Globally optimal inlier set maximization with unknown rotation and focal length
Identifying inliers and outliers among data is a fundamental problem for model estimation. This paper considers models composed of rotation and focal length, which typically occurs in the context of panoramic imaging. An efficient approach consists in computing the underlying model such that the number of inliers is maximized. The most popular tool for inlier set maximization must be RANSAC and its numerous variants. While they can provide interesting results, they are not guaranteed to return...[Show more]
|Collections||ANU Research Publications|
|Source:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|01_Bazin_Globally_optimal_inlier_set_2014.pdf||460.43 kB||Adobe PDF||Request a copy|
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.