to the category of data filtering. In the procedure of the algorithm, we use kd tree to reduce the computational complexity and make it practical for large number of points, then use the radial basis function to approximate, the good performance of the proposed filtering scheme is finally shown by some experimental examples