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A Modified Iterative Closest Point Algorithm for 3D Point Cloud Registration
Author(s) -
Marani Roberto,
Renò Vito,
Nitti Massimiliano,
D'Orazio Tiziana,
Stella Ettore
Publication year - 2016
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/mice.12184
Subject(s) - iterative closest point , point cloud , point (geometry) , computer science , computer vision , enhanced data rates for gsm evolution , algorithm , artificial intelligence , mathematics , geometry
In this article, an accurate method for the registration of point clouds returned by a 3D rangefinder is presented. The method modifies the well‐known iterative closest point (ICP) algorithm by introducing the concept of deletion mask. This term is defined starting from virtual scans of the reconstructed surfaces and using inconsistencies between measurements. In this way, spatial regions of implicit ambiguities, due to edge effects or systematical errors of the rangefinder, are automatically found . Several experiments are performed to compare the proposed method with three ICP variants. Results prove the capability of deletion masks to aid the point cloud registration, lowering the errors of the other ICP variants, regardless the presence of artifacts caused by small changes of the sensor view‐point and changes of the environment.