Next Article in Journal
Ongoing Conflict Makes Yemen Dark: From the Perspective of Nighttime Light
Previous Article in Journal
Refocusing of Moving Targets in SAR Images via Parametric Sparse Representation
Article Menu
Issue 8 (August) cover image

Export Article

Open AccessArticle
Remote Sens. 2017, 9(8), 796; doi:10.3390/rs9080796

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

Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute FGI, Geodeetinrinne 2, FI-02430 Masala, Finland
Institute of Measuring and Modeling for the Built Environment, Aalto University, P.O. box 15800, 00076 Aalto, Finland
Informatics VII—Robotics and Telematics, Julius Maximilians University Würzburg, 97074 Würzburg, Germany
These authors contributed equally to this work.
Author to whom correspondence should be addressed.
Academic Editors: Jie Shan and Prasad S. Thenkabail
Received: 26 June 2017 / Revised: 17 July 2017 / Accepted: 24 July 2017 / Published: 2 August 2017


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 Würzburg 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. View Full-Text
Keywords: point cloud; indoor; mobile laser scanning; MLS; metric; 3D scanning; mobile mapping; SLAM; review; comparison point cloud; indoor; mobile laser scanning; MLS; metric; 3D scanning; mobile mapping; SLAM; review; comparison

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Lehtola, V.V.; Kaartinen, H.; Nüchter, A.; Kaijaluoto, R.; Kukko, A.; Litkey, P.; Honkavaara, E.; Rosnell, T.; Vaaja, M.T.; Virtanen, J.-P.; Kurkela, M.; El Issaoui, A.; Zhu, L.; Jaakkola, A.; Hyyppä, J. Comparison of the Selected State-Of-The-Art 3D Indoor Scanning and Point Cloud Generation Methods. Remote Sens. 2017, 9, 796.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top