Publication

Very fast solution to the PnP problem with algebraic outlier rejection

Conference Article

Conference

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Edition

2014

Pages

501-508

Doc link

http://dx.doi.org/10.1109/CVPR.2014.71

File

Download the digital copy of the doc pdf document

Abstract

We propose a real-time, robust to outliers and accurate solution to the Perspective-n-Point (PnP) problem. The main advantages of our solution are twofold: first, it integrates the outlier rejection within the pose estimation pipeline with a negligible computational overhead; and second, its scalability to arbitrarily large number of correspondences. Given a set of 3D-to-2D matches, we formulate pose estimation problem as a low-rank homogeneous system where the solution lies on its 1D null space. Outlier correspondences are those rows of the linear system which perturb the null space and are progressively detected by projecting them on an iteratively estimated solution of the null space. Since our outlier removal process is based on an algebraic criterion which does not require computing the full-pose and reprojecting back all 3D points on the image plane at each step, we achieve speed gains of more than 100× compared to RANSAC strategies. An extensive experimental evaluation will show that our solution yields accu- rate results in situations with up to 50% of outliers, and can process more than 1000 correspondences in less than 5ms.

Categories

computer vision, object detection.

Author keywords

3D pose estimation, Perspective-n-point problem, ransac

Scientific reference

L. Ferraz, X. Binefa and F. Moreno-Noguer. Very fast solution to the PnP problem with algebraic outlier rejection, 2014 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2014, Columbus, pp. 501-508.