Ring multi-camera extrinsic parameter calibration method based on cylindrical calibration body

Abstract

The present invention relates to the technical field of camera calibration, and particularly to a method for calibrating the external parameters of a ring of multiple cameras based on a cylindrical calibration body. The method includes: using a cylindrical calibration body as a reference, with multiple Aruco two-dimensional codes distributed on the surface of the cylindrical calibration body; arranging multiple cameras to be calibrated around the cylindrical calibration body, and during the calibration process, all the multiple cameras to be calibrated take pictures of the cylindrical calibration body to ensure that there is at least one complete and clearly visible Aruco two-dimensional code in each camera to be calibrated; after identifying the Aruco two-dimensional code, perform pose calculation, and solve the external parameters of the camera according to the coordinates of the identified unique Aruco two-dimensional code and the fixed spatial coordinates of the current Aruco two-dimensional code in the cylindrical calibration body coordinate system. The advantages are as follows: the number of cameras to be measured is not limited, and the placement positions are not limited. After all the cameras take pictures simultaneously, single-shot calibration of multiple cameras can be achieved. The calibration steps are few, effectively improving the calibration efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of camera calibration, and particularly to a method for calibrating the external parameters of a ring-shaped multi-camera based on a cylindrical calibration body. Background Art

[0002] Camera external parameter calibration refers to deriving the camera coordinate system that cannot be directly measured to an external reference and establishing the conversion relationship between the camera coordinate system and the world coordinate system. Camera calibration is crucial for tasks such as 3D reconstruction, visual measurement, and visual navigation. Low-quality camera calibration will produce obvious systematic errors, directly affecting the pose measurement accuracy of the vision system. The external parameters between multiple cameras represent the coordinate conversion relationship between the cameras to be calibrated. Existing external parameter calibration methods mostly use a planar calibration board for calibration, and it is impossible to achieve one-time calibration for multi-camera circular placement.

[0003] The multi-camera calibration method based on a cylindrical calibration body, such as the patent application with the publication date of May 27, 2022, publication number CN114549660A, and invention name "Multi-camera calibration method, device, and equipment based on a cylindrical self-identifying marker", discloses a multi-camera calibration method based on a cylindrical self-identifying marker. However, the calibration method is complex. After shooting the rotating calibration column, multiple shootings are required to complete the calibration. Therefore, there is an urgent need to develop a simpler and more convenient calibration method. Summary of the Invention

[0004] To solve the above problems, the present invention provides a method for calibrating the external parameters of a ring-shaped multi-camera based on a cylindrical calibration body.

[0005] The purpose of the present invention is to provide a method for calibrating the external parameters of a ring-shaped multi-camera based on a cylindrical calibration body, including:

[0006] Using a cylindrical calibration body as a reference, and a plurality of Aruco QR codes are distributed on the surface of the cylindrical calibration body;

[0007] Surrounding the cylindrical calibration body with multiple cameras to be calibrated, and during the calibration process, all the multiple cameras to be calibrated shoot the cylindrical calibration body to ensure that there is at least one complete and clearly visible Aruco QR code in each camera to be calibrated;

[0008] After identifying the Aruco QR code, perform pose calculation, and solve the camera external parameters according to the coordinates of the identified unique Aruco QR code and the fixed spatial coordinates of the current Aruco QR code in the cylindrical calibration body coordinate system.

[0009] Preferably, each Aruco QR code has a unique transformation relationship matrix with the coordinate system of the cylindrical calibration body.

[0010] Preferably, the multiple cameras to be calibrated are arranged in a ring.

[0011] Preferably, the pose calculation uses the PnP algorithm.

[0012] Preferably, during the calibration process, the conversion relationship between the single camera and the cylindrical calibration body The calculation method includes:

[0013] The camera identifies the corners of the Aruco QR code, and the pose of the QR code is obtained through the PnP algorithm. It is calculated in combination with the relationship between the Aruco QR code and the coordinate system of the cylindrical calibration body. The expression is:

[0014]

[0015] In the formula: is the measurement relationship between the camera and the Aruco QR code; is the relationship between the Aruco QR code and the coordinate system of the cylindrical calibration body.

[0016] Preferably, is the design value, and the accuracy is guaranteed by processing.

[0017] Compared with the prior art, the present invention can achieve the following beneficial effects:

[0018] (1) This calibration method uses a cylindrical calibration body. It only needs to ensure that at least one Aruco QR code on the calibration body can be seen by each camera. After all cameras take pictures simultaneously, single-shot multi-camera calibration can be achieved, effectively improving the calibration efficiency.

[0019] (2) The multi-camera calibration method based on the cylindrical calibration body proposed by the present invention has the advantages of unlimited number of cameras, unlimited placement positions, and few calibration steps.

[0020] (3) Each QR code has an independent code, and the pose of each QR code is independent and unique relative to the cylinder. As long as there is a complete QR code in the field of view of each camera, the external parameters between each camera can be obtained by taking a single shot. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is a schematic diagram of the cylindrical calibration body provided by an embodiment of the present invention.

[0022] Figure 2 is a schematic diagram of the distribution of multiple Aruco QR codes on the surface of the cylindrical calibration body provided by an embodiment of the present invention.

