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Shape Reconstruction from Large Amount of Point Data using Repetitive Domain Decomposition Method  

Yoo, Dong-Jin (대진대학교 컴퓨터응용 기계설계공학과)
Publication Information
Journal of the Korean Society for Precision Engineering / v.23, no.11, 2006 , pp. 93-102 More about this Journal
Abstract
In this study an advanced domain decomposition method is suggested in order to construct surface models from very large amount of points. In this method the spatial domain of interest that is occupied by the input set of points is divided in repetitive manner. First, the space is divided into smaller domains where the problem can be solved independently. Then each subdomain is again divided into much smaller domains where the problem can be solved locally. These local solutions of subdivided domains are blended together to obtain a solution of each subdomain using partition of unity function. Then the solutions of subdomains are merged together in order to construct whole surface model. The suggested methods are conceptually very simple and easy to implement. Since RDDM(Repetitive Domain Decomposition Method) is effective in the computation time and memory consumption, the present study is capable of providing a fast and accurate reconstructions of complex shapes from large amount of point data containing millions of points. The effectiveness and validity of the suggested methods are demonstrated by performing numerical experiments for the various types of point data.
Keywords
Shape reconstruction; Large amount of point data; Repetitive domain decomposition method;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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