期刊名称：International Journal of Environment and Geoinformatics
电子版ISSN：2148-9173
出版年度：2015
卷号：2
期号：2
页码：27-38
DOI：10.30897/ijegeo.303539
语种：English
出版社：IJEGEO
摘要：Normal 0 21 false false false TR X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable{mso-style-name:"Normal Tablo";mso-tstyle-rowband-size:0;mso-tstyle-colband-size:0;mso-style-noshow:yes;mso-style-priority:99;mso-style-parent:"";mso-padding-alt:0cm 5.4pt 0cm 5.4pt;mso-para-margin:0cm;mso-para-margin-bottom:.0001pt;mso-pagination:none;font-size:11.0pt;font-family:"Calibri",sans-serif;mso-ascii-font-family:Calibri;mso-ascii-theme-font:minor-latin;mso-hansi-font-family:Calibri;mso-hansi-theme-font:minor-latin;mso-ansi-language:EN-US;mso-fareast-language:EN-US;}Co-registration of point clouds of partially scannedobjects is the first step of the 3D modeling workflow. The aim ofco-registration is to merge the overlapping point clouds by estimating thespatial transformation parameters. In computer vision and photogrammetry domainone of the most popular methods is the ICP (Iterative Closest Point) algorithmand its variants. There exist the 3D Least Squares (LS) matching methods aswell (Gruen and Akca, 2005). Theco-registration methods commonly use the least squares (LS) estimation methodin which the unknown transformation parameters of the (floating) search surfaceis functionally related to the observation of the (fixed) template surface.Here, the stochastic properties of the search surfaces are usually omitted.This omission is expected to be minor and does not disturb the solution vectorsignificantly. However, the a posteriori covariance matrix will be affected bythe neglected uncertainty of the function values of the search surface. Thiscauses deterioration in the realistic precision estimates. In order to overcomethis limitation, we propose a method where the stochastic properties of boththe observations and the parameters are considered under an errors-in-variables(EIV) model. The experiments have been carried out using diverse laser scanningdata sets and the results of EIV with the ICP and the conventional LS matchingmethods have been compared.
关键词：Laser scanning; Point Cloud; Registration; Matching
