WO2021022989A1 - 标定参数的获取方法、装置、处理器及电子设备 - Google Patents

标定参数的获取方法、装置、处理器及电子设备 Download PDF

Info

Publication number
WO2021022989A1
WO2021022989A1 PCT/CN2020/102491 CN2020102491W WO2021022989A1 WO 2021022989 A1 WO2021022989 A1 WO 2021022989A1 CN 2020102491 W CN2020102491 W CN 2020102491W WO 2021022989 A1 WO2021022989 A1 WO 2021022989A1
Authority
WO
WIPO (PCT)
Prior art keywords
calibration
camera
image acquisition
preset threshold
error function
Prior art date
Application number
PCT/CN2020/102491
Other languages
English (en)
French (fr)
Inventor
郁理
袁磊
苗旺
王进
Original Assignee
虹软科技股份有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 虹软科技股份有限公司 filed Critical 虹软科技股份有限公司
Priority to JP2022507531A priority Critical patent/JP7387872B2/ja
Priority to KR1020227007689A priority patent/KR20220044572A/ko
Priority to US17/631,475 priority patent/US20220277468A1/en
Publication of WO2021022989A1 publication Critical patent/WO2021022989A1/zh

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/50—Depth or shape recovery
    • G06T7/55—Depth or shape recovery from multiple images
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/46—Colour picture communication systems
    • H04N1/56—Processing of colour picture signals
    • H04N1/60—Colour correction or control
    • H04N1/603—Colour correction or control controlled by characteristics of the picture signal generator or the picture reproducer
    • H04N1/6033—Colour correction or control controlled by characteristics of the picture signal generator or the picture reproducer using test pattern analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/50—Image enhancement or restoration using two or more images, e.g. averaging or subtraction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/387—Composing, repositioning or otherwise geometrically modifying originals
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N17/00—Diagnosis, testing or measuring for television systems or their details
    • H04N17/002—Diagnosis, testing or measuring for television systems or their details for television cameras
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N9/00—Details of colour television systems
    • H04N9/12—Picture reproducers
    • H04N9/31—Projection devices for colour picture display, e.g. using electronic spatial light modulators [ESLM]
    • H04N9/3179—Video signal processing therefor
    • H04N9/3185—Geometric adjustment, e.g. keystone or convergence

