Calibration method, equipment and product of central catadioptric camera

Abstract

The invention discloses a calibration method, device and product of a central catadioptric camera, and relates to the technical field of computer vision, and the method comprises the steps: carrying out the processing of an obtained target image, and obtaining a first pixel coordinate and a second pixel coordinate; fitting the first pixel coordinates and the second pixel coordinates respectively to obtain an equation of an image of a straight line and an equation of an image of the mirror surface contour, and obtaining an image of the translated straight line and a corresponding vanishing line by adopting a common autopole three-point principle; and according to the image of the translated straight line and the corresponding vanishing line, internal parameters are recovered, and mirror surface parameters are recovered by utilizing the algebraic property of the image of the straight line. According to the method, only the central catadioptric camera needs to be used for shooting the target image including the image of at least two straight lines and the image of the mirror surface contour, and the internal parameters and the mirror surface parameters of the central catadioptric camera can be recovered based on the common self-pole three-point shape principle, so that the calculation complexity is reduced, and the calibration precision is improved.

Description

Technical Field

[0001] The present application relates to the field of computer vision technology, and in particular to a calibration method, device and product for a center catadioptric camera. Background Art

[0002] The main part of the center catadioptric system is the center catadioptric camera, which consists of an ordinary camera and a catadioptric mirror. Due to its advantages of single viewpoint and large field of view, the center catadioptric camera is widely used and integrated into many computer vision fields, such as navigation, robotics and remote sensing. The premise of the application of the center catadioptric camera is the calibration of the center catadioptric camera to restore the important internal parameters and mirror parameters of the center catadioptric camera. Like the camera calibration under the pinhole, the calibration methods of the center catadioptric camera are generally divided into two categories: one is the traditional self-calibration method, such as the calibration method using corresponding point pairs, which is easy to operate and optimize; the other is the calibration using objects, especially the calibration using geometric objects, such as using lines and balls, which has the characteristics of strong noise resistance and high calibration accuracy.

[0003] Straight lines and spheres are the main geometric calibration objects studied in central catadioptric reflection. Since the imaging process of a central catadioptric camera is described using a unit view sphere model, the projection of a straight line and a sphere onto the unit view sphere is a small circle and a large circle respectively, and the images of both are quadratic curves. Therefore, the image of a straight line and the image of a sphere have good geometric properties and are easy to extract and separate. At present, the prior art uses straight lines or spheres as geometric calibration objects, and has been studied from the following aspects:

[0004] On the one hand, many existing calibration algorithms and ideas in the pinhole camera model are extended to the calibration of the center catadioptric camera, because the imaging process of the center catadioptric camera and the ordinary pinhole camera is a single viewpoint; but in the center catadioptric, the image of the spherical image or the straight line is in double contact with the image of the modified absolute quadratic curve, and the modified camera intrinsic parameters obtained after the Cholesky decomposition of the image of the modified absolute quadratic curve still need to be further decomposed to recover the final camera intrinsic parameters and mirror parameters. On the other hand, the relationship between the poles and lines of the mirror contour and the spherical image and the image of the straight line is studied to recover the camera intrinsic parameters and mirror parameters. However, the poles and lines relationship corresponds to the orthogonal constraint and is greatly affected by noise; more spherical or straight line images are required. In addition, the use of the common self-polar triad in the calibration of the center catadioptric is also studied, because one vertex of the common self-polar triad of the spherical image and its corresponding antipodal spherical image is on the vanishing line, but the existing methods cannot linearly recover the camera intrinsic parameters and mirror parameters.

[0005] In general, the calibration methods of center catadioptric cameras in the prior art generally have the common disadvantages of high computational complexity and low precision, and it is even difficult to linearly restore the camera's internal parameters and mirror parameters. Summary of the invention

[0006] The purpose of this application is to provide a calibration method, device and product for a center catadioptric camera, which can reduce the computational complexity and improve the calibration accuracy.

[0007] To achieve the above objectives, this application provides the following solutions:

[0008] In a first aspect, the present application provides a calibration method for a center catadioptric camera, comprising:

[0009] Processing the acquired target image to obtain a first pixel coordinate and a second pixel coordinate; the first pixel coordinate is a pixel coordinate of an edge point of an image of a straight line, and the second pixel coordinate is a pixel coordinate of an edge point of an image of a mirror contour; the target image includes at least two images of straight lines and an image of a mirror contour;

[0010] Fitting the first pixel coordinate and the second pixel coordinate respectively to obtain the equation of the image of the straight line and the equation of the image of the mirror profile;

[0011] Based on the equation of the image of the straight line and the equation of the image of the mirror contour, the common autopolar triad principle is used to obtain the image of the translated straight line and the corresponding vanishing line;

[0012] According to the image of the translated straight line and the corresponding vanishing line, the intrinsic parameters of the center catadioptric camera are obtained;

[0013] Based on the intrinsic parameters of the center catadioptric camera and using the algebraic properties of the image of a straight line, the mirror parameters of the center catadioptric camera are restored.

