A comparison of low-cost sensor systems in automatic cloud-based indoor 3D modeling

Matias Ingman*, Juho Pekka Virtanen, Matti T. Vaaja, Hannu Hyyppä

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

18 Citations (Scopus)
178 Downloads (Pure)


The automated 3D modeling of indoor spaces is a rapidly advancing field, in which recent developments have made the modeling process more accessible to consumers by lowering the cost of instruments and offering a highly automated service for 3D model creation. We compared the performance of three low-cost sensor systems; one RGB-D camera, one low-end terrestrial laser scanner (TLS), and one panoramic camera, using a cloud-based processing service to automatically create mesh models and point clouds, evaluating the accuracy of the results against a reference point cloud from a higher-end TLS. While adequately accurate results could be obtained with all three sensor systems, the TLS performed the best both in terms of reconstructing the overall room geometry and smaller details, with the panoramic camera clearly trailing the other systems and the RGB-D offering a middle ground in terms of both cost and quality. The results demonstrate the attractiveness of fully automatic cloud-based indoor 3D modeling for low-cost sensor systems, with the latter providing better model accuracy and completeness, and with all systems offering a rapid rate of data acquisition through an easy-to-use interface.

Original languageEnglish
Article number2624
Number of pages20
JournalRemote Sensing
Issue number16
Publication statusPublished - Aug 2020
MoE publication typeA1 Journal article-refereed


  • 3D modeling
  • 3D reconstruction
  • Indoor modeling
  • Laser scanning
  • Multi-sensor
  • Panoramic camera
  • RGB-D camera


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