ICP WITH DEPTH COMPENSATION FOR CALIBRATION OF MULTIPLE TOF SENSORS

Abstract

We propose an iterative closest point (ICP) based calibration for time of flight (ToF) multiple depth sensors. For the multiple sensor calibrations, we usually use 2D patterns calibration with IR images. The depth sensor output depends on calibration parameters at a factory; thus, the re-calibration must include gaps from the calibration in the factory. Therefore, we use direct correspondences among depth values, and the calibrating extrinsic parameters by using ICP. Usually, simultaneous localization and mapping (SLAM) uses ICP, such as KinectFusion. The case of multiple sensor calibrations, however, is harder than the SLAM case. In this case, the distance between cameras is too far to apply ICP. Therefore, we modify the ICP based calibration for multiple sensors. The proposed method uses specific calibration objects to enforce the matching ability among sensors. Also, we proposed a compensation method for ToF depth map distortions.