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pretty_name: SHREC 2021 Track Database for Quantifying Shape Complexity
Dataset Card for SHREC 2021 Track Database
The SHREC 2021 Track on Quantifying Shape Complexity aimed to provide a benchmark for the quantification of 3D shape complexity. Shape complexity is an ill-defined concept. Hence, the concept is explored complexity multiple tasks and data collections. Due to the relative nature of complexity, a linear order may not make sense. There may be multiple aspects of complexity that can be measured.
- In the first collection, we consider synthetically acquired noisy cubes and spheres.
- The second collection consists of abstract shapes and is made up of two subcollections each composed of 25 shapes.
- The third part consists of the categorized shapes of the Princeton Segmentation Benchmark (Chen et al., "A Benchmark for 3D Mesh Segmentation", TOG, 28.3, 2009). Collection 3 can be accessed at here.
Each of these collections can be considered as seeking a different aspect of shape complexity.
Dataset Structure
All datasets consist of zipped OBJ 3D mesh files.
Dataset Creation
The data in collections 1 and 2 was created by the organizers of the SHREC 2021 track on Quantifying Shape Complexity:
- M. Ferhat Arslan - Middle East Technical University, Department of Computer Engineering
- Alexandros Haridis - Massachusetts Institute of Technology, Department of Architecture
- Paul L. Rosin - Cardiff University, School of Computer Science & Informatics
- Sibel Tari - Middle East Technical University, Department of Computer Engineering
Citation
BibTeX:
@article{arslan2022shrec,
title={SHREC’21: Quantifying shape complexity},
author={Arslan, Mazlum Ferhat and Haridis, Alexandros and Rosin, Paul L and Tari, Sibel and Brassey, Charlotte and Gardiner, James D and Genctav, Asli and Genctav, Murat},
journal={Computers \& Graphics},
volume={102},
pages={144--153},
year={2022},
}
Dataset Card Contact
Paul Rosin
Cardiff University
[email protected]