Non-overlapping field-of-view camera gesture calibration method based on point cloud feature map registration

Abstract

The invention discloses a non-overlapping field-of-view camera gesture calibration method based on point cloud feature map registration. The method comprises the following steps that: (1) carrying outbasic calibration on a plurality of cameras of a non-overlapping field of view to obtain an internal reference; (2) utilizing the plurality of cameras to carry out environment detection and synchronous positioning and mapping, constructing a point cloud map, and extracting a key frame to solve the pose matrix of the camera; (3) extracting an image frame from the key frame of one camera, carryingout similarity detection on the key frames of other cameras, constructing a matching frame point set and a matching point pair set, and carrying out projection error minimization on the projection ofthe point cloud map point on the image frame and the practical pixel coordinate; and (4) carrying out feature matching on a frame near the matched frame, blending all feature points, carrying out global optimization and iterative solution on a relative pose matrix, selecting a correction parameter according to a practical situation, and carrying out final gesture calibration on the camera. By useof the method, the problems of high calibration work intensity, low work efficiency and low accuracy of a traditional calibration method are solved.

Description

technical field [0001] The invention relates to a camera calibration method in the field of machine vision, in particular to a non-overlapping field of view camera attitude calibration method based on point cloud feature map registration. Background technique [0002] In the image measurement process and machine vision applications, in order to determine the relationship between the three-dimensional geometric position of a certain point on the surface of a space object and its corresponding point in the image, it is necessary to establish a geometric model of the camera imaging. These geometric model parameters are in most conditions It must be obtained through experiments and calculations. The process of solving parameters is camera calibration. Whether it is in image measurement or machine vision applications, the calibration of camera parameters is a very critical link. The accuracy of the calibration results and the stability of the algorithm directly affect the accurac...

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Problems solved by technology

[0004] Technical problem: In view of the problems existing in the prior art, the purpose of the present invention is to provide a feature map registration based on point cloud, which can solve the problems of high intensity calibration work, low work efficiency and low precision of multiple non-overlapping field of view cameras. Calibration method for non-overlapping field-of-view cameras

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