WO2025035349A1 - 一种多视角摄像头标定方法、装置、设备及存储介质 - Google Patents

一种多视角摄像头标定方法、装置、设备及存储介质 Download PDF

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Publication number
WO2025035349A1
WO2025035349A1 PCT/CN2023/112859 CN2023112859W WO2025035349A1 WO 2025035349 A1 WO2025035349 A1 WO 2025035349A1 CN 2023112859 W CN2023112859 W CN 2023112859W WO 2025035349 A1 WO2025035349 A1 WO 2025035349A1
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camera
calibration
parameter matrix
extrinsic
cameras
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French (fr)
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陈可
蔚鹏飞
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Shenzhen Institute of Advanced Technology of CAS
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Shenzhen Institute of Advanced Technology of CAS
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration

Definitions

  • the present application belongs to the field of computer vision technology, and in particular, relates to a multi-view camera calibration method, device, equipment and storage medium.
  • Camera calibration is to estimate the relative pose of the camera (i.e., calculate the internal and external parameters of the camera).
  • camera calibration methods mainly include three-dimensional standard object calibration, two-dimensional calibration plate calibration, one-dimensional calibration object calibration, and single-point calibration object calibration.
  • the three-dimensional standard object calibration method has high accuracy, but it is difficult to make and difficult to make and move in large scenes;
  • the two-dimensional calibration plate calibration method also has sufficient accuracy, but in large scenes, it is necessary to make a large flat calibration plate, which is costly and difficult to calibrate horizontally relative cameras;
  • the one-dimensional calibration object calibration method has slightly lower accuracy, low production cost, and is easy to move;
  • the single-point calibration object calibration method is easy to make and easy to move, but can only calibrate external parameters.
  • the patent document with application number CN202010570282.4 discloses the use of a freely movable single calibration point and an L-shaped rigid body for indicating the world coordinate system for camera calibration
  • the patent document with application number CN201310135850.8 discloses the use of mutual distance as a condition for matching the image points of a one-dimensional calibration object by satisfying a constraint relationship of the one-dimensional calibration object.
  • the above calibration has the following disadvantages: only one calibration scheme is used, the accuracy is low, and the BA optimization algorithm is used, the calibration time is long, and the calibration results are not displayed in real time.
  • the present application provides a multi-view camera calibration method, device, equipment and storage medium, aiming to solve at least one of the above-mentioned technical problems in the prior art to a certain extent.
  • a multi-view camera calibration method comprising:
  • the two-dimensional calibration plate marking method is used to obtain the intrinsic parameter data of each camera and obtain the camera intrinsic parameter matrix
  • the single-point calibration object marking method is used to obtain the extrinsic parameter data of each camera and obtain the camera extrinsic parameter matrix;
  • the camera calibration result is displayed according to the camera intrinsic parameter matrix and the camera extrinsic parameter matrix.
  • the technical solution adopted by the embodiment of the present application also includes: the two-dimensional calibration plate marking method is used to obtain the internal reference data of each camera specifically:
  • the data formats of the N two-dimensional calibration plate images are converted, and the converted images are calculated to obtain the intrinsic parameter data of each camera.
  • the technical solution adopted by the embodiment of the present application also includes: the single-point calibration object marking method is used to obtain the external parameter data of each camera, and the camera external parameter matrix is obtained as follows:
  • the camera synchronous acquisition system controls N cameras to synchronously shoot the same single-point calibration object to obtain N single-point calibration object images;
  • the pixel coordinates in each single-point calibration object image are extracted, the mapping between the cameras is calculated according to the pixel coordinates, and the extrinsic parameter matrix between the cameras is calculated according to the mapping between the cameras.
  • the technical solution adopted in the embodiment of the present application also includes: the single-point calibration object is a continuously moving long rod, and a marker that is distinguished from the background is provided at the end of the long rod.
  • the technical solution adopted by the embodiment of the present application also includes: after the single-point calibration object marking method is used to obtain the extrinsic parameter data of each camera and obtain the camera extrinsic parameter matrix, it also includes:
  • the camera extrinsic parameter matrix is iteratively optimized using a reprojection error algorithm combined with a three-dimensional point consistency evaluation algorithm to obtain the optimal camera extrinsic parameter matrix.
