Graphics and Media Lab

Introduction

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:

• RANSAC
• LMedS
• LO-MSAC
• MLESAC
• MSAC
• NAPSAC
• R-RANSAC
• ZHANGSAC

Estimates after 10 iterations	Estimates after 50 iterations

Requirements

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.

Download

Download GML RANSAC Matlab Toolbox v 0.2

Related projects and publications

Projects:

Robust estimation
Image-based modeling and 3D reconstruction
Publications:

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)

The Project team

• Marinichev Kirill
• Gaganov Victor
• Dr. Konushin Anton
• Dr. Vezhnevets Vladimir

Contacts

Please mail all comments, suggestions, problems and contributions:
vision@graphics.cs.msu.ru