Open AccessPOINT CLOUD REGISTRATION AND ACCURACY FOR 3D MODELLING - A REVIEW
Author(s) -
Ahmad Firdaus Razali,
Mohd Farid Mohd Ariff,
Zulkepli Majid
Publication year - 2021
Publication title -
journal of information system and technology management
Language(s) - English
Resource type - Journals
ISSN - 0128-1666
DOI - 10.35631/jistm.624014
Subject(s) - point cloud , photogrammetry , iterative closest point , laser scanning , remote sensing , computer science , lidar , visualization , point (geometry) , computer vision , matching (statistics) , artificial intelligence , geology , laser , optics , geometry , mathematics , statistics , physics
Geoinformation is a surveying and mapping field where topography and details on the ground are spatially mapped. The point cloud is one of the data types that is used for measurement and visualisation of Earth features mapping. Point cloud could come from a different source such as terrestrial laser scanned or photogrammetry. The concepts of terrestrial laser scanning and photogrammetry surveying are elaborated in this paper. This paper also presents the method used for point cloud registration; Iterative Closest Point (ICP) and Feature Extraction and Matching (FEM) and the accuracy of laser scanned, and photogrammetric point cloud based on the previous experiments. Experimental analysis conducted in the previous study shows an impressive result on laser scanned point cloud with very mínimum errors compared to photogrammetric point cloud.