Range-Image: Incorporating sensor topology for LiDAR point cloud processing - Archive ouverte HAL Access content directly
Journal Articles Photogrammetric engineering and remote sensing Year : 2018

Range-Image: Incorporating sensor topology for LiDAR point cloud processing


This paper proposes a novel methodology for LiDAR point cloud processing that takes advantage of the implicit topology of various LiDAR sensors to derive 2D images from the point cloud while bringing spatial structure to each point. The interest of such a methodology is then proved by addressing the problems of segmentation and disocclusion of mobile objects in 3D LiDAR scenes acquired via street-based Mobile Mapping Systems (MMS). Most of the existing lines of research tackle those problems directly in the 3D space. This work promotes an alternative approach by using this image representation of the 3D point cloud, taking advantage of the fact that the problem of disocclusion has been intensively studied in the 2D image processing community over the past decade. Using the image derived from the sensor data by exploiting the sensor topology, a semi-automatic segmentation procedure based on depth histograms is presented. Then, a variational image inpainting technique is introduced to reconstruct the areas that are occluded by objects. Experiments and validation on real data prove the effectiveness of this methodology both in terms of accuracy and speed.
Fichier principal
Vignette du fichier
asprs_2017_range.pdf (2.45 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01756975 , version 1 (03-04-2018)



Pierre Biasutti, Jean-François Aujol, Mathieu Brédif, Aurélie Bugeau. Range-Image: Incorporating sensor topology for LiDAR point cloud processing. Photogrammetric engineering and remote sensing, 2018, 84 (6), pp.367--375. ⟨10.14358/PERS.84.6.367⟩. ⟨hal-01756975⟩


497 View
1836 Download



Gmail Facebook Twitter LinkedIn More