Definitions

  • the present invention is based on a Chinese patent application with an application number of 201910727431.0 and an application date of 2019-08-07, and claims the priority of the Chinese patent application.
  • the entire content of the Chinese patent application is incorporated herein by reference.
  • the present invention relates to the field of image processing, and in particular to a method, device, processor and electronic equipment for acquiring calibration parameters.
  • three cameras are simultaneously integrated in mobile terminals (for example, smart phones), showing a booming trend in the market.
  • three cameras can increase the types of cameras.
  • three cameras can include telephoto cameras, wide-angle cameras and ultra-wide-angle cameras at the same time. This combination can achieve multiple zooms and field of view. (Referred to as FOV) will also be greatly improved, which can greatly enrich the user experience.
  • FOV field of view
  • the related technology still has big technical defects for the integrated three-shot calibration.
  • the existing calibration methods mainly include the following two:
  • Method 1 Integrated RGB-D calibration.
  • This method uses an ordinary camera (for example: wide-angle camera) to take a wide-angle camera image and an infrared camera to take an infrared camera image at a certain distance, thereby obtaining the dual-camera image Calibration parameters.
  • this method cannot achieve integrated calibration for multiple cameras. The reason is that the FOV gap of the three cameras is greater.
  • the ultra-wide-angle camera can obtain accurate calibration parameters while shooting an image of the calibration environment at the same distance.
  • Method 2 Integrated dual camera calibration.
  • This method uses two ordinary cameras (for example: a telephoto camera and a wide-angle camera) to take two images at a certain distance, thereby obtaining the calibration parameters of the dual camera.
  • this method is also unable to achieve integrated calibration for multiple cameras. The reason is that the FOV gap of the three cameras is greater, especially when there are both telephoto cameras and ultra-wide-angle cameras. It is difficult to ensure telephoto cameras, wide-angle cameras, and ultra-wide-angle cameras.
  • the wide-angle camera can obtain accurate calibration parameters while shooting an image of the calibration environment at the same distance.
  • the calibration method provided in the related art can only obtain the calibration parameters of the dual camera by taking two images, but cannot obtain the calibration parameters of the three cameras. That is, it is impossible to achieve integrated calibration of the three cameras at the same distance.
  • At least some embodiments of the present invention provide a method, a device, a processor, and an electronic device for acquiring calibration parameters, so as to at least solve the technical problem of the inability to achieve integrated calibration of multiple cameras in the related art.
  • a method for obtaining calibration parameters including:
  • Multiple image acquisition elements are used to shoot the calibration map in the calibration scene to obtain multiple images; the corresponding point sets are obtained from the multiple images, where the point set is the number of three-dimensional points on the surface where the calibration map is shot.
  • Corresponding imaging points in an image acquire calibration parameters to be used for multiple image acquisition elements according to the point set.
  • acquiring the calibration parameters to be used for the multiple image acquisition elements according to the point set includes: determining the initial calibration parameter through the point set; constructing an error function based on the reprojection error obtained from the point set; performing the error function on the error function according to the initial calibration parameters Minimize the processing to get the calibration parameters to be used.
  • determining the initial calibration parameter through the point set includes: judging whether the number of the point set is greater than a first preset threshold; when the number of the point set is determined to be greater than the first preset threshold, the initial calibration parameter is obtained; when the point set is determined When the number is less than or equal to the first preset threshold, the distance between the positions of the multiple image acquisition elements and the calibration map is adjusted until the number of point sets is greater than the first preset threshold.
  • adjusting the distance between the location of the multiple image capture elements and the calibration map includes: adjusting the distance between the location of the multiple image capture elements and the calibration map in the case that multiple image capture elements shoot the calibration map at the same time , So that the proportion of the calibration map in the field of view of each image acquisition element meets the preset conditions.
  • minimizing the error function according to the initial calibration parameters to obtain the calibration parameters to be used includes: minimizing the error function according to the initial calibration parameters to obtain the camera internal matrix and the camera relative matrix; judging the error value of the error function Whether it is less than the second preset threshold; when the error value of the error function is determined to be less than the second preset threshold, the camera internal matrix and the camera relative matrix are determined as the calibration parameters to be used; when the error value of the error function is determined to be greater than or equal to the second When the threshold is preset, the corresponding point sets are obtained from multiple images again until the error value of the error function is less than the second preset threshold.
  • the multiple image capture elements are the same type of image capture elements, or the multiple image capture elements are different types of image capture elements, wherein the types of the multiple image capture elements include at least one of the following: telephoto camera , Wide-angle camera, ultra-wide-angle camera, ultra-telephoto camera, time of flight (TOF) depth camera, RGBD depth camera, structured light depth camera, Mono camera, multi-eye camera, infrared camera.
  • telephoto camera Wide-angle camera
  • ultra-wide-angle camera ultra-telephoto camera
  • time of flight (TOF) depth camera RGBD depth camera
  • structured light depth camera Mono camera
  • multi-eye camera multi-eye camera
  • a device for acquiring calibration parameters including:
  • the shooting module is set to use multiple image acquisition components to shoot the calibration map in the calibration scene to obtain multiple images; the acquisition module is set to acquire corresponding point sets from multiple images, where the point set is the calibration map. Each three-dimensional point on the photographed surface corresponds to the imaging point in the multiple images; the calibration module is configured to obtain the calibration parameters to be used of the multiple image acquisition elements according to the point set.
  • the calibration module includes: a determining unit, which is set to determine initial calibration parameters through a point set; a construction unit, which is set to construct an error function based on the reprojection error obtained from the point set; and a processing unit, which is set to adjust the initial calibration parameters based on the point set.
  • the error function is minimized to obtain the calibration parameters to be used.
  • the determining unit includes: a first determining subunit configured to determine whether the number of point sets is greater than a first preset threshold; and a first processing subunit configured to determine when the number of point sets is greater than the first preset threshold , Obtain the initial calibration parameters; when it is determined that the number of point sets is less than or equal to the first preset threshold, adjust the distance between the positions of the multiple image acquisition elements and the calibration map until the number of point sets is greater than the first preset threshold.
  • the first processing subunit is configured to adjust the distance between the positions of the multiple image acquisition elements and the calibration image in the case that multiple image acquisition elements simultaneously shoot the calibration image, so that the calibration image is displayed in each image.
  • the proportion of the field of view of the collection element meets the preset condition.
  • the processing unit includes: a second processing subunit, configured to minimize the error function according to the initial calibration parameters to obtain the camera internal matrix and the camera relative matrix; the second judging subunit, configured to determine the error of the error function Whether the value is less than the second preset threshold; the third processing subunit is set to determine the camera internal matrix and the camera relative matrix as the calibration parameters to be used when the error value of the error function is determined to be less than the second preset threshold; when the error is determined When the error value of the function is greater than or equal to the second preset threshold, the corresponding point set is obtained from multiple images again until the error value of the error function is less than the second preset threshold.
  • a storage medium in which a computer program is stored, wherein the computer program is set to execute any one of the aforementioned calibration parameter acquisition methods when running.
  • a processor is also provided, the processor is configured to run a program, wherein the method for obtaining calibration parameters of any one of the above is executed when the program is running.
  • an electronic device including a memory and a processor, a computer program is stored in the memory, and the processor is configured to run the computer program to execute any one of the aforementioned calibration parameter acquisition methods.
  • multiple image acquisition elements are used to photograph the calibration map in the calibration scene to obtain multiple images.
  • the corresponding point set is obtained from the multiple images, and the point set is the calibration map.
  • the corresponding imaging points of each three-dimensional point on the photographed surface in multiple images, and the calibration parameters to be used for multiple image acquisition elements are acquired according to the point set, which achieves the integration of multiple image acquisition elements at the same distance.
  • the purpose of calibration is to achieve the technical effect that the calibration parameters obtained through the integrated calibration of multiple cameras can effectively correct the original input image, thereby solving the technology that cannot achieve integrated calibration of multiple cameras in related technologies problem.
  • Fig. 1 is a schematic diagram of an application scenario of a calibration parameter acquisition process according to an optional embodiment of the present invention
  • Fig. 2 is a flowchart of a method for acquiring calibration parameters according to one embodiment of the present invention
  • Fig. 3 is a flowchart of a method for acquiring calibration parameters according to an optional embodiment of the present invention
  • Fig. 4 is a structural block diagram of a device for acquiring calibration parameters according to one embodiment of the present invention.
  • Integrated multi-camera calibration using multiple cameras (usually the number of cameras is greater than or equal to two) in an environment to take an image of the calibration environment at the same time to obtain the calibration parameters, where the calibration parameters include: inside the camera Parameters and relative camera parameters.
  • three cameras for example, including a telephoto camera, a wide-angle camera and an ultra-wide-angle camera at the same time
  • the above-mentioned multiple cameras may be the same type of cameras or different types of cameras. Regardless of whether the types and parameters of the above-mentioned multiple cameras are the same, the solution disclosed in the embodiment of the present invention can be used to achieve calibration of the multiple cameras.
  • the types of multiple cameras may include but are not limited to at least one of the following: telephoto camera, wide-angle camera, ultra-wide-angle camera, ultra-telephoto camera, TOF depth camera, RGBD depth camera, structured light depth camera, Mono camera, multiple Eye camera, infrared camera.
  • Intrinsic parameters of the camera include: the focal length of the camera, principal point coordinates, distortion coefficient and other parameters.
  • the internal matrix of the camera is to fill the intrinsic parameters into the matrix and output as a matrix form, which is essentially another form of representation of the camera's internal parameters.
  • Camera relative parameters include: rotation, translation and other parameters between cameras.
  • the camera-relative matrix fills the extrinsic parameters into the matrix and outputs it as a matrix form, which essentially belongs to another form of representation of camera-relative parameters.
  • Rectify refers to the use of calibration parameters to transform the original input image to the corresponding point on the same horizontal line, where the corresponding point refers to the mutual correspondence formed by the same point in the calibration environment in the three-shot image ⁇ imaging point.
  • an embodiment of a method for obtaining calibration parameters is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions And, although a logical sequence is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than here.
  • the method embodiment can be executed in a mobile terminal, a computer terminal or similar electronic equipment. Take running on a mobile terminal as an example.
  • the mobile terminal may include one or more processors (the processor may include but is not limited to a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processing (DSP) chip, a micro A processor (MCU) or a programmable logic device (FPGA), etc.) and a memory set to store data.
  • the above-mentioned mobile terminal may also include a transmission device and an input/output device configured as a communication function.
  • the mobile terminal may also include more or fewer components than those shown in the foregoing structural description, or have a different configuration from the foregoing structural description.
  • the memory may be configured to store computer programs, for example, software programs and modules of application software, such as the computer programs corresponding to the calibration parameter acquisition method in the embodiment of the present invention, and the processor executes each computer program by running the computer programs stored in the memory. This kind of functional application and data processing is to realize the above-mentioned method of obtaining calibration parameters.
  • the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory.
  • the memory may further include a memory remotely provided with respect to the processor, and these remote memories may be connected to the mobile terminal through a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.
  • the transmission device is set to receive or send data via a network.
  • the foregoing specific examples of the network may include a wireless network provided by a communication provider of a mobile terminal.
  • the transmission device includes a network adapter (Network Interface Controller, referred to as NIC for short), which can be connected to other network devices through a base station to communicate with the Internet.
  • the transmission device may be a radio frequency (Radio Frequency, referred to as RF) module, which is configured to communicate with the Internet in a wireless manner.
  • RF Radio Frequency
  • FIG 1 is a schematic diagram of an application scenario of the calibration parameter acquisition process according to one of the optional embodiments of the present invention.
  • three cameras for example, also include a telephoto camera, a wide-angle camera and an ultra-wide-angle camera
  • the camera is located in the same module and placed at a fixed distance before the calibration chart, so that the module manufacturer can complete the integrated three-camera calibration during the assembly process of the mobile phone module.
  • the present invention does not limit that the three cameras need to be in a module state, and other deployment methods can also be used.
  • the three cameras can be installed on a mobile terminal (such as a smart phone), or the above electronic equipment can be directly used for calibration. It can also be distributed in three different devices (for example: a combination of modules, mobile phones and cameras).
  • FIG. 2 is a flowchart of the method for acquiring calibration parameters according to one of the embodiments of the present invention. As shown in FIG. 2, the process includes The following steps:
  • Step S22 using multiple image acquisition elements to photograph the calibration map in the calibration scene to obtain multiple images
  • Step S24 acquiring corresponding point sets from multiple images, where the point sets are the corresponding imaging points in the multiple images of each three-dimensional point on the surface where the calibration map is shot;
  • Step S26 Acquire calibration parameters to be used for multiple image acquisition elements according to the point set.
  • multiple image acquisition elements can be used to shoot the calibration map in the calibration scene to obtain multiple images.
  • the point set is the captured image of the calibration map.
  • the corresponding imaging points of each three-dimensional point on the surface in multiple images, as well as the calibration parameters to be used for multiple image acquisition elements obtained according to the point set achieve the purpose of achieving integrated calibration of multiple image acquisition elements at the same distance. This achieves the technical effect that the calibration parameters obtained by implementing integrated calibration of multiple cameras can effectively correct the original input image, and further solves the technical problem of the inability to achieve integrated calibration of multiple cameras in the related art.
  • the above-mentioned calibration chart may include a plurality of independent calibration templates, each calibration template is composed of a number of checkerboards containing dots, one of the calibration templates is used as the reference template, and the other calibration templates are The reference template is placed at a predetermined angle in different directions.
  • the calibration chart includes 4 independent calibration templates. Each template is composed of 19*14 checkerboards with dots inside. The calibration template on the upper left is used as the reference template. The other three calibration templates They are placed at an angle of 30 degrees with the reference template in different directions.
  • the circular phase calibration map is usually used instead of the above-mentioned checkerboard.
  • the circular phase It is easier to capture and locate, which helps to achieve integrated calibration of multiple cameras, and the calibration results obtained are more reliable.
  • the images captured by the depth camera and the infrared camera will be dark, it is necessary to perform additional light-filling processing on the captured images to increase the clarity of the image.
  • infrared LED lights of the same waveband can be used to fill light. For example, if the infrared emitter of the device uses 940nm infrared light, then the fill light processing also needs to use 940nm infrared LED lights to fill light.
  • the aforementioned multiple image acquisition elements may be multiple cameras, and the number of the multiple image acquisition elements is greater than or equal to two.
  • step S26 acquiring the calibration parameters to be used of the multiple image acquisition elements according to the point set may include the following execution steps:
  • Step S261 Determine initial calibration parameters through the point set
  • Step S262 construct an error function based on the reprojection error obtained from the point set
  • step S263 the error function is minimized according to the initial calibration parameters to obtain the calibration parameters to be used.
