Multi-class anisotropic blue noise sampling for discrete element pattern generation

1Japan Advanced Institute of Science and Technology

CGI 2016

representative image

Abstract

We present an element placement method for generating patterns containing "discrete elements". By extending various blue noise sampling methods, we propose a visually uniform distribution of multi-class elements. Our method also supports tileable aperiodic distribution. Instead of actual elements, for fast calculation, we use a circular or elliptic disk as a proxy of an element when checking conflicts with nearby elements during the distribution process. The nature of our results is comparable to swatches in books, which shows that our method is capable of generating visually appealing swatches for a set of elements. The user study showed that our method outperformed state-of-the-art discrete element texture synthesis approaches in terms of pattern visual quality.

Results

Distribution Comparison

Comparison of our pattern with a pseudo-random pattern and a swatch in a reference book.

Various Textures

Various Textures.

Comparison with Maya's XGen

Comparison with Maya's XGen. Rendering results of Figurines (4-class). Same amount of objects (=total 176) are distributed inside the blue stage.

Downloads

Links

Acknowledgements

We thank all reviewers for their helpful comments. This work was supported by JSPS KAKENHI Grant number 16K12433.

Bibtex

@article{Kita:CGI2016,
  title = {Multi-class anisotropic blue noise sampling for discrete element pattern generation},
  author = {Kita, Naoki and Miyata, Kazunori},
  year = {2016},
  journal = {The Visual Computer},
  volume = {32},
  number = {6},
  issn = {1432-2315},
  year = {2016},
  pages = {1035--1044},
  url = {https://doi.org/10.1007/s00371-016-1248-6},
  doi = {10.1007/s00371-016-1248-6},
}