  • the technical solution adopted by the embodiment of the present application also includes: the iterative optimization of the camera extrinsic parameter matrix by using the reprojection error algorithm combined with the three-dimensional point consistency evaluation algorithm is specifically as follows:
  • the next round of iterative optimization is performed until the number of iterations reaches the set number and the optimal camera extrinsic parameter matrix is obtained.
  • the technical solution adopted by the embodiment of the present application also includes: after displaying the camera calibration result according to the camera intrinsic parameter matrix and the camera extrinsic parameter matrix, it also includes:
  • a multi-view camera calibration method and device comprising:
  • Intrinsic parameter data acquisition module used to obtain the intrinsic parameter data of each camera using a two-dimensional calibration plate marking method to obtain the camera intrinsic parameter matrix;
  • External parameter data acquisition module used to obtain the external parameter data of each camera using the single-point calibration object marking method to obtain the camera external parameter matrix;
  • Calibration display module used to display the camera calibration result according to the camera intrinsic parameter matrix and the camera extrinsic parameter matrix.
  • a device includes a processor and a memory coupled to the processor, wherein:
  • the memory stores program instructions for implementing the multi-view camera calibration method
  • the processor is used to execute the program instructions stored in the memory to control the multi-view camera calibration method.
  • a storage medium storing program instructions executable by a processor, wherein the program instructions are used to execute the multi-view camera calibration method.
  • the beneficial effects of the embodiments of the present application are as follows: the multi-view camera calibration method, device, equipment and storage medium of the embodiments of the present application use a marking method combining a two-dimensional calibration plate marking method and a single-point calibration object marking method to mark the internal and external parameters of the camera respectively, which can obtain the internal and external parameters completely relative to the camera in a large scene at low cost and quickly, while improving the camera calibration accuracy, making the camera calibration more convenient and labor-saving, and using an external parameter iterative optimization algorithm combining reprojection error and three-dimensional point consistency evaluation to improve the robustness of the camera external parameter optimization.
  • the embodiments of the present application can display the camera calibration results and reprojection errors in real time, which is conducive to the calibration personnel to more intuitively and quickly determine whether the camera is calibrated successfully.
  • FIG1 is a flow chart of a multi-view camera calibration method according to an embodiment of the present application.
  • FIG2 is a schematic diagram of a method for obtaining a camera intrinsic parameter matrix in an embodiment of the present application
  • FIG3 is a schematic diagram of a method for obtaining a camera extrinsic parameter matrix according to an embodiment of the present application
  • FIG4 is a schematic diagram of the structure of a multi-view camera calibration device according to an embodiment of the present application.
  • FIG5 is a schematic diagram of the device structure of an embodiment of the present application.
  • FIG. 6 is a schematic diagram of the structure of a storage medium according to an embodiment of the present application.
  • first”, “second”, “third” in this application are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features.
  • the features defined as “first”, “second”, “third” can expressly or implicitly include at least one of the features.
  • the meaning of “multiple” is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.
  • all directional indications (such as up, down, left, right, front, back%) are only used to explain the relative position relationship, movement, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication also changes accordingly.
  • FIG1 is a flow chart of a multi-view camera calibration method according to an embodiment of the present application.
  • the multi-view camera calibration method according to an embodiment of the present application comprises the following steps:
  • the shooting parameters include but are not limited to the camera shutter speed and frame size.
  • S120 Acquire the intrinsic parameter data of each camera using a two-dimensional calibration plate marking method to obtain a camera intrinsic parameter matrix
  • FIG2 it is a schematic diagram of the camera intrinsic parameter matrix acquisition method in the embodiment of the present application.
  • 101 is a single camera, and the camera does not need to be fixed at this time;
  • 102 is a two-dimensional calibration plate.