  • three cameras for example, including a telephoto camera, a wide-angle camera and an ultra-wide-angle camera at the same time
  • the three cameras are located in the same module.
  • the module is placed at a fixed distance before the calibration map.
  • control the three cameras to collect images, identify and store the corresponding point set.
  • the same point on the surface where the calibration map is shot in the calibration scene has corresponding imaging points in the images captured by the three cameras, and these corresponding imaging points are mutually corresponding point sets.
  • using these corresponding point sets can determine the initial calibration parameters, that is, the initial values of the camera internal parameters and the camera relative parameters.
  • the imaging point position of the three-dimensional point in the built image acquisition environment in the multiple images actually captured can be called the true value (that is, the observed projection position).
  • the imaging point position of the three-dimensional point calculated according to the calculated calibration parameters and the imaging model can be called a calculated value (that is, the position obtained by projecting the three-dimensional point according to the currently estimated pose), and this calculation process is called reprojection. Therefore, the difference between the calculated value of the imaging point and the true value of the imaging point is the reprojection error.
  • the error function is to construct a mathematical function based on the internal parameters of the camera and the relative parameters of the camera. By calculating the error, it is judged whether the current calibration parameters are optimal; to minimize the error function is to iteratively optimize the calibration parameters to minimize the error. Get the best calibration parameters to be used.
  • determining the initial calibration parameters through the point set may include the following execution steps:
  • Step S2611 judging whether the number of point sets is greater than a first preset threshold
  • Step S2612 when the number of determined point sets is greater than the first preset threshold, obtain the initial calibration parameters; when the number of determined point sets is less than or equal to the first preset threshold, adjust the position of the multiple image acquisition elements and the calibration map Until the number of point sets is greater than the first preset threshold.
  • the initial calibration parameters can be obtained based on the current point set. However, if it can be determined that the number of point sets is less than or equal to the first preset threshold, you first need to adjust the distance between the locations of multiple image acquisition elements and the calibration map, and then re-acquire the corresponding point sets from multiple images , Until the number of point sets is greater than the first preset threshold, so that the initial calibration parameters can be obtained based on the newly acquired point sets.
  • the distance between the positions of the multiple image acquisition elements and the calibration map is adjusted so that the calibration map is in the FOV of each image acquisition element
  • the proportion meets the preset conditions.
  • a preset ratio value can be used as the preset condition. If the proportion of the FOV of each image acquisition element of the calibration map exceeds the preset ratio value, there is no need to continue to adjust the positions and positions of multiple image acquisition elements. The distance between the calibration graphs. If the proportion of the calibration map in the FOV of each image acquisition element fails to reach the preset ratio value, it is still necessary to continue to adjust the distance between the positions of the multiple image acquisition elements and the calibration map.
  • step S263 the error function is minimized according to the initial calibration parameters, and obtaining the calibration parameters to be used may include the following execution steps:
  • step S2631 the error function is minimized according to the initial calibration parameters to obtain the camera internal matrix and the camera relative matrix
  • Step S2632 judging whether the error value of the error function is less than a second preset threshold
  • Step S2633 When it is determined that the error value of the error function is less than the second preset threshold, the camera internal matrix and the camera relative matrix are determined as the calibration parameters to be used; when the error value of the error function is determined to be greater than or equal to the second preset threshold, Re-acquire corresponding point sets from multiple images until the error value of the error function is less than the second preset threshold.
  • the internal matrix of the camera and the relative matrix of the camera are obtained by minimizing the error function.
  • the minimization process it can be determined whether the error value calculated by the error function is less than the second preset threshold. If it is determined that the error value calculated by the error function is less than the preset threshold, it means that the minimization process has been completed. If it is determined that the error value of the error function is greater than or equal to the second preset threshold, it is necessary to obtain the corresponding point set from multiple images again until the error value of the error function is less than the second preset threshold.
  • the camera internal matrix and the camera relative matrix obtained by the minimization process can be determined as the final calibration parameters to be used, without the need for the camera internal matrix and camera Relative matrix for additional processing.
  • Fig. 3 is a flow chart of a method for acquiring calibration parameters according to an alternative embodiment of the present invention. As shown in Fig. 3, the process includes the following steps:
  • Step S302 set up an image acquisition environment, and place a calibration chart
  • Step S304 adjusting the distance between the positions of the multiple image acquisition elements and the calibration map, so that the proportion of the calibration map in the FOV of each image acquisition element meets a preset condition
  • Step S306 collecting images, identifying and storing corresponding point sets
  • the same point on the surface where the calibration map is shot in the calibration scene has corresponding imaging points in the images captured by the three cameras, and these corresponding imaging points are points sets corresponding to each other.
  • Step S308 Determine whether the number of point sets is greater than the first preset threshold; if yes, continue to step S310, that is, it is necessary to obtain the initial calibration parameters; if not, skip to step S304;
  • Step S310 if it can be determined that the number of point sets is greater than the first preset threshold, initial calibration parameters can be obtained based on the current point set;
  • Step S312 construct an error function based on the reprojection error obtained from the point set;
  • step S314 the error function is minimized according to the initial calibration parameters to obtain the camera internal matrix and the camera relative matrix
  • the error function is to construct a mathematical function based on the camera's internal parameters and the relative parameters of the camera, and to determine whether the current calibration parameters are optimal by calculating the error; the minimized error function is to optimize the calibration parameters iteratively to minimize the error, thereby obtaining To the optimal calibration parameters.
  • Step S316 judge whether the error value calculated by the error function is less than the second preset threshold, if yes, continue to perform step S318, which indicates that the minimization process has been completed; if not, return to step S306;
  • step S318 when it is determined that the error value calculated by the error function is less than the preset threshold value, the camera internal matrix and the camera relative matrix obtained by the minimization process can be determined as the final calibration parameters to be used, and there is no need to check the camera internal The matrix and camera perform additional processing relative to the matrix.
  • the method according to the above embodiment can be implemented by means of software plus the necessary general hardware platform, of course, it can also be implemented by hardware, but in many cases the former is Better implementation.
  • the technical solution of the present invention essentially or the part that contributes to the existing technology can be embodied in the form of a software product, and the computer software product is stored in a storage medium (such as ROM/RAM, magnetic disk, The optical disc) includes a number of instructions to enable a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to execute the method described in each embodiment of the present invention.
  • a device for acquiring calibration parameters is also provided.
  • the device is configured to implement the above-mentioned embodiments and preferred implementations, and what has been described will not be repeated.
  • the term "module" can implement a combination of software and/or hardware with predetermined functions.
  • the devices described in the following embodiments are preferably implemented by software, hardware or a combination of software and hardware is also possible and conceived.
  • Fig. 4 is a structural block diagram of a device for acquiring calibration parameters according to one of the embodiments of the present invention.
  • the device includes: a photographing module 10 configured to use a plurality of image acquisition elements to perform a calibration on a calibration image in a calibration scene. Shooting to obtain multiple images; the obtaining module 20 is configured to obtain corresponding point sets from the multiple images, where the point set is the imaging point corresponding to each three-dimensional point on the surface where the calibration map is shot in the multiple images;
  • the calibration module 30 is configured to obtain the calibration parameters to be used of the multiple image acquisition elements according to the point set.
  • the calibration module 30 includes: a determination unit (not shown in the figure), configured to determine the initial calibration parameters through a point set; a construction unit (not shown in the figure), configured to determine the reprojection error based on the point set, To construct the error function; the processing unit (not shown in the figure) is set to minimize the error function according to the initial calibration parameters to obtain the calibration parameters to be used.
  • the determining unit includes: a first judging subunit (not shown in the figure), set to determine whether the number of point sets is greater than a first preset threshold; and a first processing subunit (not shown in the figure) Not shown in), set to obtain the initial calibration parameter when the number of determined point sets is greater than the first preset threshold; when the number of determined point sets is less than or equal to the first preset threshold, adjust the location of multiple image acquisition elements The distance between the position and the calibration map until the number of point sets is greater than the first preset threshold.
  • the first processing subunit (not shown in the figure) is configured to adjust the distance between the positions of the multiple image acquisition elements and the calibration image in the case where multiple image acquisition elements are simultaneously shooting the calibration image.
  • the proportion of the calibration map in the field of view of each image acquisition element meets the preset condition.
  • the processing unit includes: a second processing subunit (not shown in the figure), which is configured to minimize the error function according to the initial calibration parameters to obtain the camera internal matrix and the camera relative matrix
  • the second judgment subunit (not shown in the figure) is set to judge whether the error value of the error function is less than the second preset threshold
  • the third processing subunit (not shown in the figure) is set to determine when the error function is When the error value is less than the second preset threshold, the camera's internal matrix and the camera relative matrix are determined as the calibration parameters to be used; when the error value of the error function is determined to be greater than or equal to the second preset threshold, the corresponding image is obtained from multiple images again Until the error value of the error function is less than the second preset threshold.
  • each of the above modules can be implemented by software or hardware.
  • it can be implemented in the following manner, but not limited to this: the above modules are all located in the same processor; or, the above modules are combined in any combination The forms are located in different processors.
  • An embodiment of the present invention also provides a storage medium in which a computer program is stored, wherein the computer program is configured to execute the steps in any one of the foregoing method embodiments when running.
  • the foregoing storage medium may be configured to store a computer program for executing the following steps:
  • S2 Acquire corresponding point sets from multiple images, where the point sets are the corresponding imaging points in the multiple images of each three-dimensional point on the surface where the calibration map is shot;
  • S3 Acquire calibration parameters to be used for multiple image acquisition elements according to the point set.
  • the storage medium is also set to store a computer program for performing the following steps: determine the initial calibration parameters through the point set; construct the error function based on the reprojection error obtained from the point set; perform the error function on the error function based on the initial calibration parameters Minimize the processing to get the calibration parameters to be used.
  • the storage medium is further configured to store a computer program for performing the following steps: determining whether the number of point sets is greater than a first preset threshold; when it is determined that the number of point sets is greater than the first preset threshold, the initial calibration is obtained Parameter; when it is determined that the number of point sets is less than or equal to the first preset threshold, adjust the distance between the locations of the multiple image acquisition elements and the calibration map until the number of point sets is greater than the first preset threshold.
  • the storage medium is further configured to store a computer program for executing the following steps: in the case where multiple image acquisition elements simultaneously shoot the calibration map, adjusting the distance between the positions of the multiple image acquisition elements and the calibration map, So that the proportion of the calibration map in the field of view of each image acquisition element meets the preset condition.
  • the storage medium is also set to store a computer program for performing the following steps: minimizing the error function according to the initial calibration parameters to obtain the camera internal matrix and the camera relative matrix; judging whether the error value of the error function is less than the first 2.
  • the preset threshold when the error value of the determined error function is less than the second preset threshold, the camera internal matrix and the camera relative matrix are determined as the calibration parameters to be used; when the error value of the determined error function is greater than or equal to the second preset threshold At this time, the corresponding point set is obtained from multiple images again until the error value of the error function is less than the second preset threshold.
  • the foregoing storage medium may include, but is not limited to: U disk, Read-Only Memory (Read-Only Memory, ROM for short), Random Access Memory (Random Access Memory, RAM for short), Various media that can store computer programs, such as mobile hard disks, magnetic disks, or optical disks.
  • the embodiment of the present invention also provides a processor configured to run a computer program to execute the steps in any one of the above method embodiments.
  • the foregoing processor may be configured to execute the following steps through a computer program:
  • S2 Acquire corresponding point sets from multiple images, where the point sets are the corresponding imaging points in the multiple images of each three-dimensional point on the surface where the calibration map is shot;
  • S3 Acquire calibration parameters to be used for multiple image acquisition elements according to the point set.
  • the above-mentioned processor may also be configured to execute the following steps through a computer program: determine the initial calibration parameters through the point set; construct an error function based on the reprojection error obtained from the point set; and minimize the error function according to the initial calibration parameters Through chemical processing, the calibration parameters to be used are obtained.
  • the above-mentioned processor may also be configured to perform the following steps through a computer program: determine whether the number of point sets is greater than a first preset threshold; when it is determined that the number of point sets is greater than the first preset threshold, obtain the initial calibration parameters When it is determined that the number of point sets is less than or equal to the first preset threshold, adjust the distance between the positions of the multiple image acquisition elements and the calibration map until the point set is greater than the first preset threshold.
  • the above-mentioned processor may also be configured to execute the following steps through a computer program: in the case where multiple image acquisition elements simultaneously shoot the calibration map, adjust the distance between the positions of the multiple image acquisition elements and the calibration map to The proportion of the calibration map in the field of view of each image acquisition element meets the preset condition.
  • the above-mentioned processor may also be configured to perform the following steps through a computer program: set initial relative parameters; minimize the error function according to the initial calibration parameters to obtain the camera internal matrix and the camera relative matrix; determine the error of the error function If the value is less than the second preset threshold; when the error value of the error function is determined to be less than the second preset threshold, the camera internal matrix and the camera relative matrix are determined as the calibration parameters to be used; when the error value of the error function is determined to be greater than or equal to the first Second, when the threshold is preset, the corresponding point set is obtained from multiple images again until the error value of the error function is less than the second preset threshold.
  • the disclosed technical content can be implemented in other ways.
  • the device embodiments described above are merely illustrative.
  • the division of the units may be a logical function division, and there may be other divisions in actual implementation, for example, multiple units or components may be combined or may be Integrate into another system, or some features can be ignored or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, units or modules, and may be in electrical or other forms.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.
  • the functional units in the various embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated unit can be implemented in the form of hardware or software functional unit.
  • the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium.
  • the technical solution of the present invention essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium , Including several instructions to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the method described in each embodiment of the present invention.
  • the aforementioned storage media include: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program code .