[0014] In a second aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the center catadioptric camera calibration method.

[0015] In a third aspect, the present application provides a computer program product, including a computer program, which implements the calibration method of the center catadioptric camera when executed by a processor.

[0016] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0017] The present application provides a calibration method, device and product for a center catadioptric camera, the method comprising: processing an acquired target image to obtain a first pixel coordinate and a second pixel coordinate; the first pixel coordinate is the pixel coordinate of an edge point of an image of a straight line, and the second pixel coordinate is the pixel coordinate of an edge point of an image of a mirror profile; the target image comprises at least two images of straight lines and an image of a mirror profile; fitting the first pixel coordinate and the second pixel coordinate respectively to obtain an equation of the image of the straight line and an equation of the image of the mirror profile; based on the equation of the image of the straight line and the equation of the image of the mirror profile, using the common autopolar triplets principle, obtaining an image of the straight line after translation and a corresponding vanishing line; obtaining the intrinsic parameters of the center catadioptric camera according to the image of the straight line after translation and the corresponding vanishing line; based on the intrinsic parameters of the center catadioptric camera, using the algebraic properties of the image of the straight line, restoring the mirror parameters of the center catadioptric camera.

[0018] The present application only needs to use at least two straight lines in space to complete the target production, and the target production is simple; at the same time, the image of the straight line and the image of the mirror profile are fitted by using the least squares method to obtain the equation of the image of the straight line and the equation of the image of the mirror profile, so that their geometric characteristics can be determined with high precision, which helps to improve the accuracy of calibration. Moreover, by using the common autopolar three-point principle, by obtaining the image of the straight line after translation and the corresponding shadow elimination line, the intrinsic parameters of the camera can be determined more accurately; and the image of the straight line and the corresponding shadow elimination line are translated, which avoids the influence of noise that may exist in the camera calibration process and enhances the accuracy of calibration. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 This is an application environment diagram of a calibration method for a center catadioptric camera in one embodiment of the present application;

[0021] Figure 2 A schematic flow chart of a calibration method for a center catadioptric camera provided in one embodiment of the present application;

[0022] Figure 3 This is a schematic diagram of the imaging process of a straight line under a unit visual sphere model in one embodiment of the present application;

[0023] Figure 4 It is a schematic diagram of a process of obtaining a translated image of a straight line and a corresponding vanishing line from an image of a straight line and an image of a mirror profile in one embodiment of the present application;

[0024] Figure 5 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0026] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0027] The calibration method of the center catadioptric camera provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be set up separately, integrated on the server 104, or placed on the cloud or other servers. The terminal 102 can send the acquired target image to the server 104. After the server 104 receives the acquired target image, the server 104 processes the target image to obtain the first pixel coordinate and the second pixel coordinate; the first pixel coordinate and the second pixel coordinate are respectively fitted to obtain the equation of the image of the straight line and the equation of the image of the mirror contour, and the common self-polar three-point principle is used to obtain the image of the straight line after translation and the corresponding shadow elimination line; according to the image of the straight line after translation and the corresponding shadow elimination line, the internal parameters of the center catadioptric camera are obtained, and the mirror parameters of the center catadioptric camera are restored by using the algebraic properties of the image of the straight line. The server 104 can feedback the restored internal parameters and mirror parameters of the center catadioptric camera to the terminal 102. In addition, in some embodiments, the calibration method of the central catadioptric camera can also be implemented independently by the server 104 or the terminal 102. For example, the terminal 102 can directly perform calibration processing on the target image, or the server 104 can obtain the target image from the data storage system and perform calibration processing on the target image.

[0028] Among them, the terminal 102 can be but is not limited to various desktop computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices, and the server 104 can be implemented by an independent server or a server cluster composed of multiple servers, and can also be a cloud server.

[0029] In an exemplary embodiment, Figure 2 As shown, a calibration method for a center catadioptric camera is provided. The method is executed by a computer device, and can be executed by a computer device such as a terminal or a server alone, or by a terminal and a server together. In the embodiment of the present application, the method is applied to Figure 1 The server 104 in the example is used as an example to illustrate the method, which includes the following steps 201 to 208. Among them:

[0030] Step 201, processing the acquired target image to obtain first pixel coordinates and second pixel coordinates; the first pixel coordinates are the pixel coordinates of the edge points of the image of the straight line, and the second pixel coordinates are the pixel coordinates of the edge points of the image of the mirror contour; the target image includes at least two straight line images and a mirror contour image.

[0031] Further, the acquired target image is processed to obtain the first pixel coordinate and the second pixel coordinate, specifically including:

[0032] Step 2011, acquiring a target image; the target image is an image obtained by photographing the target using a center catadioptric camera, and the target includes at least two straight lines in space.

