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Author Hoowko, Elwira ♦ Wojsz, Jerzy ♦ Sitnik, Robert ♦ Karaszewski, Maciej
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2014
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Color features ♦ Automatic merging of directional point clouds ♦ Feature descriptor ♦ Interest points
Abstract In this article, a method of merging point clouds using the modified Harris corner detection algorithm for extracting interest points of textured 3D point clouds is proposed. A new descriptor characterizing point features for identifying corresponding points in datasets is presented. The merging process is based on the Random Sample Consensus (RANSAC) algorithm, which enables calculation of the geometric transformation between point clouds based on a set of interest points that includes incorrect samples, called outliers. The proposed processing path is designed to integrate many directional measurements, which are acquired with a 3D scanner and are represented as unsorted point clouds (x, y, z) with color information (R, G, B). Exemplary measurements shown in this article represent sections of ceiling in the King's Chinese Cabinet of the Museum of King Jan III's Palace at Wilanow in Warsaw, Poland, as well as some more complex objects. Experimental verification confirms the effectiveness of the proposed method in integrating directional measurements of objects with detailed texture, particularly if they have no unique geometric features.
ISSN 15564673
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2014-06-01
Publisher Place New York
e-ISSN 15564711
Journal Journal on Computing and Cultural Heritage (JOCCH)
Volume Number 7
Issue Number 3
Page Count 21
Starting Page 1
Ending Page 21

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Source: ACM Digital Library