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Signal Processing (AREA)
  • Multimedia (AREA)
  • Geometry (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Studio Devices (AREA)
  • Length Measuring Devices By Optical Means (AREA)
  • Testing, Inspecting, Measuring Of Stereoscopic Televisions And Televisions (AREA)
  • Measurement Of Optical Distance (AREA)

Abstract

本发明公开了一种标定参数的获取方法、装置、处理器及电子设备。该方法包括：采用多个图像采集元件对标定场景中的标定图进行拍摄，得到多张图像；从多张图像中获取对应的点集，其中，点集为标定图被拍摄到的表面上各个三维点在多张图像中对应的成像点；根据点集获取多个图像采集元件的待使用标定参数。本发明解决了相关技术中无法对多个摄像头实现一体式标定的技术问题。

Description

标定参数的获取方法、装置、处理器及电子设备
交叉援引
本发明基于申请号为201910727431.0、申请日为2019-08-07的中国专利申请提出，并要求该中国专利申请的优先权，该中国专利申请的全部内容在此引入本发明作为参考。
技术领域
本发明涉及图像处理领域，具体而言，涉及一种标定参数的获取方法、装置、处理器及电子设备。
背景技术
目前，三摄像头同时集成在移动终端(例如：智能手机)在市场上呈现蓬勃发展的趋势。三摄像头比于双摄像头而言，可以增加摄像头的种类，例如：三摄像头可以同时包含长焦摄像头，广角摄像头和超广角摄像头，这样的组合可以实现多倍变焦，并且视野范围(field of view，简称为FOV)也会得到极大地提升，由此可以极大地丰富用户体验。然而，相关技术对于一体式三摄标定方面仍然存在较大的技术缺陷。现有的标定方式主要包括以下两种：
方式一、一体式RGB-D标定，该方式在一定距离下采用一个普通摄像头(例如：广角摄像头)拍摄一张广角摄像头图像以及采用一个红外摄像头拍摄一张红外摄像头图像，由此获得双摄像头的标定参数。但是，该方式却无法针对多摄像头实现一体式标定，其原因在于：三摄像头的FOV差距更大，尤其是在同时存在长焦摄像头和超广角摄像头前提下，难以确保长焦摄像头、广角摄像头、超广角摄像头在同一个距离下对标定环境同时拍摄一张图像的情况下获得精准的标定参数。
方式二、一体式双摄像头标定，该方式在一定距离下采用两个普通摄像头(例如：一个长焦摄像头和一个广角摄像头)拍摄两张图像，由此获得双摄像头的标定参数。但是该方式同样无法针对多摄像头实现一体式标定，其原因在于：三摄像头的FOV差距更大，尤其是在同时存在长焦摄像头和超广角摄像头前提下，难以确保长焦摄像头、广角摄像头、超广角摄像头在同一个距离下对标定环境同时拍摄一张图像的情况下获得精准的标定参数。
由此可见，相关技术中所提供的标定方式只能通过拍摄两张图像来获得双摄像头的标定参数，然而却无法获得三摄像头的标定参数。即，无法在同一距离下对三摄像头实现一体式标定。
针对上述的问题，目前尚未提出有效的解决方案。
发明内容
本发明至少部分实施例提供了一种标定参数的获取方法、装置、处理器及电子设备，以至少解决相关技术中无法对多个摄像头实现一体式标定的技术问题。
根据本发明其中一实施例，提供了一种标定参数的获取方法，包括：
采用多个图像采集元件对标定场景中的标定图进行拍摄，得到多张图像；从多张图像中获取对应的点集，其中，点集为标定图被拍摄到的表面上各个三维点在多张图像中对应的成像点；根据点集获取多个图像采集元件的待使用标定参数。
可选地，根据点集获取多个图像采集元件的待使用标定参数包括：通过点集确定初始标定参数；基于点集得到的重投影误差，来构建误差函数；根据初始标定参数对误差函数进行最小化处理，得到待使用标定参数。
可选地，通过点集确定初始标定参数包括：判断点集的数量是否大于第一预设阈值；当确定点集的数量大于第一预设阈值时，得到初始标定参数；当确定点集的数量小于或等于第一预设阈值时，调整多个图像采集元件所在位置与标定图之间的距离，直至点集的数量大于第一预设阈值。
可选地，调整多个图像采集元件所在位置与标定图之间的距离包括：在多个图像采集元件同时拍摄标定图的情况下，调整多个图像采集元件所在位置与标定图之间的距离，以使标定图在每个图像采集元件的视野范围的占比满足预设条件。
可选地，根据初始标定参数对误差函数进行最小化处理，得到待使用标定参数包括：根据初始标定参数对误差函数进行最小化处理，得到相机内部矩阵和相机相对矩阵；判断误差函数的误差值是否小于第二预设阈值；当确定误差函数的误差值小于第二预设阈值时，将相机内部矩阵和相机相对矩阵确定为待使用标定参数；当确定误差函数的误差值大于或等于第二预设阈值时，重新从多张图像中获取对应的点集，直至误差函数的误差值小于第二预设阈值。
可选地，多个图像采集元件为相同类型的图像采集元件，或者，多个图像采集元件为不同类型的图像采集元件，其中，多个图像采集元件的类型包括以下至少之一：长焦摄像头、广角摄像头、超广角摄像头、超长焦摄像头、飞行时间(TOF)深度摄 像头、RGBD深度摄像头、结构光深度摄像头、Mono摄像头、多目摄像头、红外摄像头。
根据本发明其中一实施例，还提供了一种标定参数的获取装置，包括：
拍摄模块，设置为采用多个图像采集元件对标定场景中的标定图进行拍摄，得到多张图像；获取模块，设置为从多张图像中获取对应的点集，其中，点集为标定图被拍摄到的表面上各个三维点在多张图像中对应的成像点；标定模块，设置为根据点集获取多个图像采集元件的待使用标定参数。
可选地，标定模块包括：确定单元，设置为通过点集确定初始标定参数；构建单元，设置为基于点集得到的重投影误差，来构建误差函数；处理单元，设置为根据初始标定参数对误差函数进行最小化处理，得到待使用标定参数。
可选地，确定单元包括：第一判断子单元，设置为判断点集的数量是否大于第一预设阈值；第一处理子单元，设置为当确定点集的数量大于第一预设阈值时，得到初始标定参数；当确定点集的数量小于或等于第一预设阈值时，调整多个图像采集元件所在位置与标定图之间的距离，直至点集的数量大于第一预设阈值。
可选地，第一处理子单元，设置为在多个图像采集元件同时拍摄标定图的情况下，调整多个图像采集元件所在位置与标定图之间的距离，以使标定图在每个图像采集元件的视野范围的占比满足预设条件。
可选地，处理单元包括：第二处理子单元，设置为根据初始标定参数对误差函数进行最小化处理，得到相机内部矩阵和相机相对矩阵；第二判断子单元，设置为判断误差函数的误差值是否小于第二预设阈值；第三处理子单元，设置为当确定误差函数的误差值小于第二预设阈值时，将相机内部矩阵和相机相对矩阵确定为待使用标定参数；当确定误差函数的误差值大于或等于第二预设阈值时，重新从多张图像中获取对应的点集，直至误差函数的误差值小于第二预设阈值。
根据本发明其中一实施例，还提供了一种存储介质，存储介质中存储有计算机程序，其中，计算机程序被设置为运行时执行上述任一项的标定参数的获取方法。
根据本发明其中一实施例，还提供了一种处理器，处理器设置为运行程序，其中，程序运行时执行上述任一项的标定参数的获取方法。
根据本发明其中一实施例，还提供了一种电子设备，包括存储器和处理器，存储器中存储有计算机程序，处理器被设置为运行计算机程序以执行上述任一项的标定参数的获取方法。
在本发明至少部分实施例中，采用多个图像采集元件对标定场景中的标定图进行拍摄，得到多张图像的方式，通过从多张图像中获取对应的点集，该点集为标定图被拍摄到的表面上各个三维点在多张图像中对应的成像点，以及根据点集获取多个图像采集元件的待使用标定参数，达到了在同一距离下对多个图像采集元件实现一体式标定的目的，从而实现了通过对多个摄像头实现一体式标定得到的标定参数能够有效地对原始输入图像进行矫正的技术效果，进而解决了相关技术中无法对多个摄像头实现一体式标定的技术问题。
附图说明
此处所说明的附图用来提供对本发明的进一步理解，构成本申请的一部分，本发明的示意性实施例及其说明用于解释本发明，并不构成对本发明的不当限定。在附图中：
图1是根据本发明其中一可选实施例的标定参数获取过程的应用场景示意图；
图2是根据本发明其中一实施例的标定参数的获取方法的流程图；
图3是根据本发明其中一可选实施例的标定参数的获取方法的流程图；
图4是根据本发明其中一实施例的标定参数的获取装置的结构框图。
具体实施方式
为了使本技术领域的人员更好地理解本发明方案，下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分的实施例，而不是全部的实施例。基于本发明中的实施例，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，都应当属于本发明保护的范围。
需要说明的是，本发明的说明书和权利要求书及上述附图中的术语“第一”、“第二”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换，以便这里描述的本发明的实施例能够以除了在这里图示或描述的那些以外的顺序实施。此外，术语“包括”和“具有”以及他们的任何变形，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、产品或设备不必限于清楚地列出的那些步骤或单元，而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。
首先，在对本发明至少部分实施例进行描述的过程中出现的部分名词或术语适用于如下解释：
(1)一体式多摄像头标定：采用多个摄像头(通常摄像头的数量大于或等于两个)在一个环境中对标定环境同时各拍一张图像以获得标定参数，其中，标定参数包括：相机内部参数和相机相对参数。在后续本发明至少部分实施例中，将会以三个摄像头(例如：同时包含长焦摄像头，广角摄像头和超广角摄像头)为例，对一体式三摄标定过程进行解释说明。