  • the camera intrinsic parameter matrix acquisition method is specifically: use the single camera 101 to shoot the two-dimensional calibration plate 102 respectively, and obtain N two-dimensional calibration plate pictures, N is the number of cameras; convert the data format of the N two-dimensional calibration plate pictures, and then use OpenCV or other toolkits to calculate the converted pictures to obtain the intrinsic parameter data of each camera.
  • the two-dimensional calibration plate 102 is a two-dimensional checkerboard calibration plate.
  • the grid points of the two-dimensional checkerboard calibration plate can be set according to the actual application scenario. In the embodiment of the present application, the checkerboard grid points are set to 3*2, and other types of two-dimensional calibration plates can also be used.
  • the camera extrinsic matrix acquisition method includes: fixing N cameras in different directions of the camera fixing frame 201, and the N cameras are connected to the camera synchronization acquisition system 202, and the camera synchronization acquisition system 202 controls all cameras to synchronously shoot the continuously moving single-point calibration object 203, and obtain N single-point calibration object images, and extract the pixel coordinates in each single-point calibration object picture, calculate the mapping between each camera according to the pixel coordinates, and then use OpenCV or other toolkits to calculate the extrinsic matrix between each camera.
  • the camera fixing frame 201 is made of stainless steel or aluminum material, which can provide stable support for the camera;
  • the single-point calibration object 203 is a long rod, and the end of the long rod is provided with a luminous point or other markers that are distinguished from the background, and can also be other types or shapes of markers.
  • the number of cameras N is at least two. In FIG. 3, only four cameras are taken as an example, and the specific number of cameras can be set according to the actual application scenario.
  • S140 Iteratively optimize the camera extrinsic parameter matrix by using a reprojection error algorithm combined with a three-dimensional point consistency evaluation algorithm to obtain an optimal camera extrinsic parameter matrix;
  • the camera extrinsic parameter matrix is iteratively optimized by using the reprojection error algorithm combined with the 3D point consistency evaluation algorithm. Specifically, the average reprojection error of N single-point calibration object images is calculated first, and then the 3D points are reconstructed using the camera extrinsic parameter matrix, and the 3D point variance (i.e., the 3D point consistency evaluation algorithm) is calculated. It is estimated that the average reprojection error and the 3D point variance are both smaller than the previous iteration. If so, the camera parameters are updated, otherwise they are not updated. The next round of optimization is performed iteratively until the number of iterations reaches the set number, and the optimal camera extrinsic parameter matrix is obtained. In the embodiment of the present application, the number of iterations is set to 3-5 rounds, which can be set according to the actual application scenario.
  • the camera calibration results can be displayed in graphical or digital form, which helps the calibrator to more intuitively and quickly determine whether the camera is calibrated successfully.
  • S160 Save the camera intrinsic parameter matrix and the optimal camera extrinsic parameter matrix after the iteration, and delete the camera intrinsic parameter matrix and the camera extrinsic parameter matrix before the iteration;
  • the multi-view camera calibration method of the second embodiment of the present application adopts a marking method combining a two-dimensional calibration plate marking method and a single-point calibration object marking method to mark the internal and external parameters of the camera respectively, which can obtain the internal and external parameters completely relative to the camera in a large scene at low cost and quickly, while improving the camera calibration accuracy, making the camera calibration more convenient and labor-saving, and adopting an external parameter iterative optimization algorithm combining reprojection error and three-dimensional point consistency evaluation to improve the robustness of the camera external parameter optimization.
  • the embodiment of the present application can display the camera calibration results and reprojection errors in real time, which is conducive to the calibration personnel to more intuitively and quickly determine whether the camera is calibrated successfully.
  • FIG4 is a schematic diagram of a multi-view camera calibration method device structure according to an embodiment of the present application.
  • the multi-view camera calibration method device 40 according to the embodiment of the present application includes:
  • the internal parameter data acquisition module 41 is used to acquire the internal parameter data of each camera by using a two-dimensional calibration plate marking method to obtain a camera internal parameter matrix;
  • the external parameter data acquisition module 42 is used to acquire the external parameter data of each camera by using a single-point calibration object marking method to obtain a camera external parameter matrix;
  • Calibration display module 43 used to display the camera according to the camera intrinsic parameter matrix and the camera extrinsic parameter matrix Calibration results.
