CALIBRATION OF 3D SCANNING SYSTEMS

1 . A method comprising:

placing a calibration target having a plurality of spheres in a scan volume of a 3D scanning system;

capturing images of the calibration target using the 3D scanning system;

determining image pixel correspondences of the captured images; and

calibrating the 3D scanning system using the image pixel correspondences.

2 . A method as claimed in claim 1 , wherein calibrating the 3D scanning system using the image pixel correspondences comprises:

constructing surface points of the spheres using the image pixel correspondences and camera models;

solving an error function based on the constructed surface points; and

adjusting parameters of the camera models to reduce the error function.

3 . A method as claimed in claim 2 , wherein each sphere has a known radius, and solving the error function comprises determining, for surface points of each sphere, a difference error between the estimated radius at a surface point and the known radius.

4 . A method as claimed in claim 1 , wherein the method comprises:

placing a further calibration target having a plurality of two-dimensional markers in the scan volume;

capturing images of the further calibration target using the 3D scanning system;

determining positions of the markers in the captured images; and

calibrating the 3D scanning system using the determined positions of the markers.

5 . A method as claimed in claim 4 , wherein calibrating the 3D scanning system comprises:

determining parameters of camera models using the determined positions of the markers; and

refining the parameters using the determined image pixel correspondences.

6 . A method as claimed in claim 5 , wherein refining the parameters comprises adjusting the parameters within constraints.

7 . A method as claimed in claim 1 , wherein the calibration target comprises at least three spheres.

8 . A method as claimed in claim 1 , wherein the calibration target comprises at least four spheres, three of the spheres lie in a common plane, and at least a fourth sphere lies outside the common plane.

9 . A method comprising:

receiving image data from cameras of a 3D scanning system, the image data comprising views of a calibration target having a plurality of spheres in a scan volume;

determining from the image data image pixel correspondences; and

refining parameters of camera models of the 3D scanning system using the determined image pixel correspondences.

10 . A method as claimed in claim 9 , wherein refining the parameters comprises:

constructing surface points of the spheres using the image pixel correspondences and the camera models;

solving an error function based on the constructed surface points; and

adjusting parameters of the camera models to reduce the error function.

11 . A method as claimed in claim 10 , wherein each sphere has a known radius, and solving the error function comprises determining, for surface points of each sphere, a difference error between the estimated radius at a surface point and the known radius.

12 . A method as claimed in claim 9 , wherein the method comprises:

receiving further image data from the cameras, the further image data comprising views of a further calibration target having a plurality of two-dimensional markers in the scan volume;

determining from the further image data positions of the markers;

determining parameters of the camera models using the determined positions of the markers; and

refining the parameters using the determined image pixel correspondences.

13 . A method as claimed in claim 10 , wherein refining the parameters comprises adjusting the parameters within constraints.

14 . A method as claimed in claim 9 , wherein the calibration target comprises at least three spheres.

15 . A non-transitory storage medium storing machine-readable instructions that, when executed by a processor of a computing device, cause the computing device to:

receive image data of a calibration target having a plurality of spheres in a scan volume;

determine from the image data image pixel correspondences; and

refine parameters of camera models using the determined image pixel correspondences.