DARTBOARD BASED GROUND DETECTION ON 3D POINT CLOUD - Mines Paris Accéder directement au contenu
Communication Dans Un Congrès Année : 2022

DARTBOARD BASED GROUND DETECTION ON 3D POINT CLOUD

Résumé

3D laser scanners acquire 3D point clouds of real environments. The process consists in sampling the scene with laser beams rotating around an axis. By construction, the point density decreases with the distance to the scanner. This density heterogeneity is a major issue, in particular for mobile systems in the context of autonomous driving, as usually a single scan is processed simultaneously (instead of mapping applications that can integrate several scans, reducing the density heterogeneity). We propose a dartboard grid with cell size increasing radially in order to adapt the grid size to the point density. The effectiveness of this strategy is demonstrated by means of a ground detection task, a fundamental step in many workflows of analysis of 3D point clouds.
Fichier principal
Vignette du fichier
2022_ISPRS_GroundDetector.pdf (5.54 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04028693 , version 1 (14-03-2023)

Identifiants

  • HAL Id : hal-04028693 , version 1

Citer

Leonardo Gigli, Beatriz Marcotegui, Santiago Velasco-Forero. DARTBOARD BASED GROUND DETECTION ON 3D POINT CLOUD. XXIV ISPRS Congress, Jun 2022, Nice, France. pp.185-192. ⟨hal-04028693⟩
8 Consultations
26 Téléchargements

Partager

Gmail Facebook X LinkedIn More