  • FIG5 is a schematic diagram of the device structure of an embodiment of the present application.
  • the device 50 includes:
  • a memory 51 storing executable program instructions
  • a processor 52 connected to the memory 51;
  • the processor 52 is used to call the executable program instructions stored in the memory 51 and execute the following steps: using a two-dimensional calibration plate marking method to obtain the intrinsic parameter data of each camera to obtain a camera intrinsic parameter matrix; using a single-point calibration object marking method to obtain the extrinsic parameter data of each camera to obtain a camera extrinsic parameter matrix; and displaying the camera calibration result according to the camera intrinsic parameter matrix and the camera extrinsic parameter matrix.
  • the processor 52 may also be referred to as a CPU (Central Processing Unit).
  • the processor 52 may be an integrated circuit chip having signal processing capabilities.
  • the processor 52 may also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
  • DSP digital signal processor
  • ASIC application-specific integrated circuit
  • FPGA field-programmable gate array
  • the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.
  • FIG. 6 is a schematic diagram of the structure of the storage medium of the embodiment of the present application.
  • the storage medium of the embodiment of the present application stores a program instruction 61 that can implement the following steps: using a two-dimensional calibration plate marking method to obtain the intrinsic parameter data of each camera to obtain a camera intrinsic parameter matrix; using a single-point calibration object marking method to obtain the extrinsic parameter data of each camera to obtain a camera extrinsic parameter matrix; displaying the camera calibration result according to the camera intrinsic parameter matrix and the camera extrinsic parameter matrix.
  • the program instruction 61 can be stored in the above-mentioned storage medium in the form of a software product, including a number of instructions to enable a device (which can be a personal computer, a server, or a network device, etc.) or a processor (processor) to execute all or part of the steps of each implementation method of the present application.
