Unsupervised intrinsic and extrinsic calibration of a camera-depth sensor couple

Abstract

The availability of affordable depth sensors in conjunction with common RGB cameras (even in the same device, e.g. the Microsoft Kinect) provides robots with a complete and instantaneous representation of both the appearance and the 3D structure of the current surrounding environment. This type of information enables robots to safely navigate, perceive and actively interact with other agents inside the working environment. It is clear that, in order to obtain a reliable and accurate representation, not only the intrinsic parameters of each sensors should be precisely calibrated, but also the extrinsic parameters relating the two sensors should be precisely known. In this paper, we propose a human-friendly and reliable calibration framework, that enables to easily estimate both the intrinsic and extrinsic parameters of a camera-depth sensor couple. Real world experiments using a Kinect show improvements for both the 3D structure estimation and the association tasks.