{"title":"从体素重建欧几里得平面","authors":"T. Linh, A. Imiya","doi":"10.1109/TDPVT.2004.1335395","DOIUrl":null,"url":null,"abstract":"We aim to formulate the recognition of a planes from a discrete point set as a nonlinear optimization problem, and we prove a uniqueness theorem for the solution of this problem. We deal with the supercover model in a space for the expression of discrete planes. The algorithm achieves invertible data compression of digital objects, since the algorithm transforms a collection voxels to a collection of plane parameters, which classify the voxels.","PeriodicalId":191172,"journal":{"name":"Proceedings. 2nd International Symposium on 3D Data Processing, Visualization and Transmission, 2004. 3DPVT 2004.","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Reconstruction of Euclidean planes from voxels\",\"authors\":\"T. Linh, A. Imiya\",\"doi\":\"10.1109/TDPVT.2004.1335395\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We aim to formulate the recognition of a planes from a discrete point set as a nonlinear optimization problem, and we prove a uniqueness theorem for the solution of this problem. We deal with the supercover model in a space for the expression of discrete planes. The algorithm achieves invertible data compression of digital objects, since the algorithm transforms a collection voxels to a collection of plane parameters, which classify the voxels.\",\"PeriodicalId\":191172,\"journal\":{\"name\":\"Proceedings. 2nd International Symposium on 3D Data Processing, Visualization and Transmission, 2004. 3DPVT 2004.\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 2nd International Symposium on 3D Data Processing, Visualization and Transmission, 2004. 3DPVT 2004.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TDPVT.2004.1335395\",\"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. 2nd International Symposium on 3D Data Processing, Visualization and Transmission, 2004. 3DPVT 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TDPVT.2004.1335395","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We aim to formulate the recognition of a planes from a discrete point set as a nonlinear optimization problem, and we prove a uniqueness theorem for the solution of this problem. We deal with the supercover model in a space for the expression of discrete planes. The algorithm achieves invertible data compression of digital objects, since the algorithm transforms a collection voxels to a collection of plane parameters, which classify the voxels.