  • the aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program instructions, or terminal devices such as computers, servers, mobile phones, tablets, etc.
  • the server can be an independent server or a server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, etc.
  • Cloud servers that provide basic cloud computing services such as cloud services, security services, content delivery network (CDN), and big data and artificial intelligence platforms.
  • each functional unit in each embodiment of the present application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.
  • the above integrated unit can be implemented in the form of hardware or in the form of software functional units. The above is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made by using the description and drawings of this application, or directly or indirectly used in other related technical fields, is also included in the patent protection scope of the present application.

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Abstract

本申请涉及一种多视角摄像头标定方法、装置、设备以及存储介质。所述方法包括：采用二维标定板标记法获取各个相机的内参数据，得到相机内参矩阵；采用单点标定物标记法获取各个相机的外参数据，得到相机外参矩阵；根据所述相机内参矩阵和相机外参矩阵显示相机标定结果。本申请实施例采用二维标定板标记法和单点标定物标记法相结合的标记方法分别对相机进行内外参标记，能够低成本且快速地获取大场景下完全相对相机的内外参数，在提高相机标定精度的同时，使得相机标定更加方便、省力。

Description

一种多视角摄像头标定方法、装置、设备及存储介质 技术领域
本申请属于计算机视觉技术领域，特别涉及一种多视角摄像头标定方法、装置、设备以及存储介质。
背景技术
相机标定就是进行相机的相对位姿估计(即计算相机的内外参)。现有技术中，相机标定方法主要包括三维标准物体标定、二维标定板标定、一维标定物标定以及单点标定物标定等，其中，三维标准物体标定方法的精度较高，但制作困难，在大场景下难以制作和移动；二维标定板标定方法同样精度足够，但在大场景下需要制作很大的平面标定板，成本高，且难以标定水平相对的摄像头；一维标定物标定方法的精度略低，且制作成本低，容易移动；单点标定物标定方法制作容易，移动方便，但只能标定外参。
例如，在申请号为CN202010570282.4的专利文献中公开了采用自由移动的单个标定点以及用于指示世界坐标系的L型刚体进行相机标定，申请号为CN201310135850.8的专利文献中公开了以一维标定物满足约束关系使用相互距离作为条件，对一维标定物的图像点进行匹配。上述标定具有如下缺点：只采用一种标定方案，精度较低，且均使用BA优化算法，标定时间长，且没有实时显示标定结果。
发明内容
本申请提供了一种多视角摄像头标定方法、装置、设备以及存储介质，旨在至少在一定程度上解决现有技术中的上述技术问题之一。
为了解决上述问题，本申请提供了如下技术方案：
一种多视角摄像头标定方法，包括：
采用二维标定板标记法获取各个相机的内参数据，得到相机内参矩阵；
采用单点标定物标记法获取各个相机的外参数据，得到相机外参矩阵；
根据所述相机内参矩阵和相机外参矩阵显示相机标定结果。
本申请实施例采取的技术方案还包括：所述采用二维标定板标记法获取各个相机的内参数据具体为：
利用单相机分别拍摄二维标定板，得到N幅二维标定板图片，N为相机数量；
