{"title":"拟合距离数据的平面参数方差。","authors":"Marek Franaszek","doi":"10.6028/jres.115.032","DOIUrl":null,"url":null,"abstract":"<p><p>Formulas for variances of plane parameters fitted with Nonlinear Least Squares to point clouds acquired by 3D imaging systems (e.g., LADAR) are derived. Two different error objective functions used in minimization are discussed: the orthogonal and the directional functions. Comparisons of corresponding formulas suggest the two functions can yield different results when applied to the same dataset.</p>","PeriodicalId":17039,"journal":{"name":"Journal of Research of the National Institute of Standards and Technology","volume":"115 6","pages":"461-70"},"PeriodicalIF":1.5000,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4548868/pdf/","citationCount":"2","resultStr":"{\"title\":\"Variances of Plane Parameters Fitted to Range Data.\",\"authors\":\"Marek Franaszek\",\"doi\":\"10.6028/jres.115.032\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Formulas for variances of plane parameters fitted with Nonlinear Least Squares to point clouds acquired by 3D imaging systems (e.g., LADAR) are derived. Two different error objective functions used in minimization are discussed: the orthogonal and the directional functions. Comparisons of corresponding formulas suggest the two functions can yield different results when applied to the same dataset.</p>\",\"PeriodicalId\":17039,\"journal\":{\"name\":\"Journal of Research of the National Institute of Standards and Technology\",\"volume\":\"115 6\",\"pages\":\"461-70\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2010-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4548868/pdf/\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Research of the National Institute of Standards and Technology\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.6028/jres.115.032\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2010/11/1 0:00:00\",\"PubModel\":\"Print\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Research of the National Institute of Standards and Technology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.6028/jres.115.032","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2010/11/1 0:00:00","PubModel":"Print","JCR":"","JCRName":"","Score":null,"Total":0}
Variances of Plane Parameters Fitted to Range Data.
Formulas for variances of plane parameters fitted with Nonlinear Least Squares to point clouds acquired by 3D imaging systems (e.g., LADAR) are derived. Two different error objective functions used in minimization are discussed: the orthogonal and the directional functions. Comparisons of corresponding formulas suggest the two functions can yield different results when applied to the same dataset.
期刊介绍:
The Journal of Research of the National Institute of Standards and Technology is the flagship publication of the National Institute of Standards and Technology. It has been published under various titles and forms since 1904, with its roots as Scientific Papers issued as the Bulletin of the Bureau of Standards.
In 1928, the Scientific Papers were combined with Technologic Papers, which reported results of investigations of material and methods of testing. This new publication was titled the Bureau of Standards Journal of Research.
The Journal of Research of NIST reports NIST research and development in metrology and related fields of physical science, engineering, applied mathematics, statistics, biotechnology, information technology.