Inpainting occlusion holes in 3d built environment point clouds

P. Väänänen, V. Lehtola

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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.
Original languageEnglish
Title of host publicationThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Subtitle of host publication6th International Workshop LowCost 3D – Sensors, Algorithms, Applications,
EditorsP. Grussenmeyer, A. Murtiyoso, H. Macher, R. Assi
Place of PublicationStrasbourg
PublisherInternational Society for Photogrammetry and Remote Sensing (ISPRS)
Pages393-398
Number of pages6
VolumeXLII-2/W17
DOIs
Publication statusPublished - 29 Nov 2019

Publication series

NameInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
PublisherCopernicus
ISSN (Print)2194-9034

Keywords

  • ITC-GOLD

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    Väänänen, P., & Lehtola, V. (2019). Inpainting occlusion holes in 3d built environment point clouds. In P. Grussenmeyer, A. Murtiyoso, H. Macher, & R. Assi (Eds.), The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences: 6th International Workshop LowCost 3D – Sensors, Algorithms, Applications, (Vol. XLII-2/W17, pp. 393-398). (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences). Strasbourg: International Society for Photogrammetry and Remote Sensing (ISPRS). https://doi.org/10.5194/isprs-archives-XLII-2-W17-393-2019