对所述N幅二维标定板图片进行数据格式转换，并对转换后的图片进行计算，得到各个相机的内参数据。
本申请实施例采取的技术方案还包括：所述采用单点标定物标记法获取各个相机的外参数据，得到相机外参矩阵具体为：
将N个相机分别固定在相机固定框的不同方向上，所述N个相机分别与相机同步采集系统连接；
通过所述相机同步采集系统控制N个相机分别对同一个单点标定物进行同步拍摄，得到N幅单点标定物图像；
提取每幅单点标定物图片中的像素点坐标，根据所述像素点坐标计算各个相机之间的映射，根据所述相机之间的映射计算得到各个相机之间的外参矩阵。
本申请实施例采取的技术方案还包括：所述单点标定物为一个不断移动的长杆，所述长杆的末端设置有区分于背景的标记物。
本申请实施例采取的技术方案还包括：所述采用单点标定物标记法获取各个相机的外参数据，得到相机外参矩阵之后，还包括：
利用重投影误差算法结合三维点一致性评估算法对所述相机外参矩阵进行迭代优化，得到最优的相机外参矩阵。
本申请实施例采取的技术方案还包括：所述利用重投影误差算法结合三维点一致性评估算法对所述相机外参矩阵进行迭代优化具体为：
计算所述N幅单点标定物图片的平均重投影误差，利用所述相机外参矩阵重建得到三维点，并计算三维点方差；
判断所述平均重投影误差和三维点方差是否均小于上一轮迭代，如果是则更新相机参数，否则不更新；
执行下一轮迭代优化，直到迭代次数达到设定次数，得到最优的相机外参矩阵。
本申请实施例采取的技术方案还包括：所述根据所述相机内参矩阵和相机外参矩阵显示相机标定结果之后，还包括：
保存迭代结束后的相机内参矩阵和相机外参矩阵。
本申请实施例采取的另一技术方案为：一种多视角摄像头标定方法装置，包括：
内参数据获取模块：用于采用二维标定板标记法获取各个相机的内参数据，得到相机内参矩阵；
外参数据获取模块：用于采用单点标定物标记法获取各个相机的外参数据，得到相机外参矩阵；
标定显示模块：用于根据所述相机内参矩阵和相机外参矩阵显示相机标定结果。
本申请实施例采取的又一技术方案为：一种设备，所述设备包括处理器、与所述处理器耦接的存储器，其中，
所述存储器存储有用于实现所述多视角摄像头标定方法的程序指令；
所述处理器用于执行所述存储器存储的所述程序指令以控制多视角摄像头标定方法。
本申请实施例采取的又一技术方案为：一种存储介质，存储有处理器可运行的程序指令，所述程序指令用于执行所述多视角摄像头标定方法。
相对于现有技术，本申请实施例产生的有益效果在于：本申请实施例的多视角摄像头标定方法、装置、设备以及存储介质采用二维标定板标记法和单点标定物标记法相结合的标记方法分别对相机进行内外参标记，能够低成本且快速地获取大场景下完全相对相机的内外参数，在提高相机标定精度的同时，使得相机标定更加方便、省力，并采用重投影误差和三维点一致性评估相结合的外参迭代优化算法，提高了相机外参优化的鲁棒性。同时，本申请实施例可以实时显示相机标定结果和重投影误差，有利于标定人员更加直观快速的判定相机是否标定成功。
附图说明
图1是本申请实施例的多视角摄像头标定方法的流程图；
图2为本申请实施例中的相机内参矩阵获取方法示意图；
图3为本申请实施例的相机外参矩阵获取方法示意图；
图4为本申请实施例的多视角摄像头标定装置结构示意图；
图5为本申请实施例的设备结构示意图；
图6为本申请实施例的存储介质的结构示意图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清 楚、完整地描述，显然，所描述的实施例仅是本申请的一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
本申请中的术语“第一”、“第二”、“第三”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”、“第三”的特征可以明示或者隐含地包括至少一个该特征。本申请的描述中，“多个”的含义是至少两个，例如两个，三个等，除非另有明确具体的限定。本申请实施例中所有方向性指示(诸如上、下、左、右、前、后……)仅用于解释在某一特定姿态(如附图所示)下各部件之间的相对位置关系、运动情况等，如果该特定姿态发生改变时，则该方向性指示也相应地随之改变。此外，术语“包括”和“具有”以及它们任何变形，意图在于覆盖不排他的包含。例如包含了一系列步骤或单元的过程、方法、系统、产品或设备没有限定于已列出的步骤或单元，而是可选地还包括没有列出的步骤或单元，或可选地还包括对于这些过程、方法、产品或设备固有的其它步骤或单元。
在本文中提及“实施例”意味着，结合实施例描述的特定特征、结构或特性可以包含在本申请的至少一个实施例中。在说明书中的各个位置出现该短语并不一定均是指相同的实施例，也不是与其它实施例互斥的独立的或备选的实施例。本领域技术人员显式地和隐式地理解的是，本文所描述的实施例可以与其它实施例相结合。
请参阅图1，是本申请实施例的多视角摄像头标定方法的流程图。本申请实施例的多视角摄像头标定方法包括以下步骤：
S100：初始化所有相机，并设定或读取每个相机的拍摄参数；
本步骤中，拍摄参数包括但不限于相机快门速度以及画幅大小等。
