Comparison of material models in modern physically based rendering pipelines
Abstract
The appearance of materials results from a complex interaction of light, material properties and the geometric shape of an object. In computer graphics, various models were developed to describe these correlations. Modern rendering pipelines commonly adapt the philosophy of physically based rendering. This study examines if the reproduction of materials differs across modern physically based rendering tools, and compares the intuitiveness of material design, the quality and range of reproducible materials. A sequential rendering framework was developed to evaluate the visual influences of four selected parameters on material appearance. The rendered images are qualitatively compared based on material charts, scanline plots and difference images. The examined rendering tools mostly yield similar results, with the main differences caused by disparate rendering methods. Still, subtle variations between the tools are noticable, indicating the individual strengths and flaws of each renderer in terms of intuitiveness and physical accuracy.
Paper
- SKILL conference paper (12 pages, author's version) (.pdf, 15.1 MB)
The published version will be soon available in the proceedings of SKILL.
- full bachelor thesis (.pdf, 2.7 MB)
Supplementary Material
- all figures (.zip, 285 MB)
- Jupyter notebooks (.zip, 156 MB)
- source code for rendering framework (.zip, 216 KB)
Jupyter notebooks
The Jupyter notebooks require an installation of Python (last tested with version 3.9) and the Python modules jupyter
, numpy
and matplotlib
. You can install them for example with pip
:
pip install jupyter numpy matplotlib
or create e.g. a Conda environment:
conda create --name pbr_materials python=3.9 jupyter numpy matplotlib
Make sure to extract the zipped (compressed) data. The notebook ZipUnzip.ipynb
can be used to process this step automatically by executing the first code cell.
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