
# About

Self Tuning Texture Optimization was developed to try to overcome limitations
in current 2d texture synthesis methods.

For more information on the method, see the paper:

Self Tuning Texture Optimization
Alexandre Kaspar, Boris Neubert, Dani Lischinski, Mark Pauly, Johannes Kopf
EUROGRAPHICS 2015

Page:
http://w-x.ch/pub/self-tuning-texopt

# Dependencies

The project builds upon several dependencies that are
provided in separate folders:
* EdgeMap: code of P. Dollar and C. Zitnick for ”Structured Forests for Fast Edge Detection", ICCV 2013
* ImageMelding: base code of Image Melding (which our method started building upon)
* PatchMatch: our implementation of PatchMatch [Barnes09] with several new parameters and the spatial uniformity term, as well as different voting strategies
* PiotrToolbox: dependency of EdgeMap
* vlfeat: feature library which we use for SIFT descriptors / features computation

Depending on your platform, you may want to build / install the dependencies.

# Running our code

After having taken care of the dependencies, the rest is happening in SelfTuningTexOpt
with bash scripts used to do synthesis of several textures in a batch, with multiple parameters.

The parameters used in the paper are available in:
SelfTuningTexOpt/result_params.dat

You may want to look at the following script:

SelfTuningTexOpt/demo.sh

# License

Released under the MIT License, see the LICENSE file for usage conditions.
