Isolating a Tree’s Skeleton using a 3-Dimensional Reconstruction

Bachelor thesis (2024)

Authors

S. Sahay Electrical Engineering, Mathematics and Computer Science

Contributors

E. Eisemann Computer Graphics and Visualisation - EEMCS (mentor)
P. Kellnhofer Computer Graphics and Visualisation - EEMCS (mentor)
L. Uzolas Computer Graphics and Visualisation - EEMCS (mentor)
Marcel Reinders Pattern Recognition and Bioinformatics - EEMCS (graduation committee member)
M.J.T. Reinders Pattern Recognition and Bioinformatics - EEMCS (graduation committee member)
M. J.T. Reinders Pattern Recognition and Bioinformatics - EEMCS (graduation committee member)
Marcel J.T. Reinders Pattern Recognition and Bioinformatics - EEMCS (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2024 Shashwat Sahay
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Published Date

01-02-2024

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

L-Systems allow for the efficient procedeural generation of trees to be used for rendering in video games and simulations. Currently, however, it is difficult to engineer grammars that mimic the behaviours of real life trees in 3 dimensions. To be able to deduce them, the skeleton of a tree can be used to train a model and generate an L-system for a given tree in particular. The aim of this paper is to provide a pipeline to isolate these skeletons from images of a tree, using Neural Radiance Fields (NeRFs) to reconstruct the tree, and using Laplacian Based Contraction to retrieve the underlying skeleton. We find that this approach leads to 3-dimensional topologies that very closely resemble the given tree.

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