S110：开启所有相机的拍摄功能；
S120：采用二维标定板标记法获取各个相机的内参数据，得到相机内参矩阵；
本步骤中，如图2所示，为本申请实施例中的相机内参矩阵获取方法示意图。其中，101为单相机，此时相机无需固定；102为二维标定板。相机内参矩阵获取方法具体为：利用单相机101分别拍摄二维标定板102，得到N幅二维标定板图片，N为相机数量；对N幅二维标定板图片进行数据格式转换，然后利用OpenCV或其他工具包对转换后的图片进行计算，得到各个相机的内参数据。本申请实施例中，二维标定板102为二维棋盘格标定板，二维棋盘格标定板的格点可根据实际应用场景进行设定，本申请实施例中设定棋盘格格点为3*2，具体也可采用其他类型的二维标定板。
S130：采用单点标定物标记法获取各个相机的外参数据，得到相机外参矩阵；
本步骤中，请参阅图3，为本申请实施例的相机外参矩阵获取方法示意图。具体的，相机外参矩阵获取方式包括：将N个相机分别固定在相机固定框201的不同方向上，且N个相机分别与相机同步采集系统202连接，通过相机同步采集系统202控制所有相机分别对不断移动的单点标定物203进行同步拍摄，得到N幅单点标定物图像，并提取每幅单点标定物图片中的像素点坐标，根据像素点坐标计算各个相机之间的映射，然后利用OpenCV或其他工具包计算得到各个相机之间的外参矩阵。其中，相机固定框201为不锈钢或铝制材料，能够为相机提供稳定的支撑；单点标定物203为一个长杆，长杆的末端设置有发光点或其他区分于背景的标记物，具体也可以是其他类型或形状的标记物。可以理解，相机数量N为至少两个，在图3中，仅以四个相机为例，相机的具体数量可根据实际应用场景进行设定。
S140：利用重投影误差算法结合三维点一致性评估算法对相机外参矩阵进行迭代优化，得到最优的相机外参矩阵；
本步骤中，利用重投影误差算法结合三维点一致性评估算法对相机外参矩阵进行迭代优化具体为：首先计算N幅单点标定物图片的平均重投影误差，然后利用相机外参矩阵重建得到三维点，并计算三维点方差(即三维点一致性评 估)，判断平均重投影误差和三维点方差是否均小于上一轮迭代，如果是则更新相机参数，否则不更新。迭代执行下一轮优化，直到迭代次数达到设定次数，得到最优的相机外参矩阵。本申请实施例中，迭代设定次数为3-5轮最优，具体可根据实际应用场景进行设定。
S150：在每轮迭代结束后，根据相机内参矩阵和相机外参矩阵显示相机标定结果；
本步骤中，在每轮迭代结束后，可通过图形化或数据化等形式显示相机标定结果，有利于标定人员更加直观快速的判定相机是否标定成功。
S160：保存迭代结束后的相机内参矩阵和最优相机外参矩阵，并删除迭代前的相机内参矩阵和相机外参矩阵；
本步骤中，仅保存最优的相机内参矩阵和相机外参矩阵，有利于释放系统资源，减少系统的内存占用。
基于上述，本申请第二实施例的多视角摄像头标定方法采用二维标定板标记法和单点标定物标记法相结合的标记方法分别对相机进行内外参标记，能够低成本且快速地获取大场景下完全相对相机的内外参数，在提高相机标定精度的同时，使得相机标定更加方便、省力，并采用重投影误差和三维点一致性评估相结合的外参迭代优化算法，提高了相机外参优化的鲁棒性。同时，本申请实施例可以实时显示相机标定结果和重投影误差，有利于标定人员更加直观快速的判定相机是否标定成功。
请参阅图4，为本申请实施例的多视角摄像头标定方法装置结构示意图。本申请实施例的多视角摄像头标定方法装置40包括：
内参数据获取模块41：用于采用二维标定板标记法获取各个相机的内参数据，得到相机内参矩阵；
外参数据获取模块42：用于采用单点标定物标记法获取各个相机的外参数据，得到相机外参矩阵；
标定显示模块43：用于根据所述相机内参矩阵和相机外参矩阵显示相机 标定结果。
请参阅图5，为本申请实施例的设备结构示意图。该设备50包括：
存储有可执行程序指令的存储器51；
与存储器51连接的处理器52；
处理器52用于调用存储器51中存储的可执行程序指令并执行以下步骤：采用二维标定板标记法获取各个相机的内参数据，得到相机内参矩阵；采用单点标定物标记法获取各个相机的外参数据，得到相机外参矩阵；根据所述相机内参矩阵和相机外参矩阵显示相机标定结果。
其中，处理器52还可以称为CPU(Central Processing Unit，中央处理单元)。处理器52可能是一种集成电路芯片，具有信号的处理能力。处理器52还可以是通用处理器、数字信号处理器(DSP)、专用集成电路(ASIC)、现成可编程门阵列(FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
