Accurate and robust spherical camera pose estimation using consistent points

Abstract

This paper addresses the problem of multi-view camera pose estimation of high resolution, full spherical images. A novel approach to simultaneously retrieve camera poses along with a sparse point cloud is designed for large scale scenes. We introduce the concept of consistent points that allows to dynamically select the most reliable 3D points for nonlinear pose refinement. In contrast to classical bundle adjustment approaches, we propose to reduce the parameter search space while jointly optimizing camera poses and scene geometry. Our method notably improves accuracy and robustness of camera pose estimation, as shown by experiments carried out on real image data.