Fast and Robust Registration and Calibration of Depth-Only Sensors

The precise registration between multiple depth cameras is a crucial prerequisite for many applications. Previous techniques frequently rely on RGB or IR images and checkerboard targets for feature detection, partly due to the depth data being inherently noisy. This limitation prohibits the usage for use-cases where neither is available. We present a novel registration approach that solely uses depth data for feature detection, making it more universally applicable while still achieving robust and precise results. We propose a combination of a custom 3D registration target a lattice with regularly-spaced holes and a feature detection algorithm that is able to reliably extract the lattice and its features from noisy depth images. CCS Concepts • Computing methodologies → Interest point and salient region detections; Camera calibration;

[1]  Udo Frese,et al.  Accurate Detection and Localization of Checkerboard Corners for Calibration , 2018, BMVC.

[2]  Radu Bogdan Rusu,et al.  3D is here: Point Cloud Library (PCL) , 2011, 2011 IEEE International Conference on Robotics and Automation.

[3]  P. Payeur,et al.  Calibration of a network of Kinect sensors for robotic inspection over a large workspace , 2013, 2013 IEEE Workshop on Robot Vision (WORV).

[4]  Dieter Schmalstieg,et al.  Improving RGB Image Consistency for Depth-Camera based Reconstruction through Image Warping , 2020 .

[5]  Roland Siegwart,et al.  Automatic detection of checkerboards on blurred and distorted images , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[6]  Fan Zhong,et al.  Modeling deviations of rgb-d cameras for accurate depth map and color image registration , 2017, Multimedia Tools and Applications.