Multiple video cameras synchronous quick calibration method in three-dimensional scanning system

Abstract

A synchronous quick calibration method of a plurality of video cameras in a three-dimensional scanning system, which includes: (1) setting a regular truncated rectangular pyramid calibration object, setting eight calibration balls at the vertexes of the truncated rectangular pyramid, and respectively setting two reference calibration balls at the upper and lower planes; (2) using the video cameras to pick-up the calibration object, adopting the two-threshold segmentation method to respectively obtain the corresponding circles of the upper and lower planes, extracting centers of the circles, obtaining three groups of corresponding relationships between circle center points in the image and the centres of calibration ball in the space, solving the homography matrix to obtain the internal parameter matrix and external parameter matrix and obtaining the distortion coefficient, taking the solved video camera parameter as the initial values, and then using a non-linear optimization method to obtain the optimum solution of a single video camera parameter; (3) obtaining in sequence the external parameter matrix between a plurality of video cameras and a certain video camera in the space, using the polar curve geometric constraint relationship of the binocular stereo vision to establish an optimizing object function, and then adopting a non-linear optimization method to solve to get the optimum solution of the external parameter matrix between two video cameras.

Description

technical field [0001] The invention relates to the calibration of camera model parameters in a vision system, in particular to a method for synchronously fast calibration of multiple camera parameters based on a three-dimensional calibration object in a three-dimensional scanning system. Background technique [0002] One of the basic tasks of computer vision is to calculate the three-dimensional information of the object in the field of view from the image captured by the camera, so as to reconstruct and recognize the three-dimensional object. The relationship between the three-dimensional geometric information of the object surface point and its corresponding point on the image is determined by the imaging model of the camera. The process of establishing this geometric model is actually the solution process of the camera parameters. Therefore, the calibration of camera parameters is the premise and key of this modeling process. The process of solving the camera parameters...

AI Technical Summary

Problems solved by technology

The disadvantage of this method when applied to the simultaneous rapid calibration of multiple camera parameters is that it requires multiple manual interventions, that is, manually rotate the plane calibration template at a certain angle to shoot multiple images, and the camera can only see the plane at a certain angle Marking points on the template, when the angle between the optical axis of the camera and the plane template is too small, the marking points on it will not be accurately displayed on the camera plane, resulting in the inability to achieve simultaneous and fast calibration of multiple camera parameters

Another common calibration object is the three-dimensional calibration block. The common three-dimensional calibration block is complicated to manufacture and requires high precision, and generally only the surface information of the three planes on the calibration block can be observed.

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