需要说明的是，上述多个摄像头既可以为相同类型的摄像头也可以为不同类型的摄像头。不论上述多个摄像头的类型和参数是否相同，均可以采用本发明实施例所公开的方案实现对多个摄像头进行标定。另外，多个摄像头的类型可以包括但不限于以下至少之一：长焦摄像头、广角摄像头、超广角摄像头、超长焦摄像头、TOF深度摄像头、RGBD深度摄像头、结构光深度摄像头、Mono摄像头、多目摄像头、红外摄像头。
(2)相机内部参数(intrinsic parameter)包括：相机的焦距，主点坐标，畸变系数等参数。
(3)相机内部矩阵(intrinsic matrix)是将intrinsic parameter填充至矩阵并输出为矩阵形式，其实质上属于相机内部参数的另外一种表示形式。
(4)相机相对参数(extrinsic matrix)包括：相机之间的旋转，平移等参数。
(5)相机相对矩阵(extrinsic matrix)是将extrinsic parameter填充至矩阵并输出为矩阵形式，其实质上属于相机相对参数的另外一种表示形式。
(6)矫正(rectify)是指使用标定参数将原始输入图像变换到对应点在同一水平线上，其中，对应点是指在标定环境中的同一点在三摄拍摄的图像中所形成的相互对应的成像点。
根据本发明其中一实施例，提供了一种标定参数的获取方法的实施例，需要说明的是，在附图的流程图示出的步骤可以在诸如一组计算机可执行指令的计算机系统中执行，并且，虽然在流程图中示出了逻辑顺序，但是在某些情况下，可以以不同于此处的顺序执行所示出或描述的步骤。
该方法实施例可以在移动终端、计算机终端或者类似的电子设备中执行。以运行在移动终端上为例，移动终端可以包括一个或多个处理器(处理器可以包括但不限于中央处理器(CPU)、图形处理器(GPU)、数字信号处理(DSP)芯片、微处理器(MCU) 或可编程逻辑器件(FPGA)等的处理装置)和设置为存储数据的存储器。可选地，上述移动终端还可以包括设置为通信功能的传输设备以及输入输出设备。本领域普通技术人员可以理解，上述结构描述仅为示意，其并不对上述移动终端的结构造成限定。例如，移动终端还可包括比上述结构描述中所示更多或者更少的组件，或者具有与上述结构描述不同的配置。
存储器可设置为存储计算机程序，例如，应用软件的软件程序以及模块，如本发明实施例中的标定参数的获取方法对应的计算机程序，处理器通过运行存储在存储器内的计算机程序，从而执行各种功能应用以及数据处理，即实现上述的标定参数的获取方法。存储器可包括高速随机存储器，还可包括非易失性存储器，如一个或者多个磁性存储装置、闪存、或者其他非易失性固态存储器。在一些实例中，存储器可进一步包括相对于处理器远程设置的存储器，这些远程存储器可以通过网络连接至移动终端。上述网络的实例包括但不限于互联网、企业内部网、局域网、移动通信网及其组合。
传输设备设置为经由一个网络接收或者发送数据。上述的网络具体实例可包括移动终端的通信供应商提供的无线网络。在一个实例中，传输设备包括一个网络适配器(Network Interface Controller，简称为NIC)，其可通过基站与其他网络设备相连从而可与互联网进行通讯。在一个实例中，传输设备可以为射频(Radio Frequency，简称为RF)模块，其设置为通过无线方式与互联网进行通讯。
图1是根据本发明其中一可选实施例的标定参数获取过程的应用场景示意图，以三摄像头为例，如图1所示，三摄像头(例如：同时包含长焦摄像头，广角摄像头和超广角摄像头)位于同一个模组中并放置在标定图前的固定距离处，以便模组厂商在手机模组的组装过程中完成一体式三摄像机标定。当然，本发明并不限定三摄像头需要处于模组状态，还可以采用其他部署方式，例如：可以将三摄像头安装到移动终端(例如：智能手机)，也可以直接采用上述电子设备来进行标定，还可以分布在三个不同设备(例如：模组、手机以及相机的组合)。
在本实施例中提供了一种运行于上述移动终端的标定参数的获取方法，图2是根据本发明其中一实施例的标定参数的获取方法的流程图，如图2所示，该流程包括如下步骤：
步骤S22，采用多个图像采集元件对标定场景中的标定图进行拍摄，得到多张图像；
步骤S24，从多张图像中获取对应的点集，其中，点集为标定图被拍摄到的表面上各个三维点在多张图像中对应的成像点；
步骤S26，根据点集获取多个图像采集元件的待使用标定参数。
通过上述步骤，可以采用多个图像采集元件对标定场景中的标定图进行拍摄，得到多张图像的方式，通过从多张图像中获取对应的点集，该点集为标定图被拍摄到的表面上各个三维点在多张图像中对应的成像点，以及根据点集获取多个图像采集元件的待使用标定参数，达到了在同一距离下对多个图像采集元件实现一体式标定的目的，从而实现了通过对多个摄像头实现一体式标定得到的标定参数能够有效地对原始输入图像进行矫正的技术效果，进而解决了相关技术中无法对多个摄像头实现一体式标定的技术问题。
在一个可选实施例中，上述标定图可以包括多个独立的标定模板，每个标定模板由若干个内含圆点的棋盘格构成，以其中一个标定模板作为参考模板，其它标定模板分别与参考模板在不同方向上呈预定夹角摆放。例如，如图1所示，标定图包括4个独立的标定模板，每个模板由19*14个内含圆点的棋盘格构成，并且以左上的标定模板作为参考模板，其它三个标定模板分别与参考模板在不同方向上成30度夹角摆放。
在另一个可选实施例中，如果多个摄像头的类型中包含深度摄像头和红外摄像头，则通常会采用圆相标定图而并非采用上述棋盘格，其原因在于：相比于棋盘格，圆相更容易被捕捉和定位，从而有助于对多个摄像头实现一体式标定，并且所得到的标定结果也更为可靠。此外，由于深度摄像头和红外摄像头所拍摄到的图像会偏暗，因此，还需要对所拍摄到的图像进行额外的补光处理，以增加图像的清晰度。作为一个可选的示例，可以采用同波段的红外LED灯补光，例如：设备自身的红外发射器采用940nm红外光，那么补光处理也需要采用940nm的红外LED灯补光。
上述多个图像采集元件可以为多个摄像头，多个图像采集元件的数量大于或等于两个。
可选地，在步骤S26中，根据点集获取多个图像采集元件的待使用标定参数可以包括以下执行步骤：
步骤S261，通过点集确定初始标定参数；
步骤S262，基于点集得到的重投影误差，来构建误差函数；
步骤S263，根据初始标定参数对误差函数进行最小化处理，得到待使用标定参数。
在一个可选实施例中，以三摄像头(例如：同时包含长焦摄像头，广角摄像头和超广角摄像头)为例，且三摄像头位于同一个模组中。通过搭建图像采集环境(即标定场景)，在标定图之前的固定距离处放置模组。然后，控制三摄像头采集图像，识别 并存储对应的点集。标定场景中标定图被拍摄到的表面上的同一点在三摄像头拍摄的图像中分别存在对应的成像点，这些对应的成像点即是相互对应的点集。最后，采用这些对应的点集(包括但不限于：点集的坐标、点与点之间的对应关系)便可确定初始标定参数，即相机内部参数和相机相对参数的初始值。
在搭建的图像采集环境中的三维点在实际拍摄到多张图像中的成像点位置可以称为真实值(即观测到的投影位置)。而根据计算的标定参数以及成像模型推算得到此三维点的成像点位置可以称为计算值(即三维点按照当前估计的位姿进行投影得到的位置)，该推算过程被称为重投影。因此，成像点的计算值与成像点的真实值之间的差值即为重投影误差。
误差函数是根据相机内部参数和相机相对参数来构建一个数学函数，通过计算误差来判断当前的标定参数是否为最优；对误差函数进行最小化处理便是通过迭代优化标定参数使得误差最小，从而获取到最优的待使用标定参数。
可选地，在步骤S261中，通过点集确定初始标定参数可以包括以下执行步骤：
步骤S2611，判断点集的数量是否大于第一预设阈值；
步骤S2612，当确定点集的数量大于第一预设阈值时，得到初始标定参数；当确定点集的数量小于或等于第一预设阈值时，调整多个图像采集元件所在位置与标定图之间的距离，直至点集的数量大于第一预设阈值。
在通过点集确定初始标定参数的过程中，需要判断点集的数量是否大于第一预设阈值。如果能够确定点集的数量大于第一预设阈值，则基于当前点集便可得到初始标定参数。然而，如果能够确定点集的数量小于或等于第一预设阈值时，则首先需要调整多个图像采集元件所在位置与标定图之间的距离，然后重新从多张图像中获取对应的点集，直至点集的数量大于第一预设阈值，以便基于最新获取到的点集便可得到初始标定参数。
在一个可选实施例中，在多个图像采集元件同时拍摄标定图的情况下，调整多个图像采集元件所在位置与标定图之间的距离，以使标定图在每个图像采集元件的FOV的占比满足预设条件。例如：可以将预先设定的比例值作为该预设条件，如果标定图在每个图像采集元件的FOV的占比超过预先设定的比例值，则无需继续调整多个图像采集元件所在位置与标定图之间的距离。如果标定图在每个图像采集元件的FOV的占比未能达到预先设定的比例值，则仍需继续调整多个图像采集元件所在位置与标定图之间的距离。
可选地，在步骤S263中，根据初始标定参数对误差函数进行最小化处理，得到待 使用标定参数可以包括以下执行步骤：
步骤S2631，根据初始标定参数对误差函数进行最小化处理，得到相机内部矩阵和相机相对矩阵；
步骤S2632，判断误差函数的误差值是否小于第二预设阈值；
步骤S2633，当确定误差函数的误差值小于第二预设阈值时，将相机内部矩阵和相机相对矩阵确定为待使用标定参数；当确定误差函数的误差值大于或等于第二预设阈值时，重新从多张图像中获取对应的点集，直至误差函数的误差值小于第二预设阈值。
在基于点集得到的重投影误差来构建误差函数之后，通过对误差函数进行最小化处理，得到相机内部矩阵和相机相对矩阵。在最小化处理过程中，可以判断通过误差函数计算得到的误差值是否小于第二预设阈值，如果确定误差函数计算得到的误差值小于预设阈值，则表示最小化过程已经完成。如果确定误差函数的误差值大于或等于第二预设阈值时，则需要重新从多张图像中获取对应的点集，直至误差函数的误差值小于第二预设阈值。在确定误差函数计算得到的误差值小于预设阈值的情况下，可以将最小化处理所得到的相机内部矩阵和相机相对矩阵确定为最终的待使用标定参数，而无需再对相机内部矩阵和相机相对矩阵进行额外处理。
