Localization with Time-of-Flight cameras

Abstract: Time-of-Flight (ToF) cameras are becoming an increasingly common sensor in smartphones. These sensors are able to produce depth measurements in a grid at a relatively high rate. Using these depth measurements, point-clouds representing the captured scene can be produced. Previous research has been conducted in using ToF or LIDAR images to localize the camera. In this paper, we investigate several methods to localize the camera using point-clouds and surface meshes. Small alterations were made to some of the algorithms but the concepts remain the same. The main algorithms consisted of ICP variants as well as a relatively recent method called Corrective Gradient Refinement (CGR). The results obtained from generated data indicate that some of the methods are applicable for real-time applications, and the position estimates are comparable to those found in previous results.