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Data on annotated approximate bilaterally symmetric leaf-off trees based on particle flow simulation and predefined

Štefan Kohek¹, Niko Lukač¹, Damjan Strnad¹

¹Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia.

|January 24, 2022

Summary

This study introduces a dataset of 3D tree models with identified symmetry planes. These models aid in developing and verifying methods for detecting approximate reflectional symmetry in 3D objects.

Keywords:

3D tree modeling Approximate symmetry Symmetry detection Tree synthesis

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Area of Science:

Computer Graphics
Computational Geometry
Biometrics

Background:

3D tree models present geometric complexities challenging applications like compression and symmetry detection.
Accurate 3D representations are crucial for various scientific and engineering fields.

Purpose of the Study:

To introduce a novel dataset of approximately symmetric 3D tree models.
To provide benchmark data for evaluating approximate reflectional symmetry detection algorithms.
To facilitate research in 3D model compression, visualization, and simulation.

Main Methods:

Procedural synthesis of 3D tree models with manually adjusted parameters for bilateral symmetry.
Manual identification and annotation of the predominant symmetry plane for each tree model.
Inclusion of geometric data, synthesis parameters, point clouds, and symmetry scores in the dataset.

Main Results:

A dataset of approximately bilaterally symmetric 3D tree models across various species.
Each model is annotated with its predominant symmetry plane and a bilateral symmetry strength score.
The dataset includes detailed geometric data and synthesis parameters.

Conclusions:

The dataset serves as a valuable resource for verifying approximate reflectional symmetry detection methods.
Generated 3D tree models can be utilized for diverse applications including compression and radiative transfer simulation.