This package contains the source code which implements robust geometric model fitting proposed in:
T.T. Pham, T.-J. Chin, J. Yu and D. Suter
The Random Cluster Model for Geometric Model Fitting
In Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Providence, Rhode Island, USA, 2012.
T. T. Pham, T.-J. Chin, J. Yu and D. Suter The Random Cluster Model for Robust Geometric Fitting IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014.
Related papers:
T. T. Pham, T.-J. Chin, K. Schindler and D. Suter, Interacting Geometric Priors for Robust Multi-Model Fitting IEEE Transactions on Image Processing
T. T. Pham, T.-J. Chin, J. Yu and D. Suter Simultaneous Sampling and Multi-Structure Fitting with Adaptive Reversible Jump MCMC In NIPS 2011, Granada, Spain.
Copyright (c) 2012 Trung T. Pham and Tat-Jun Chin School of Computer Science, The University of Adelaide, South Australia The Australian Center for Visual Technologies http://www.cs.adelaide.edu.au/~{trung,tjchin}
If you encounter any issues with the code, please feel free to contact me at: trung.pham@adelaide.edu.au
Last updated: 22 Jan 2018.
This software uses the Multi-label optimization toolbox developed by Olga Veksler and Andrew Delong, which can be downloaded from http://vision.csd.uwo.ca/code/gco-v3.0.zip. We include this toolbox to our package.
This program also makes use of Peter Kovesi and Andrew Zisserman's MATLAB functions for multi-view geometry (http://www.csse.uwa.edu.au/~pk/Research/MatlabFns/ http://www.robots.ox.ac.uk/~vgg/hzbook/code/).
Note: We have tested the code under Ubuntu 16.04 and Matlab R2017a.