A Calibration Method for 3D Point Cloud Acquisition System

Abstract

The invention relates to a calibration method for a three-dimensional point cloud acquisition system, comprising the steps of: establishing a world coordinate system and a local coordinate system; establishing a measurement model of the three-dimensional point cloud acquisition system; selecting calibration objects with geometric constraints, and obtaining the calibration objects The three-dimensional point cloud data of a plurality of measurement points in the local coordinate system; according to the measurement model of the three-dimensional point cloud acquisition system, the geometric constraints and the three-dimensional point cloud data, the parameters of the first model and the three-dimensional point cloud data are established A nonlinear objective function of the second model parameter; using an optimization algorithm to optimize the nonlinear objective function to obtain calibration values ​​of the first model parameter and the second model parameter. The calibration method of the 3D point cloud acquisition system in the embodiment of the present invention solves the problem of calibrating the 3D point cloud acquisition system when the parameters of the calibration object are unknown, and does not need to measure the relevant dimensions of the calibration object, thereby improving the estimation accuracy of the model parameters .

Description

technical field [0001] The invention belongs to the technical field of three-dimensional point cloud data acquisition, and in particular relates to a calibration method for a three-dimensional point cloud acquisition system. Background technique [0002] In the process of digitizing the real world, 3D point cloud data records the geometric properties and position information of the object surface. High-precision 3D point cloud data can provide a lot of help for the application of computer vision in human daily life, so it is of great significance to build a high-precision 3D point cloud acquisition system. [0003] At present, there are various collection systems for the collection of 3D point cloud data, such as a 3D point cloud collection system based on a pan / tilt and a 2D laser scanner, a 3D point cloud collection system based on a pan / tilt and a Kinect sensor, etc. Calibration of these 3D acquisition systems is a prerequisite for obtaining high-precision 3D point cloud...

AI Technical Summary

Problems solved by technology

[0004] However, most of the existing calibration algorithms need to give the relevant dimensions of the calibration object. For example, the calibration algorithm of the pitch laser scanner based on the least square method needs to measure the distance from the center of rotation of the laser scanner to the thin rod; in practice, it is usually difficult to Accurate measurements of the relative dimensions of the calibrator, resulting in less accurate model parameter estimates for existing calibration algorithms

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