Geometric calibration of a camera and a turntable system using two views.

A calibration algorithm for a system comprising a camera and turntable is provided, in which the camera captures three-dimensional point clouds while a target object rotates on the turntable to three-dimensionally scan the entire object. A mathematical approach is used to obtain the geometry between the coordinate systems of the camera and the turntable. As a minimal setup, the camera captures two views of a chessboard calibration pattern placed on the turntable. The coordinate transformation from the camera to the turntable is then calculated through geometric reasoning. First, two camera poses are computed with respect to the chessboard images taken before and after rotation. The direction of the rotation axis of the turntable coordinate system can be calculated without any ambiguity. However, there is one degree of freedom in the choice of the other two directions and one degree of freedom in choosing the location of the origin of the turntable coordinate system. We provide a practical method for these choices. Experimental results with a stereo-vision system and a turntable validate the proposed method.

[1]  Andriy Myronenko,et al.  Point Set Registration: Coherent Point Drift , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Giorgio Grisetti,et al.  NICP: Dense normal based point cloud registration , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[3]  Jian Zhao,et al.  Accelerated Coherent Point Drift for Automatic Three-Dimensional Point Cloud Registration , 2016, IEEE Geoscience and Remote Sensing Letters.

[4]  Kun Li,et al.  Markerless Shape and Motion Capture From Multiview Video Sequences , 2011, IEEE Transactions on Circuits and Systems for Video Technology.

[5]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Allen R. Tannenbaum,et al.  Point Set Registration via Particle Filtering and Stochastic Dynamics , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.