A Computational Model for Repeated Pattern Perception using Crystallographic Groups
What do you see when you look at a regularly textured surface? Do you see tiles or do you see structures? This project is developing a computational model for repeated pattern perception that is able to automatically classify a given pattern into one of the 7 frieze groups, one of the 17 wallpaper groups, or one of the 230 space groups. It can also automatically generate a finite set of possible tiles (based on our theoretical proofs). Furthermore, we study repeated patterns under different viewing directions to find out what happens to a periodic pattern when it is deformed by Affine or perspective transformations. We are also exploring texture replacement in real images and texture synthesis.
This project is funded by NSF grant No. IIS-0099597
current staff
past head
- Yanxi Liu
past staff
- Robert Collins
- James Z Wang
past contact
- Yanxi Liu