CardiffVisualComputing/SHREC2021

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]