Guided Modeling of Natural Scenarios: Vegetation and Terrain
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Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
The generation of realistic natural scenarios is a longstanding and ongoing challenge in Computer Graphics. LiDAR (Laser Imaging Detection and Ranging) point clouds have been gaining interest for the representation and analysis of real-world scenarios. However, the output of these sensors is conditioned by several parameters, including, but not limited to, distance to scanning target, aperture angle, number of laser beams, as well as systematic and random errors for the acquisition process. Hence, LiDAR point clouds may present inaccuracies and low density, thus hardening their visualization. In this work, we propose reconstructing the surveyed environments to enhance the point cloud density and provide a 3D representation of the scenario. To this end, ground and vegetation layers are detected and parameterized to allow their reconstruction. As a result, point clouds of any required density can be modeled, as well as 3D realistic natural scenarios that may lead to procedural generation through their parameterization.
Description
CCS Concepts: Computing methodologies --> Point-based models; Modeling methodologies
@inproceedings{10.2312:ceig.20221144,
booktitle = {Spanish Computer Graphics Conference (CEIG)},
editor = {Posada, Jorge and Serrano, Ana},
title = {{Guided Modeling of Natural Scenarios: Vegetation and Terrain}},
author = {Collado, José Antonio and López, Alfonso and Pérez, Juan Roberto Jiménez and Ortega, Lidia M. and Jurado, Juan M. and Feito, Francisco},
year = {2022},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-186-1},
DOI = {10.2312/ceig.20221144}
}