Easy-to-Use and Accurate Calibration of RGB-D Cameras from Spheres

Abstract. RGB-Depth (or RGB-D) cameras are increasingly being adop-ted for real-world applications, especially in areas of healthcare and at-home monitoring. As for any other sensor, and since the manufacturer’s parameters (e.g., focal length) might change between models, calibration is necessary to increase the camera’s sensing accuracy. In this paper, we present a novel RGB-D camera-calibration algorithm that is easy-to-use even for non-expert users at their home; our method can be used for any arrangement of RGB and depth sensors, and only requires that a spherical object (e.g., a basketball) is moved in front of the camera for a few seconds. A robust image-processing pipeline automatically detects the moving sphere and rejects noise and outliers in the image data. A novel closed-form solution is presented to accurately compute an ini-tial set of calibration parameters which are then utilized in a nonlinear minimization stage over all the camera parameters including lens dis-tortion. Extensive simulation and experimental results show the accu-racy and robustness to outliers of our algorithm with respect to exist-ing checkerboard-based methods. Furthermore, an RGB-D Calibration Toolbox for MATLAB is made freely available for the entire research community