Single-shot extrinsic calibration of a generically configured RGB-D camera rig from scene constraints

With the increasing use of commodity RGB-D cameras for computer vision, robotics, mixed and augmented reality and other areas, it is of significant practical interest to calibrate the relative pose between a depth (D) camera and an RGB camera in these types of setups. In this paper, we propose a new single-shot, correspondence-free method to extrinsically calibrate a generically configured RGB-D camera rig. We formulate the extrinsic calibration problem as one of geometric 2D-3D registration which exploits scene constraints to achieve single-shot extrinsic calibration. Our method first reconstructs sparse point clouds from a single-view 2D image. These sparse point clouds are then registered with dense point clouds from the depth camera. Finally, we directly optimize the warping quality by evaluating scene constraints in 3D point clouds. Our single-shot extrinsic calibration method does not require correspondences across multiple color images or across different modalities and it is more flexible than existing methods. The scene constraints can be very simple and we demonstrate that a scene containing three sheets of paper is sufficient to obtain reliable calibration and with a lower geometric error than existing methods.