A Novel Method for Extrinsic Calibration of Multiple RGB-D Cameras Using Descriptor-Based Patterns

This paper presents a novel method to estimate the relative poses between RGB-D cameras with minimal overlapping fields of view. This calibration problem is relevant to applications such as indoor 3D mapping and robot navigation that can benefit from a wider field of view using multiple RGB-D cameras. The proposed approach relies on descriptor-based patterns to provide well-matched 2D keypoints in the case of a minimal overlapping field of view between cameras. Integrating the matched 2D keypoints with corresponding depth values, a set of 3D matched keypoints are constructed to calibrate multiple RGB-D cameras. Experiments validated the accuracy and efficiency of the proposed calibration approach.

[1]  Luo Juan,et al.  A comparison of SIFT, PCA-SIFT and SURF , 2009 .

[2]  Marc Pollefeys,et al.  CamOdoCal: Automatic intrinsic and extrinsic calibration of a rig with multiple generic cameras and odometry , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Paul H. J. Kelly,et al.  SLAM++: Simultaneous Localisation and Mapping at the Level of Objects , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[4]  Daniel Cremers,et al.  Direct Sparse Odometry , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Patrick Rives,et al.  Extrinsic Calibration of Multiple RGB-D Cameras From Line Observations , 2018, IEEE Robotics and Automation Letters.

[6]  Patrick Rives,et al.  A dense map building approach from spherical RGBD images , 2014, 2014 International Conference on Computer Vision Theory and Applications (VISAPP).

[7]  Javier González,et al.  Extrinsic calibration of a set of range cameras in 5 seconds without pattern , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[8]  Andrew W. Fitzgibbon,et al.  KinectFusion: Real-time dense surface mapping and tracking , 2011, 2011 10th IEEE International Symposium on Mixed and Augmented Reality.

[9]  Sebastian Zug,et al.  Are laser scanners replaceable by Kinect sensors in robotic applications? , 2012, 2012 IEEE International Symposium on Robotic and Sensors Environments Proceedings.

[10]  Marc Pollefeys,et al.  A multiple-camera system calibration toolbox using a feature descriptor-based calibration pattern , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[11]  Hyun Myung,et al.  Solution to the SLAM Problem in Low Dynamic Environments Using a Pose Graph and an RGB-D Sensor , 2014, Sensors.

[12]  Kurt Konolige,et al.  Sparse Sparse Bundle Adjustment , 2010, BMVC.

[13]  Davide Scaramuzza,et al.  SVO: Fast semi-direct monocular visual odometry , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[14]  Javier González,et al.  Scene structure registration for localization and mapping , 2016, Robotics Auton. Syst..

[15]  Stefan Leutenegger,et al.  ElasticFusion: Real-time dense SLAM and light source estimation , 2016, Int. J. Robotics Res..

[16]  Mao Ye,et al.  Dense Visual SLAM with Probabilistic Surfel Map , 2017, IEEE Transactions on Visualization and Computer Graphics.

[17]  Wolfram Burgard,et al.  3-D Mapping With an RGB-D Camera , 2014, IEEE Transactions on Robotics.

[18]  Wolfram Burgard,et al.  A benchmark for the evaluation of RGB-D SLAM systems , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[19]  Juan D. Tardós,et al.  ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras , 2016, IEEE Transactions on Robotics.

[20]  Andrew J. Davison,et al.  SLAM-based automatic extrinsic calibration of a multi-camera rig , 2011, 2011 IEEE International Conference on Robotics and Automation.

[21]  Hans-Joachim Wünsche,et al.  Odometry-based online extrinsic sensor calibration , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[22]  Patrick Rives,et al.  A compact spherical RGBD keyframe-based representation , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[23]  Seth J. Teller,et al.  Extrinsic Calibration from Per-Sensor Egomotion , 2012, Robotics: Science and Systems.

[24]  Wolfram Burgard,et al.  G2o: A general framework for graph optimization , 2011, 2011 IEEE International Conference on Robotics and Automation.

[25]  Daniel Cremers,et al.  Dense visual SLAM for RGB-D cameras , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[26]  Sander Oude Elberink,et al.  Accuracy and Resolution of Kinect Depth Data for Indoor Mapping Applications , 2012, Sensors.

[27]  Martyna Poreba,et al.  A Robust Linear Feature-Based Procedure for Automated Registration of Point Clouds , 2015, Sensors.