TreeSpecies-PC2DT: Automated Tree Species Modeling from Point Clouds to Digital Twins

Like Gobeawan, Xuan Liu, Chi Lim, Venugopalan Raghavan, Joyjit Chattoraj, Jan Schindler, Feng Yang

2024

Abstract

3D digital twin trees for a city-scale have been limited to low-resolution, static shape models due to challenges in automation/scalability, cost performance, tree growth dynamics, species complexities and compatibilities with simulations and virtual city platforms. To address those challenges for high-resolution tree models, we propose an automated workflow of generating large-scale, lightweight, dynamic digital-twin tree species models from point cloud data. Species digital twins are modelled as detailed hierarchical branch structures by solving for all species profile parameters through stages of branch reconstruction from point cloud data, species profiling by machine learning, tropism transfer, optimisation and species growth modelling based on botany and limited field survey. We show that the generated high-resolution tree models can be lightweight while representing their true species characteristics and dynamic botanical architecture (branching patterns and growth processes).

Paper Citation

in Harvard Style

Gobeawan L., Liu X., Lim C., Raghavan V., Chattoraj J., Schindler J. and Yang F. (2024). TreeSpecies-PC2DT: Automated Tree Species Modeling from Point Clouds to Digital Twins. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP; ISBN 978-989-758-679-8, SciTePress, pages 81-91. DOI: 10.5220/0012389700003660

in Bibtex Style

@conference{grapp24,
author={Like Gobeawan and Xuan Liu and Chi Lim and Venugopalan Raghavan and Joyjit Chattoraj and Jan Schindler and Feng Yang},
title={TreeSpecies-PC2DT: Automated Tree Species Modeling from Point Clouds to Digital Twins},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP},
year={2024},
pages={81-91},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012389700003660},
isbn={978-989-758-679-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP
TI - TreeSpecies-PC2DT: Automated Tree Species Modeling from Point Clouds to Digital Twins
SN - 978-989-758-679-8
AU - Gobeawan L.
AU - Liu X.
AU - Lim C.
AU - Raghavan V.
AU - Chattoraj J.
AU - Schindler J.
AU - Yang F.
PY - 2024
SP - 81
EP - 91
DO - 10.5220/0012389700003660
PB - SciTePress