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: [email protected]

Last updated: 22 Jan 2018.

0. Libraries

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/).

1. Installation Instructions

• Uncompress the package.
• Install GCO library.
  • Go to gco-v3.0/matlab directory.
  • Run GCO_UnitTest.m. The mex file should be compiled automatically. For more information, please see readme.txt file under gco-v3.0/matlab directory.
• Run make.m file.

2. Run evaluation

• Run homo_eval.m to test the method using AdelaideRMF dataset.
• Run funda_eval.m to test the method using AdelaideRMF dataset.

Note: We have tested the code under Ubuntu 16.04 and Matlab R2017a.