ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume V-2-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 343–350, 2020
https://doi.org/10.5194/isprs-annals-V-2-2020-343-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 343–350, 2020
https://doi.org/10.5194/isprs-annals-V-2-2020-343-2020

  03 Aug 2020

03 Aug 2020

PLANAR POLYGONS DETECTION IN LIDAR SCANS BASED ON SENSOR TOPOLOGY ENHANCED RANSAC

S. A. Guinard1, Z. Mallé1, O. Ennafii1, P. Monasse2, and B. Vallet1 S. A. Guinard et al.
  • 1LASTIG, Université Gustave Eiffel, ENSG, IGN, F-94160 Saint-Mandé, France
  • 2LIGM, École des Ponts, Univ Gustave Eiffel, CNRS, Marne-la-Vallée, France

Keywords: Lidar processing, 3D reconstruction, plane detection, planar polygons extraction

Abstract. Detecting planar structures in point clouds is a very central step of the point cloud processing pipeline as many Lidar scans, in particular in anthropic environments, present such planar structures. Many improvements have been proposed to RANSAC and the Hough transform, the two major types of plane detection methods. An important limitation however is that these methods detect planes running across the whole scene instead of more localized planar patches. Moreover, they do not exploit the sensor information that often comes with Lidar point cloud (sensor topology and optical center position in particular). In this paper we address both issues: we aim at detecting planar polygons that have a limited spatial extent, and we exploit sensor topology. The latter is used to enhance a RANSAC framework on two aspects: to make seed points selection more local and to define more compact sets of inliers through sensor space region growing.