Global Camera Parameterization for Bundle Adjustment

Abstract

Bundle adjustment is an important optimization technique in computer vision. It is a key part of Structure from Motion computation. An important problem in Bundle Adjustment is to choose a proper parameterization of cameras, especially their orientations. In this paper we propose a new parameterization of a perspective camera based on quaternions, with no redundancy in dimensionality and no constraints on the rotations. We conducted extensive experiments comparing this parameterization to four other widely used parameterizations. The proposed parameterization is non-redundant, global, and achieving the same performance in all investigated parameters. It is a viable and practical choice for Bundle Adjustment.