Konferenzband
Real-time camera pose estimation using correspondences with high outlier ratios
Tobias Nöll; Alain Pagani; Didier Stricker (Hrsg.)
International Joint Conference on Computer Vision and Computer Graphics Theory and Applications (VISIGRAPP-2010), The International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, located at VISIGRAPP, May 17-21, Angers, France, Springer, 2010.
Abstract
We present PPnP, an algorithm capable of estimating a robust camera pose in real-time, even if being provided with large sets of correspondences containing high ratios of outliers. For these situations, standard pose estimation algorithms using RANSAC are often unable to provide a solution or at least not in the required time frame. PPnP is provided with a probability distribution function which describes all valid possible camera pose estimates. By checking the correspondences for being compatible with the prior probability, it can be decided effectively at a very early stage, which correspondences can be treated as outliers. This allows a considerably more effective selection of hypothetical inliers than in RANSAC. Although PPnP is based on a technique called BlindPnP which is not intended for real-time computing, a number of changes in PPnP allows to estimate a camera pose with the same high quality as BlindPnP while being considerably faster.