[0023] Figure 3 is the coordinate conversion relationship between each camera to be calibrated and the cylindrical calibration body provided by an embodiment of the present invention.

[0024] Figure 4 is a schematic diagram of the external parameter relationship of each camera to be measured provided by an embodiment of the present invention.

[0025] Reference numerals:

[0026] 1. Cylindrical calibration body; 2. Aruco QR code; 3. Camera to be calibrated. Detailed implementation manners

[0027] In the following, embodiments of the present invention will be described with reference to the accompanying drawings. In the following description, the same modules are denoted by the same reference numerals. In the case of the same reference numerals, their names and functions are also the same. Therefore, their detailed descriptions will not be repeated.

[0028] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, rather than limiting the present invention.

[0029] As Figures 1-4 shown, the present invention provides a method for calibrating the external parameters of a ring-shaped multi-camera based on a cylindrical calibration body, and the calibration is completed by using a calibration system composed of a camera to be calibrated and a cylindrical calibration body, including: using the cylindrical calibration body 1 as a reference, and a plurality of Aruco QR codes 2 are distributed on the surface of the cylindrical calibration body 1 ( Figure 2 );

[0030] A plurality of cameras 3 to be calibrated are arranged around the cylindrical calibration body 1 in a ring shape. During the calibration process, each of the plurality of cameras 3 to be calibrated takes pictures of the cylindrical calibration body 1 to ensure that there is at least one complete and clearly visible Aruco QR code 2 in each camera to be calibrated; there is a unique transformation relationship matrix between each Aruco QR code 2 and the coordinate system of the cylindrical calibration body 1

[0031] After identifying the Aruco QR code 2, the PnP algorithm is used for pose calculation, and according to the identified unique coordinates of the Aruco QR code and the fixed spatial coordinates of the current Aruco QR code in the coordinate system of the cylindrical calibration body, the external parameters of the camera are solved.

[0032] Figure 3 shows the coordinate transformation relationship between each camera to be calibrated and the cylindrical calibration body; during the calibration process, the transformation relationship between a single camera and the cylindrical calibration body 1 The calculation method includes:

[0033] The corners of the Aruco QR code 2 are identified by the camera, and the pose of the QR code is obtained by the PnP algorithm, and it is calculated in combination with the relationship between the Aruco QR code 2 and the coordinate system of the cylindrical calibration body 1. The expression is:

[0034]

[0035] In the formula: It is the measurement relationship between the camera and the Aruco QR code, which is obtained by the PnP algorithm; It is the relationship between the Aruco QR code and the coordinate system of the cylindrical calibration body, which is a design value and is ensured by processing.

[0036] Specifically, the relationship between each camera to be calibrated such as Figure 4 shown, the expression is as follows:

[0037]

[0038] The relationship between two cameras to be calibrated is:

[0039]

[0040] In the above formula is solved by the pnp algorithm, is the transformation matrix between the Aruco QR code and the coordinate system of the cylindrical calibration body, which is a design value and is ensured by processing.

[0041] The present invention completes the pose solution by recognizing the Aruco QR code and using the pnp algorithm, and realizes the closed-loop between each coordinate system.

[0042] It should be understood that various forms of the processes shown above can be used, steps can be reordered, added or deleted. For example, the steps recorded in the disclosure of the present invention can be executed in parallel, sequentially or in a different order, as long as the desired results of the technical solution disclosed by the present invention can be achieved, and no limitation is made herein.

[0043] The above specific embodiments do not constitute a limitation to the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for calibrating the external parameters of a ring of multiple cameras based on a cylindrical calibration body, characterized in that, Including: Using a cylindrical calibration body as a reference, with multiple Aruco QR codes distributed on the surface of the cylindrical calibration body; each Aruco QR code has a unique transformation relationship matrix with the coordinate system of the cylindrical calibration body; Surrounding the cylindrical calibration body, multiple cameras to be calibrated are arranged. During the calibration process, all the multiple cameras to be calibrated take pictures of the cylindrical calibration body to ensure that there is at least one complete and clearly visible Aruco QR code in each camera to be calibrated; after all the cameras take pictures simultaneously, single-shot multi-camera calibration can be achieved; After identifying the Aruco QR code, the PnP algorithm is used for pose calculation. According to the identified unique coordinates of the Aruco QR code and the fixed spatial coordinates of the current Aruco QR code in the coordinate system of the cylindrical calibration body, the external parameters of the camera are solved; During the calibration process, the conversion relationship between the single camera and the cylindrical calibration object The calculation method includes: identifying the corners of the Aruco QR code by the camera, obtaining the pose of the QR code through the PnP algorithm, and calculating based on the relationship between the Aruco QR code and the coordinate system of the cylindrical calibration object. The expression is: Wherein: is the measurement relationship between the camera and the Aruco QR code; is the relationship between the Aruco QR code and the coordinate system of the cylindrical calibration body.

2. The ring multi-camera external parameter calibration method based on a cylindrical calibration body according to claim 1, characterized in that: The multiple cameras to be calibrated are arranged in a ring.

3. A method for calibrating the external parameters of a ring of multiple cameras based on a cylindrical calibration body according to claim 2, characterized in that: The said is the design value, and the accuracy is guaranteed by machining.

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