下面将通过图3所示的可选实施方式对上述可选实施过程做进一步地详细描述。图3是根据本发明其中一可选实施例的标定参数的获取方法的流程图，如图3所示，该流程包括如下步骤：
步骤S302，搭建图像采集环境，摆放标定图；
步骤S304，调整多个图像采集元件所在位置与标定图之间的距离，以使标定图在每个图像采集元件的FOV的占比满足预设条件；
步骤S306，采集图像，识别并存储对应的点集；
其中，标定场景中标定图被拍摄到的表面上的同一点在三摄像头拍摄的图像中分别存在对应的成像点，这些对应的成像点即是相互对应的点集。
步骤S308，判断点集的数量是否大于第一预设阈值；如果是，则继续执行步骤S310，即需要获取初始标定参数；如果否，则跳转执行步骤S304；
步骤S310，如果能够确定点集的数量大于第一预设阈值，则基于当前点集便可得到初始标定参数；
步骤S312，基于点集得到的重投影误差，来构建误差函数；
步骤S314，根据初始标定参数对误差函数进行最小化处理，得到相机内部矩阵和相机相对矩阵；
其中，误差函数是根据相机内部参数和相机相对参数来构建一个数学函数，通过计算误差来判断当前的标定参数是否为最优；最小化误差函数便是通过迭代优化标定参数使得误差最小，从而获取到最优的标定参数。
步骤S316，判断通过误差函数计算得到的误差值是否小于第二预设阈值，如果是，则继续执行步骤S318，表示最小化过程已经完成；如果否，则返回步骤S306；
步骤S318，在确定误差函数计算得到的误差值小于预设阈值的情况下，可以将最小化处理所得到的相机内部矩阵和相机相对矩阵确定为最终的待使用标定参数，而无需再对相机内部矩阵和相机相对矩阵进行额外处理。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到根据上述实施例的方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件，但很多情况下前者是更佳的实施方式。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质(如ROM/RAM、磁碟、光盘)中，包括若干指令用以使得一台终端设备(可以是手机，计算机，服务器，或者网络设备等)执行本发明各个实施例所述的方法。
在本实施例中还提供了一种标定参数的获取装置，该装置设置为实现上述实施例及优选实施方式，已经进行过说明的不再赘述。如以下所使用的，术语“模块”可以实现预定功能的软件和/或硬件的组合。尽管以下实施例所描述的装置较佳地以软件来实现，但是硬件，或者软件和硬件的组合的实现也是可能并被构想的。
图4是根据本发明其中一实施例的标定参数的获取装置的结构框图，如图4所示，该装置包括：拍摄模块10，设置为采用多个图像采集元件对标定场景中的标定图进行拍摄，得到多张图像；获取模块20，设置为从多张图像中获取对应的点集，其中，点集为标定图被拍摄到的表面上各个三维点在多张图像中对应的成像点；标定模块30，设置为根据点集获取多个图像采集元件的待使用标定参数。
可选地，标定模块30包括：确定单元(图中未示出)，设置为通过点集确定初始标定参数；构建单元(图中未示出)，设置为基于点集得到的重投影误差，来构建误差 函数；处理单元(图中未示出)，设置为根据初始标定参数对误差函数进行最小化处理，得到待使用标定参数。
可选地，确定单元(图中未示出)包括：第一判断子单元(图中未示出)，设置为判断点集的数量是否大于第一预设阈值；第一处理子单元(图中未示出)，设置为当确定点集的数量大于第一预设阈值时，得到初始标定参数；当确定点集的数量小于或等于第一预设阈值时，调整多个图像采集元件所在位置与标定图之间的距离，直至点集的数量大于第一预设阈值。
可选地，第一处理子单元(图中未示出)，设置为在多个图像采集元件同时拍摄标定图的情况下，调整多个图像采集元件所在位置与标定图之间的距离，以使标定图在每个图像采集元件的视野范围的占比满足预设条件。
可选地，处理单元(图中未示出)包括：第二处理子单元(图中未示出)，设置为根据初始标定参数对误差函数进行最小化处理，得到相机内部矩阵和相机相对矩阵；第二判断子单元(图中未示出)，设置为判断误差函数的误差值是否小于第二预设阈值；第三处理子单元(图中未示出)，设置为当确定误差函数的误差值小于第二预设阈值时，将相机内部矩阵和相机相对矩阵确定为待使用标定参数；当确定误差函数的误差值大于或等于第二预设阈值时，重新从多张图像中获取对应的点集，直至误差函数的误差值小于第二预设阈值。
需要说明的是，上述各个模块是可以通过软件或硬件来实现的，对于后者，可以通过以下方式实现，但不限于此：上述模块均位于同一处理器中；或者，上述各个模块以任意组合的形式分别位于不同的处理器中。
本发明的实施例还提供了一种存储介质，该存储介质中存储有计算机程序，其中，该计算机程序被设置为运行时执行上述任一项方法实施例中的步骤。
可选地，在本实施例中，上述存储介质可以被设置为存储用于执行以下步骤的计算机程序：
S1，采用多个图像采集元件对标定场景中的标定图进行拍摄，得到多张图像；
S2，从多张图像中获取对应的点集，其中，点集为标定图被拍摄到的表面上各个三维点在多张图像中对应的成像点；
S3，根据点集获取多个图像采集元件的待使用标定参数。
可选地，存储介质还被设置为存储用于执行以下步骤的计算机程序：通过点集确 定初始标定参数；基于点集得到的重投影误差，来构建误差函数；根据初始标定参数对误差函数进行最小化处理，得到待使用标定参数。
可选地，存储介质还被设置为存储用于执行以下步骤的计算机程序：判断点集的数量是否大于第一预设阈值；当确定点集的数量大于第一预设阈值时，得到初始标定参数；当确定点集的数量小于或等于第一预设阈值时，调整多个图像采集元件所在位置与标定图之间的距离，直至点集的数量大于第一预设阈值。
可选地，存储介质还被设置为存储用于执行以下步骤的计算机程序：在多个图像采集元件同时拍摄标定图的情况下，调整多个图像采集元件所在位置与标定图之间的距离，以使标定图在每个图像采集元件的视野范围的占比满足预设条件。
可选地，存储介质还被设置为存储用于执行以下步骤的计算机程序：根据初始标定参数对误差函数进行最小化处理，得到相机内部矩阵和相机相对矩阵；判断误差函数的误差值是否小于第二预设阈值；当确定误差函数的误差值小于第二预设阈值时，将相机内部矩阵和相机相对矩阵确定为待使用标定参数；当确定误差函数的误差值大于或等于第二预设阈值时，重新从多张图像中获取对应的点集，直至误差函数的误差值小于第二预设阈值。
可选地，在本实施例中，上述存储介质可以包括但不限于：U盘、只读存储器(Read-Only Memory，简称为ROM)、随机存取存储器(Random Access Memory，简称为RAM)、移动硬盘、磁碟或者光盘等各种可以存储计算机程序的介质。
本发明的实施例还提供了一种处理器，该处理器被设置为运行计算机程序以执行上述任一项方法实施例中的步骤。
可选地，在本实施例中，上述处理器可以被设置为通过计算机程序执行以下步骤：
S1，采用多个图像采集元件对标定场景中的标定图进行拍摄，得到多张图像；
S2，从多张图像中获取对应的点集，其中，点集为标定图被拍摄到的表面上各个三维点在多张图像中对应的成像点；
S3，根据点集获取多个图像采集元件的待使用标定参数。
可选地，上述处理器还可以被设置为通过计算机程序执行以下步骤：通过点集确定初始标定参数；基于点集得到的重投影误差，来构建误差函数；根据初始标定参数对误差函数进行最小化处理，得到待使用标定参数。
可选地，上述处理器还可以被设置为通过计算机程序执行以下步骤：判断点集的数量是否大于第一预设阈值；当确定点集的数量大于第一预设阈值时，得到初始标定参数；当确定点集的数量小于或等于第一预设阈值时，调整多个图像采集元件所在位置与标定图之间的距离，直至点集大于第一预设阈值。
可选地，上述处理器还可以被设置为通过计算机程序执行以下步骤：在多个图像采集元件同时拍摄标定图的情况下，调整多个图像采集元件所在位置与标定图之间的距离，以使标定图在每个图像采集元件的视野范围的占比满足预设条件。
可选地，上述处理器还可以被设置为通过计算机程序执行以下步骤：设置初始化相对参数；根据初始标定参数对误差函数进行最小化处理，得到相机内部矩阵和相机相对矩阵；判断误差函数的误差值是否小于第二预设阈值；当确定误差函数的误差值小于第二预设阈值时，将相机内部矩阵和相机相对矩阵确定为待使用标定参数；当确定误差函数的误差值大于或等于第二预设阈值时，重新从多张图像中获取对应的点集，直至误差函数的误差值小于第二预设阈值。
可选地，本实施例中的具体示例可以参考上述实施例及可选实施方式中所描述的示例，本实施例在此不再赘述。
上述本发明实施例序号仅仅为了描述，不代表实施例的优劣。
在本发明的上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述的部分，可以参见其他实施例的相关描述。
在本申请所提供的几个实施例中，应该理解到，所揭露的技术内容，可通过其它的方式实现。其中，以上所描述的装置实施例仅仅是示意性的，例如所述单元的划分，可以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，单元或模块的间接耦合或通信连接，可以是电性或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本发明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。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可为个人计算机、服务器或者网络设备等)执行本发明各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、移动硬盘、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述仅是本发明的优选实施方式，应当指出，对于本技术领域的普通技术人员来说，在不脱离本发明原理的前提下，还可以做出若干改进和润饰，这些改进和润饰也应视为本发明的保护范围。

