Minimal Solution for Uncalibrated Absolute Pose Problem with a Known Vanishing Point

We present a novel minimal solution for the uncalibrated absolute pose problem given one vanishing point. The proposed method complements state-of-the-art minimal absolute pose solvers and contributes to the handling camera localization problem in poor textured indoor environments. Those environments almost always exhibit edges aligned with the gravity direction which can be detected in images as a vanishing point. The vanishing point with suitable parametrization of the unknowns allows to cast the problem as a Quartic Eigenvalue Problem, a type of nonlinear problem for which very effective solvers exist. The proposed solution yields a reduction in one of the point correspondences which are required by PnP algorithms. In comparison to the general four point PnP algorithms, our method is numerically more stable and more robust to noise. This is demonstrated on a variety of synthetic and real data in scope of calibrating surveillance and mobile phone cameras.