Comparison of the Selected State-Of-The-Art 3D Indoor Scanning and Point Cloud Generation Methods

Research output: Contribution to journalArticleScientificpeer-review

Researchers

Research units

  • University of Würzburg
  • Finnish Geospatial Research Institute

Abstract

Accurate three-dimensional (3D) data from indoor spaces are of high importance for various applications in construction, indoor navigation and real estate management. Mobile scanning techniques are offering an efficient way to produce point clouds, but with a lower accuracy than the traditional terrestrial laser scanning (TLS). In this paper, we first tackle the problem of how the quality of a point cloud should be rigorously evaluated. Previous evaluations typically operate on some point cloud subset, using a manually-given length scale, which would perhaps describe the ranging precision or the properties of the environment. Instead, the metrics that we propose perform the quality evaluation to the full point cloud and over all of the length scales, revealing the method precision along with some possible problems related to the point clouds, such as outliers, over-completeness and misregistration. The proposed methods are used to evaluate the end product point clouds of some of the latest methods. In detail, point clouds are obtained from five commercial indoor mapping systems, Matterport, NavVis, Zebedee, Stencil and Leica Pegasus: Backpack, and three research prototypes, Aalto VILMA, FGI Slammer and the Wurzburg backpack. These are compared against survey-grade TLS point clouds captured from three distinct test sites that each have different properties. Based on the presented experimental findings, we discuss the properties of the proposed metrics and the strengths and weaknesses of the above mapping systems and then suggest directions for future research.

Details

Original languageEnglish
Article number796
Number of pages26
JournalRemote Sensing
Volume9
Issue number8
Publication statusPublished - Aug 2017
MoE publication typeA1 Journal article-refereed

    Research areas

  • point cloud, indoor, mobile laser scanning, MLS, metric, 3D scanning, mobile mapping, SLAM, review, comparison, MOBILE LASER SCANNER, LOCALIZATION, RECONSTRUCTION, EXTRACTION

Download statistics

No data available

ID: 15120579