The problem of parametric model estimation is very important in Computer Vision and many other fields of science. But often it became very complicated, due to presence of noise and a big percentage of outliers. In that case the RANSAC algorithm family can be useful and give a good solution.
So GML RANSAC Matlab Toolbox is a set of MATLAB scripts, implementing RANSAC algorithm family:
|Estimates after 10 iterations||Estimates after 50 iterations|
The toolbox was tested only with MatLab 6.5 and MatLab 7.0-7.1 on Windows platform (as this is the only version of MatLab available to the author), but should work with other version also.
Related projects and publications
Image-based modeling and 3D reconstruction
Anton Konouchine, Victor Gaganov, Vladimir Vezhnevets "AMLESAC: A New Maximum Likelihood Robust Estimator". Graphicon-2005, Novosibirsk,Akademgorodok, 2005. .pdf(419kb)
Anton Konouchine, Kirill Marinichev, Vladimir Vezhnevets "A survey of robust parameter estimation methods based on random sampling." Graphicon-2004, Moscow, Moscow State University, Russia, 2004 .pdf (240kb) (in Russian)
Please mail all comments, suggestions, problems and contributions:
vision [at] graphics [dot] cs [dot] msu [dot] ru