Automatic registration of mobile LiDAR and spherical panoramas

Ruisheng Wang, Frank P. Ferrie, Jane MacFarlane

Abstract: We present an automatic mutual information (MI) registration method for mobile LiDAR and panoramas collected from a driving vehicle. The suitability of MI for registration of aerial LiDAR and aerial oblique images has been demonstrated in [17], under an assumption that minimization of joint entropy (JE) is a sufficient approximation of maximization of MI. In this paper, we show that this assumption is invalid for the ground-level data. The entropy of a LiDAR image can not be regarded as approximately constant for small perturbations. Instead of minimizing the JE, we directly maximize MI to estimate corrections of camera poses. Our method automatically registers mobile LiDAR with spherical panoramas over an approximate 4 kilometer drive, and is the first example we are aware of that tests mutual information registration in large-scale context.