I. Atmosukarto, W. Leow, Zhiyong Huang, Yong Zhang, K. Sung
{"title":"从图像序列中恢复的非均匀分布和噪声的三维点进行网格构建","authors":"I. Atmosukarto, W. Leow, Zhiyong Huang, Yong Zhang, K. Sung","doi":"10.1109/PCCGA.2000.883976","DOIUrl":null,"url":null,"abstract":"This paper describes a novel method for constructing triangle meshes from noisy and non-uniformly distributed 3D points. It consists of two steps: noise point removal uses a clustering algorithm and epipolar constraint method to identify and remove noise points from the 3D points; and a constructive polygonization algorithm interpolates cleaned 3D points to construct a triangle mesh of the object.","PeriodicalId":342067,"journal":{"name":"Proceedings the Eighth Pacific Conference on Computer Graphics and Applications","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Mesh construction from non-uniformly distributed and noisy 3D points recovered from image sequence\",\"authors\":\"I. Atmosukarto, W. Leow, Zhiyong Huang, Yong Zhang, K. Sung\",\"doi\":\"10.1109/PCCGA.2000.883976\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes a novel method for constructing triangle meshes from noisy and non-uniformly distributed 3D points. It consists of two steps: noise point removal uses a clustering algorithm and epipolar constraint method to identify and remove noise points from the 3D points; and a constructive polygonization algorithm interpolates cleaned 3D points to construct a triangle mesh of the object.\",\"PeriodicalId\":342067,\"journal\":{\"name\":\"Proceedings the Eighth Pacific Conference on Computer Graphics and Applications\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings the Eighth Pacific Conference on Computer Graphics and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PCCGA.2000.883976\",\"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 the Eighth Pacific Conference on Computer Graphics and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PCCGA.2000.883976","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mesh construction from non-uniformly distributed and noisy 3D points recovered from image sequence
This paper describes a novel method for constructing triangle meshes from noisy and non-uniformly distributed 3D points. It consists of two steps: noise point removal uses a clustering algorithm and epipolar constraint method to identify and remove noise points from the 3D points; and a constructive polygonization algorithm interpolates cleaned 3D points to construct a triangle mesh of the object.
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
