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Author Dez, Yago ♦ Roure, Ferran ♦ Llad, Xavier ♦ Salvi, Joaquim
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2015
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword 3D registration ♦ Coarse matching ♦ Computational geometry ♦ Point cloud matching ♦ Point descriptors ♦ Surface alignment
Abstract 3D registration or matching is a crucial step in 3D model reconstruction. Registration applications span along a variety of research fields, including computational geometry, computer vision, and geometric modeling. This variety of applications produces many diverse approaches to the problem but at the same time yields divergent notations and a lack of standardized algorithms and guidelines to classify existing methods. In this article, we review the state of the art of the 3D rigid registration topic (focused on Coarse Matching) and offer qualitative comparison between the most relevant approaches. Furthermore, we propose a pipeline to classify the existing methods and define a standard formal notation, offering a global point of view of the literature. Our discussion, based on the results presented in the analyzed papers, shows how, although certain aspects of the registration process still need to be tested further in real application situations, the registration pipeline as a whole has progressed steadily. As a result of this progress in all registration aspects, it is now possible to put together algorithms that are able to tackle new and challenging problems with unprecedented data sizes and meeting strict precision criteria.
ISSN 03600300
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-02-01
Publisher Place New York
e-ISSN 15577341
Journal ACM Computing Surveys (CSUR)
Volume Number 47
Issue Number 3
Page Count 36
Starting Page 1
Ending Page 36


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Source: ACM Digital Library