On detailed 3D reconstruction of large indoor environments

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In this paper we present techniques for highly detailed 3D reconstruction of extra large indoor environments. We discuss the benefits and drawbacks of low-range, far-range and hybrid sensing and reconstruction approaches. The proposed techniques for low-range and hybrid reconstruction, enabling the reconstruction density of 125 points/cm3 on large 100.000 m3 models, are presented in detail. The techniques tackle the core challenges for the above requirements, such as a multi-modal data fusion (fusion of a LIDAR data with a Kinect data), accurate sensor pose estimation, high-density scanning and depth data noise filtering. Other important aspects for extra large 3D indoor reconstruction are the point cloud decimation and real-time rendering. In this paper, we present a method for planar-based point cloud decimation, allowing for reduction of a point cloud size by 80-95%. Besides this, we introduce a method for online rendering of extra large point clouds enabling real-time visualization of huge cloud spaces in conventional web browsers.

Original languageEnglish
Title of host publicationImage Processing: Algorithms and Systems XIII
EditorsK.O. Egiazarian, S.A. Agaian, A.P. Gotchev
Place of PublicationBellingham
Number of pages10
ISBN (Electronic)9781628414899
Publication statusPublished - 1 Jan 2015
EventImage Processing: Algorithms and Systems XIII - San Francisco, United States
Duration: 7 Apr 20157 Apr 2015

Publication series

NameProceedings of SPIE
ISSN (Electronic)0277-786X


ConferenceImage Processing: Algorithms and Systems XIII
Country/TerritoryUnited States
CitySan Francisco
OtherPart of: 2015 SPIE/IS&T Electronic Imaging Conference
Internet address


  • 3D reconstruction
  • Decimation
  • LIDAR sensing
  • Mapping and tracking
  • Point cloud
  • Real-time
  • Rendering
  • RGB-D sensing
  • Visualization
  • Volumetric processing


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