This repo is similar to the one in https://github.com/freifeld/fastSCSP/, except that the old Python 2 wrapper was replaced with a Python 3 wrapper (the C++ and Matlab wrappers have not been changed) and that a slighly faster parallelization scheme is used in the E step.

This implementation is based on the algorithm from [Freifeld, Li and Fisher, ICIP '15]. See also the project page.

Note that in ICCV 2019 we released a better superpixel method, called Bayesian Adaptive Superpixel Segmentation.

This software is released under the MIT License (included with the software). Note, however, that if you use this code (and/or the results of running it) to support any form of publication (e.g.,a book, a journal paper, a conference paper, a patent application, etc.), then we ask you to cite the following paper:

@incollection{Freifeld:ICIP:2015,
  title={A Fast Method for Inferring High-Quality Simply-Connected Superpixels},
  author={Freifeld, Oren and Li, Yixin and Fisher III, John W},
  booktitle={International Conference on Image Processing},
  year={2015},
}

Please see the original repository: https://github.com/freifeld/fastSCSP/

Batel Steiner (email: [email protected])

Yixin Li (email: [email protected])

Oren Freifeld (email: [email protected])

An early/partial version of this software, using python and CUDA, was written by Oren. It was then completed and improved by Yixin, who also wrote the Matlab and C++ wrappers. In 2019, Batel replaced the Python 2 wrapper with a Python 3 wrapper.