MLESAC: a new robust estimator with application to estimating image geometry by Torr, PHS, Zisserman, A

“…The first is a new robust estimator MLESAC which is a generalization of the RANSAC estimator. It adopts the same sampling strategy as RANSAC to generate putative solutions, but chooses the solution that maximizes the likelihood rather than just the number of inliers. …”

IMPSAC: synthesis of importance sampling and random sample consensus by Torr, PHS, Davidson, C

“…It is shown that the method is superior to previous single resolution RANSAC-style feature matchers.…”

An integrated Bayesian approach to layer extraction from image sequences by Torr, PHS, Szeliski, R, Anandan, P

“…In order to achieve the optimization, a Bayesian version of RANSAC is developed with which to initialize the segmentation. …”

What Could Move? Finding Cars, Pedestrians and Bicyclists in 3D Laser Data by Wang, D, Posner, I, Newman, P, IEEE

“…While our system is agnostic to the specific clustering algorithm deployed we explore the use of a Euclidean Minimum Spanning Tree for an end-to-end segmentation pipeline and devise a RANSAC-based edge selection criterion. © 2012 IEEE.…”

Scalable Active Matching by Handa, A, Chli, M, Strasdat, H, Davison, A, IEEE

“…While these priors are often partially used post-hoc to resolve matching consensus in algorithms like RANSAC, it was recently shown that fully integrating them in an 'Active Matching' (AM) approach permits efficient guided image processing with rigorous decisions guided by Information Theory. …”

Robust detection of degenerate configurations while estimating the fundamental matrix by Torr, PHS, Zisserman, A, Maybank, SJ

“…The method is called PLUNDER-DL and is a generalization of the robust estimator RANSAC.</p> <p>The method is evaluated on many differing pairs of real images. …”

Towards real-time forest inventory using handheld LiDAR by Proudman, A, Ramezani, M, Digumarti, ST, Chebrolu, N, Fallon, M

“…The DBH is estimated online by fitting a cylinder to each tree trunk through a least-squares optimization within a RANSAC loop. We demonstrate our mapping approach operating in two different forests (both ecological and commercial) with the total travel distance spanning several kilometres. …”

Real-time RGB-D camera pose estimation in novel scenes using a relocalisation cascade by Cavallari, T, Golodetz, S, Lord, NA, Valentin, J, Prisacariu, VA, Di Stefano, L, Torr, PHS

“…To achieve this, we make several changes to the original approach: (i) instead of simply accepting the camera pose hypothesis produced by RANSAC without question, we make it possible to score the final few hypotheses it considers using a geometric approach and select the most promising one; (ii) we chain several instantiations of our relocaliser (with different parameter settings) together in a cascade, allowing us to try faster but less accurate relocalisation first, only falling back to slower, more accurate relocalisation as necessary; and (iii) we tune the parameters of our cascade, and the individual relocalisers it contains, to achieve effective overall performance. …”