Claims (14)

  1. 一种标定参数的获取方法，包括：
    采用多个图像采集元件对标定场景中的标定图进行拍摄，得到多张图像；
    从所述多张图像中获取对应的点集，其中，所述点集为所述标定图被拍摄到的表面上各个三维点在所述多张图像中对应的成像点；
    根据所述点集获取所述多个图像采集元件的待使用标定参数。
  2. 根据权利要求1所述的方法，其中，根据所述点集获取所述多个图像采集元件的所述待使用标定参数包括：
    通过所述点集确定初始标定参数；
    基于所述点集得到的重投影误差，来构建误差函数；
    根据所述初始标定参数对所述误差函数进行最小化处理，得到所述待使用标定参数。
  3. 根据权利要求2所述的方法，其中，通过所述点集确定所述初始标定参数包括：
    判断所述点集的数量是否大于第一预设阈值；
    当确定所述点集的数量大于所述第一预设阈值时，得到所述初始标定参数；当确定所述点集的数量小于或等于所述第一预设阈值时，调整所述多个图像采集元件所在位置与标定图之间的距离，直至所述点集的数量大于所述第一预设阈值。
  4. 根据权利要求3所述的方法，其中，调整所述多个图像采集元件所在位置与标定图之间的距离包括：
    在所述多个图像采集元件同时拍摄所述标定图的情况下，调整所述多个图像采集元件所在位置与所述标定图之间的距离，以使所述标定图在每个图像采集元件的视野范围的占比满足预设条件。
  5. 根据权利要求2所述的方法，其中，根据所述初始标定参数对所述误差函数进行最小化处理，得到所述待使用标定参数包括：
    根据所述初始标定参数对所述误差函数进行最小化处理，得到相机内部矩阵和相机相对矩阵；
    判断所述误差函数的误差值是否小于第二预设阈值；
    当确定所述误差函数的误差值小于所述第二预设阈值时，将所述相机内部矩阵和所述相机相对矩阵确定为所述待使用标定参数；当确定所述误差函数的误差值大于或等于所述第二预设阈值时，重新从所述多张图像中获取对应的点集，直至所述误差函数的误差值小于所述第二预设阈值。
  6. 根据权利要求1所述的方法，其中，所述多个图像采集元件为相同类型的图像采集元件，或者，所述多个图像采集元件为不同类型的图像采集元件，其中，所述多个图像采集元件的类型包括以下至少之一：长焦摄像头、广角摄像头、超广角摄像头、超长焦摄像头、飞行时间TOF深度摄像头、RGBD深度摄像头、结构光深度摄像头、Mono摄像头、多目摄像头、红外摄像头。
  7. 一种标定参数的获取装置，包括：
    拍摄模块，设置为采用多个图像采集元件对标定场景中的标定图进行拍摄，得到多张图像；
    获取模块，设置为从所述多张图像中获取对应的点集，其中，所述点集为所述标定图被拍摄到的表面上各个三维点在所述多张图像中对应的成像点；
    标定模块，设置为根据所述点集获取所述多个图像采集元件的待使用标定参数。
  8. 根据权利要求7所述的装置，其中，所述标定模块包括：
    确定单元，设置为通过所述点集确定初始标定参数；
    构建单元，设置为基于所述点集得到的重投影误差，来构建误差函数；
    处理单元，设置为根据所述初始标定参数对所述误差函数进行最小化处理，得到所述待使用标定参数。
  9. 根据权利要求8所述的装置，其中，所述确定单元包括：
    第一判断子单元，设置为判断所述点集的数量是否大于第一预设阈值；
    第一处理子单元，设置为当确定所述点集的数量大于所述第一预设阈值时，得到所述初始标定参数；当确定所述点集的数量小于或等于所述第一预设阈值时，调整所述多个图像采集元件所在位置与标定图之间的距离，直至所述点集的数量大于所述第一预设阈值。
  10. 根据权利要求9所述的装置，其中，所述第一处理子单元，设置为在所述多个图像采集元件同时拍摄所述标定图的情况下，调整所述多个图像采集元件所在位置 与所述标定图之间的距离，以使所述标定图在每个图像采集元件的视野范围的占比满足预设条件。
  11. 根据权利要求8所述的装置，其中，所述处理单元包括：
    第二处理子单元，设置为根据所述初始标定参数对所述误差函数进行最小化处理，得到相机内部矩阵和相机相对矩阵；
    第二判断子单元，设置为判断所述误差函数的误差值是否小于第二预设阈值；
    第三处理子单元，设置为当确定所述误差函数的误差值小于所述第二预设阈值时，将所述相机内部矩阵和所述相机相对矩阵确定为所述待使用标定参数；当确定所述误差函数的误差值大于或等于所述第二预设阈值时，重新从所述多张图像中获取对应的点集，直至所述误差函数的误差值小于所述第二预设阈值。
  12. 一种存储介质，所述存储介质中存储有计算机程序，其中，所述计算机程序被设置为运行时执行权利要求1至6中任一项所述的标定参数的获取方法。
  13. 一种处理器，所述处理器设置为运行程序，其中，所述程序运行时执行权利要求1至6中任一项所述的标定参数的获取方法。
  14. 一种电子设备，包括存储器和处理器，所述存储器中存储有计算机程序，所述处理器被设置为运行所述计算机程序以执行权利要求1至6中任一项所述的标定参数的获取方法。
PCT/CN2020/102491 2019-08-07 2020-07-16 标定参数的获取方法、装置、处理器及电子设备 WO2021022989A1 (zh)