请参阅图6，图6为本申请实施例的存储介质的结构示意图。本申请实施例的存储介质存储有能够实现以下步骤的程序指令61：采用二维标定板标记法获取各个相机的内参数据，得到相机内参矩阵；采用单点标定物标记法获取各个相机的外参数据，得到相机外参矩阵；根据所述相机内参矩阵和相机外参矩阵显示相机标定结果。其中，该程序指令61可以以软件产品的形式存储在上述存储介质中，包括若干指令用以使得一台设备(可以是个人计算机，服务器，或者网络设备等)或处理器(processor)执行本申请各个实施方式方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序指令的介质，或者是计算机、服务器、手机、平板等终端设备。其中，服务器可以是独立的服务器，也可以是提供云服务、云数据库、云计算、云函数、云存储、网络服务、云通信、中间件服务、域名服 务、安全服务、内容分发网络(Content Delivery Network，CDN)、以及大数据和人工智能平台等基础云计算服务的云服务器。
在本申请所提供的几个实施例中，应该理解到，所揭露的系统，装置和方法，可以通过其它的方式实现。例如，以上所描述的系统实施例仅仅是示意性的，例如，单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。以上仅为本申请的实施方式，并非因此限制本申请的专利范围，凡是利用本申请说明书及附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本申请的专利保护范围内。

Claims (10)

  1. 一种多视角摄像头标定方法，其特征在于，包括：
    采用二维标定板标记法获取各个相机的内参数据，得到相机内参矩阵；
    采用单点标定物标记法获取各个相机的外参数据，得到相机外参矩阵；
    根据所述相机内参矩阵和相机外参矩阵显示相机标定结果。
  2. 根据权利要求1所述的多视角摄像头标定方法，其特征在于，所述采用二维标定板标记法获取各个相机的内参数据具体为：
    利用单相机分别拍摄二维标定板，得到N幅二维标定板图片，N为相机数量；
    对所述N幅二维标定板图片进行数据格式转换，并对转换后的图片进行计算，得到各个相机的内参数据。
  3. 根据权利要求2所述的多视角摄像头标定方法，其特征在于，所述采用单点标定物标记法获取各个相机的外参数据，得到相机外参矩阵具体为：
    将N个相机分别固定在相机固定框的不同方向上，所述N个相机分别与相机同步采集系统连接；
    通过所述相机同步采集系统控制N个相机分别对同一个单点标定物进行同步拍摄，得到N幅单点标定物图像；
    提取每幅单点标定物图片中的像素点坐标，根据所述像素点坐标计算各个相机之间的映射，根据所述相机之间的映射计算得到各个相机之间的外参矩阵。
  4. 根据权利要求3所述的多视角摄像头标定方法，其特征在于，所述单点标定物为一个不断移动的长杆，所述长杆的末端设置有区分于背景的标记物。
  5. 根据权利要求1至4任一项所述的多视角摄像头标定方法，其特征在于，所述采用单点标定物标记法获取各个相机的外参数据，得到相机外参矩阵之后，还包括：
    利用重投影误差算法结合三维点一致性评估算法对所述相机外参矩阵进行迭代优化，得到最优的相机外参矩阵。
  6. 根据权利要求5所述的多视角摄像头标定方法，其特征在于，所述利用重投影误差算法结合三维点一致性评估算法对所述相机外参矩阵进行迭代优化具体为：
    计算所述N幅单点标定物图片的平均重投影误差，利用所述相机外参矩阵重建得到三维点，并计算三维点方差；
    判断所述平均重投影误差和三维点方差是否均小于上一轮迭代，如果是则更新相机参数，否则不更新；
    执行下一轮迭代优化，直到迭代次数达到设定次数，得到最优的相机外参矩阵。
  7. 根据权利要求6所述的多视角摄像头标定方法，其特征在于，所述根据所述相机内参矩阵和相机外参矩阵显示相机标定结果之后，还包括：
    保存迭代结束后的相机内参矩阵和相机外参矩阵。
  8. 一种多视角摄像头标定方法装置，其特征在于，包括：
    内参数据获取模块：用于采用二维标定板标记法获取各个相机的内参数据，得到相机内参矩阵；
    外参数据获取模块：用于采用单点标定物标记法获取各个相机的外参数据，得到相机外参矩阵；
    标定显示模块：用于根据所述相机内参矩阵和相机外参矩阵显示相机标定结果。
  9. 一种设备，其特征在于，所述设备包括处理器、与所述处理器耦接的存储器，其中，
    所述存储器存储有用于实现权利要求1-7任一项所述的多视角摄像头标定方法的程序指令；
    所述处理器用于执行所述存储器存储的所述程序指令以控制多视角摄像头标定方法。
  10. 一种存储介质，其特征在于，存储有处理器可运行的程序指令，所述程序指令用于执行权利要求1至7任一项所述多视角摄像头标定方法。
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CN115797465A (zh) * 2022-11-30 2023-03-14 杭州一隅千象科技有限公司 适用于多传感摄像头多角度应用时的外参标定方法及应用

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CN108288291A (zh) * 2018-06-07 2018-07-17 北京轻威科技有限责任公司 基于单点标定物的多相机标定
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