Modeling and Enhancement of LiDAR Point Clouds from Natural Scenarios

  1. Collado, José Antonio 1
  2. López, Alfonso 1
  3. Jiménez-Pérez, J. Roberto 1
  4. Ortega, Lidia M. 1
  5. Feito, Francisco R. 1
  6. Jurado, Juan Manuel 1
  1. 1 Department of Computer Science, University of Jaén
Actas:
Eurographics 2022

Editorial: The Eurographics Association

ISSN: 1017-4656

ISBN: 978-3-03868-171-7

Año de publicación: 2022

Congreso: EUROGRAPHICS 2022, the 43nd Annual Conference of the European Association for Computer Graphics

Tipo: Aportación congreso

DOI: 10.2312/EGP.20221016 GOOGLE SCHOLAR lock_openAcceso abierto editor

Resumen

The generation of realistic natural scenarios is a longstanding and ongoing challenge in Computer Graphics. A common source of real-environmental scenarios is open point cloud datasets acquired by LiDAR (Laser Imaging Detection and Ranging) devices. However, these data have low density and are not able to provide sufficiently detailed environments. In this study, we propose a method to reconstruct real-world environments based on data acquired from LiDAR devices that overcome this limitation and generate rich environments, including ground and high vegetation. Additionally, our proposal segments the original data to distinguish among different kinds of trees. The results show that the method is capable of generating realistic environments with the chosen density and including specimens of each of the identified tree types.