Priority Applications (3)

Application Number Priority Date Filing Date Title
JP2022507531A JP7387872B2 (ja) 2019-08-07 2020-07-16 キャリブレーションパラメータの取得方法、装置、プロセッサ及び電子機器
KR1020227007689A KR20220044572A (ko) 2019-08-07 2020-07-16 캘리브레이션 파라미터의 획득 방법, 장치, 프로세서 및 전자기기
US17/631,475 US20220277468A1 (en) 2019-08-07 2020-07-16 Calibration Parameter Obtaining Method and Apparatus, Processor, and Electronic Device

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201910727431.0A CN112348899A (zh) 2019-08-07 2019-08-07 标定参数的获取方法、装置、处理器及电子设备
CN201910727431.0 2019-08-07

Publications (1)

Publication Number Publication Date
WO2021022989A1 true WO2021022989A1 (zh) 2021-02-11

Family

ID=74367392

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2020/102491 WO2021022989A1 (zh) 2019-08-07 2020-07-16 标定参数的获取方法、装置、处理器及电子设备

Country Status (5)

Country Link
US (1) US20220277468A1 (zh)
JP (1) JP7387872B2 (zh)
KR (1) KR20220044572A (zh)
CN (1) CN112348899A (zh)
WO (1) WO2021022989A1 (zh)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113112553A (zh) * 2021-05-26 2021-07-13 北京三快在线科技有限公司 双目相机的参数标定方法、装置、电子设备及存储介质
CN114913088A (zh) * 2022-05-10 2022-08-16 宁波力显智能科技有限公司 显微成像的多通道对齐方法、装置和计算机设备

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1622083A2 (en) * 2004-07-27 2006-02-01 Microsoft Corporation A system and method for calibrating multiple cameras without employing a pattern by inter-image homography
CN108171758A (zh) * 2018-01-16 2018-06-15 重庆邮电大学 基于最小光程原理和透明玻璃标定板的多相机标定方法
CN109697737A (zh) * 2018-11-30 2019-04-30 Oppo广东移动通信有限公司 摄像头标定方法、装置、电子设备和计算机可读存储介质
CN109767474A (zh) * 2018-12-31 2019-05-17 深圳积木易搭科技技术有限公司 一种多目相机标定方法、装置及存储介质
CN110009687A (zh) * 2019-03-14 2019-07-12 深圳市易尚展示股份有限公司 基于三相机的彩色三维成像系统及其标定方法

Family Cites Families (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP3929384B2 (ja) 2002-10-23 2007-06-13 オリンパス株式会社 ファインダ、撮影装置、マーカ提示部材、及び、キャリブレーションのための撮影方法
JP2006121750A (ja) 2006-01-06 2006-05-11 Olympus Corp キャリブレーションパターンユニット
JP4816464B2 (ja) 2007-01-17 2011-11-16 株式会社ニコン レンズのキャリブレーション方法、レンズのキャリブレーション装置、撮像装置のキャリブレーション方法およびキャリブレーション装置
JP2015232442A (ja) 2012-10-04 2015-12-24 アルプス電気株式会社 画像処理装置及び車両前方監視装置
CN102982548B (zh) * 2012-12-11 2015-11-25 清华大学 多目立体视频采集系统及其相机参数标定方法
CN103824278B (zh) * 2013-12-10 2016-09-21 清华大学 监控摄像机的标定方法和系统
JP6523925B2 (ja) 2015-11-10 2019-06-05 株式会社日立製作所 生体情報を用いた認証装置及び認証方法
JP2018004420A (ja) 2016-06-30 2018-01-11 株式会社リコー 装置、移動体装置、位置ずれ検出方法及び測距方法
JP6922348B2 (ja) 2017-03-31 2021-08-18 富士通株式会社 情報処理装置、方法、及びプログラム
EP3606038B1 (en) 2017-03-31 2021-12-08 Panasonic Intellectual Property Management Co., Ltd. Imaging system and correction method
JP2019074699A (ja) 2017-10-18 2019-05-16 パナソニックＩｐマネジメント株式会社 インタラクティブインタフェースシステム、作業支援システム、厨房支援システム、及びインタラクティブインタフェースシステムのキャリブレーション方法
JP2019079468A (ja) 2017-10-27 2019-05-23 キヤノン株式会社 画像処理システム、画像処理システムの制御方法及びプログラム
CN109754427A (zh) * 2017-11-01 2019-05-14 虹软科技股份有限公司 一种用于标定的方法和装置
CN109785390B (zh) * 2017-11-13 2022-04-01 虹软科技股份有限公司 一种用于图像矫正的方法和装置

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1622083A2 (en) * 2004-07-27 2006-02-01 Microsoft Corporation A system and method for calibrating multiple cameras without employing a pattern by inter-image homography
CN108171758A (zh) * 2018-01-16 2018-06-15 重庆邮电大学 基于最小光程原理和透明玻璃标定板的多相机标定方法
CN109697737A (zh) * 2018-11-30 2019-04-30 Oppo广东移动通信有限公司 摄像头标定方法、装置、电子设备和计算机可读存储介质
CN109767474A (zh) * 2018-12-31 2019-05-17 深圳积木易搭科技技术有限公司 一种多目相机标定方法、装置及存储介质
CN110009687A (zh) * 2019-03-14 2019-07-12 深圳市易尚展示股份有限公司 基于三相机的彩色三维成像系统及其标定方法

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113112553A (zh) * 2021-05-26 2021-07-13 北京三快在线科技有限公司 双目相机的参数标定方法、装置、电子设备及存储介质
CN114913088A (zh) * 2022-05-10 2022-08-16 宁波力显智能科技有限公司 显微成像的多通道对齐方法、装置和计算机设备

Also Published As

Publication number Publication date
JP7387872B2 (ja) 2023-11-28
JP2022543158A (ja) 2022-10-07
US20220277468A1 (en) 2022-09-01
CN112348899A (zh) 2021-02-09
KR20220044572A (ko) 2022-04-08

Similar Documents

Publication Publication Date Title
CN107113415B (zh) 用于多技术深度图获取和融合的方法和设备
WO2018201809A1 (zh) 基于双摄像头的图像处理装置及方法
CN106851122B (zh) 基于双摄像头系统的自动曝光参数的标定方法和装置
CN112311965B (zh) 虚拟拍摄方法、装置、系统及存储介质
CN110278382B (zh) 一种聚焦方法、装置、电子设备及存储介质
CN110099220B (zh) 一种全景拼接方法及装置
CN104735348B (zh) 双摄像头拍照方法和系统
CN107704798B (zh) 图像虚化方法、装置、计算机可读存储介质和计算机设备
CN110675458B (zh) 用于摄像头标定的方法、装置及存储介质
WO2021022989A1 (zh) 标定参数的获取方法、装置、处理器及电子设备
CN106708070B (zh) 一种航拍控制方法和装置
US11523056B2 (en) Panoramic photographing method and device, camera and mobile terminal
US11514608B2 (en) Fisheye camera calibration system, method and electronic device
CN111279393A (zh) 相机标定方法、装置、设备及存储介质
CN106888353A (zh) 一种图像采集方法及设备
CN112446251A (zh) 图像处理方法及相关装置
CN107431751B (zh) 采集图像的方法、装置和系统
US11166005B2 (en) Three-dimensional information acquisition system using pitching practice, and method for calculating camera parameters
CN109120846B (zh) 图像处理方法和装置、电子设备、计算机可读存储介质
CN110848907A (zh) 空调器的控制方法、空调器及计算机可读存储介质
CN110691197A (zh) 一种拍摄追踪的方法、装置、电子设备
CN106101539A (zh) 一种自拍杆角度调节方法及自拍杆
CN110012208B (zh) 拍照对焦方法、装置、存储介质及电子设备
CN112532856A (zh) 一种拍摄方法、装置和系统
CN110809116A (zh) 一种拍摄追踪的方法、装置、电子设备

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 20850541

Country of ref document: EP

Kind code of ref document: A1

ENP Entry into the national phase

Ref document number: 2022507531

Country of ref document: JP

Kind code of ref document: A

NENP Non-entry into the national phase

Ref country code: DE

ENP Entry into the national phase

Ref document number: 20227007689

Country of ref document: KR

Kind code of ref document: A

122 Ep: pct application non-entry in european phase

Ref document number: 20850541

Country of ref document: EP

Kind code of ref document: A1