The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLII-2/W17
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W17, 393–398, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W17-393-2019
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W17, 393–398, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W17-393-2019

  29 Nov 2019

29 Nov 2019

INPAINTING OCCLUSION HOLES IN 3D BUILT ENVIRONMENT POINT CLOUDS

P. Väänänen1 and V. Lehtola2 P. Väänänen and V. Lehtola
  • 1Umbra Software Ltd., Helsinki, Finland
  • 2University of Twente, ITC faculty, Enschede, the Netherlands

Keywords: inpainting, point cloud, occlusion, indoor, built environment

Abstract. Point clouds obtained from mobile and terrestrial laser scanning are imperfect as data is typically missing due to occlusions. This problem is often encountered in 3D reconstruction and is especially troublesome for 3D visualization applications. The missing data may be recovered by intensifying the scanning mission, which may be expensive, or to some extent, by computational means. Here, we present an inpainting technique that covers these occlusion holes in 3D built environment point clouds. The proposed technique uses two neural networks with an identical architecture, applied separately for geometry and colors.