[0033] Take the imaging process of a straight line in space under a central catadioptric camera as an example: According to the unit view sphere model, the imaging process of a straight line under a central catadioptric camera is as follows: Figure 3 As shown. Line L and point M on the line, with the center of the unit sphere O s The perspective center is projected onto the great circle C on the surface of the unit visual sphere. s and point M s ; Then take the virtual camera optical center O at a distance of ξ units c is the perspective center, projected to the principal point O p The quadratic curve C and point m on the image plane π. c With O s Located on the optical axis, ξ is the mirror parameter of the central catadioptric camera, π s =[n x n y n z 0] is the center of the sphere O s The plane formed by the straight line L, the world coordinate system OX w Y w Z w and the unit spherical coordinate system O s -X s Y s Z s Phase difference rotation R and translation T, O c -X c Yc Z c is the virtual camera coordinate system. c The intrinsic parameter matrix of the virtual camera with the optical center is Among them, [u0v0] T is the principal point O of the central catadioptric camera p The non-homogeneous coordinates of u and f v is the scale factor in the u and v axis directions of the target image plane, and s is the distortion factor. v ,f u ,u0,v0,s are the intrinsic parameters and mirror parameters of the central catadioptric camera that need to be solved.

[0034] Step 2012: Use the Edge function in the MATLAB program to extract the first pixel coordinates and the second pixel coordinates in the target image.

[0035] Step 202 , fitting the first pixel coordinates and the second pixel coordinates respectively to obtain the equation of the image of the straight line and the equation of the image of the mirror profile.

[0036] Further, the least square method is used to fit the first pixel coordinate and the second pixel coordinate respectively to obtain the equation of the image of the straight line and the equation of the image of the mirror profile, both of which are 3×3 real symmetric matrices. In this application, C0 represents the equation of the image of the mirror profile, and C1 and C2 represent the equations of the images of two straight lines in the target image, respectively.

[0037] Step 203, based on the equation of the image of the straight line and the equation of the image of the mirror profile, the common autopolar triad principle is used to obtain the image of the translated straight line and the corresponding vanishing line.

[0038] Furthermore, the image equation of the straight line includes the image equation of the first straight line and the image equation of the second straight line; the image equation of the straight line and the image equation of the mirror profile are based on the common autopolar triad principle to obtain the image of the translated straight line and the corresponding vanishing line, specifically including:

[0039] Step 2031, according to the common autopolar triad principle, the equation of the image of the first straight line, the equation of the image of the second straight line and the equation of the image of the mirror profile are processed to obtain the first generalized eigenvector and the second generalized eigenvector; the equation of the image of the mirror profile and the first generalized eigenvector are calculated to obtain the first straight line; and the equation of the image of the mirror profile and the second generalized eigenvector are calculated to obtain the second straight line; the first straight line and the second straight line intersect at the principal point.

[0040] like Figure 4As shown, the equation C1 of the image of the first straight line, the equation C2 of the image of the second straight line, and the equation C0 of the image of the mirror profile are taken as examples. According to the common autopolar triad principle, one side of the common autopolar triad of the image equation of the straight line and the image equation of the mirror profile passes through the principal point O. p According to the principle of matching poles, we need to restore the vertex E of the common polar triad of the image of the mirror contour and the image of the straight line on the vanishing line before translation. i , which satisfies

[0041] (λ 0i C0-C i )x i =0 (1);

[0042] Among them, λ 0i (i=1,2) is C0, C i A generalized eigenvalue with a different sign from other generalized eigenvalues, and its corresponding generalized eigenvector x i C0, C i The vertex E of the common autopolar triad on the shadow vanishing line i The homogeneous coordinates of .

[0043] Then the straight line l passing through the principal point Ei It is obtained by the following formula:

[0044] l Ei =C0E i (2);

[0045] Equations of images of at least two straight lines C i (i=1,2) get two straight lines l passing through the principal point Ei , they intersect to recover the principal point O p (the intersection of two straight lines), that is:

[0046] O p = l E1 × E2 (3).

[0047] Step 2032: determine the principal point information according to the first straight line and the second straight line, and construct a translation matrix containing the principal point information according to the principal point information.

[0048] Step 2033, determining the image of the translated straight line and the corresponding vanishing line according to the translation matrix containing the principal point information.

[0049] Specifically, the image C of the translated straight line ip And the corresponding vanishing line l ip The determination process is expressed by the following formula:

[0050]

[0051] Among them, T p is the translation matrix containing the principal point information, expressed as:

[0052]

[0053] Step 204, obtaining the intrinsic parameters of the center catadioptric camera according to the image of the translated straight line and the corresponding vanishing line.

[0054] Furthermore, according to the image of the translated straight line and the corresponding vanishing line, the intrinsic parameters of the central catadioptric camera are obtained, which specifically include:

[0055] Step 2041, intersecting the image of the translated straight line with the vanishing line corresponding to the image of the translated straight line, to obtain the image constraint of the absolute quadratic curve without principal point information;

[0056] Then the image C of the translated line is ip The vanishing line l corresponding to the image of the translated straight line ip Intersection, we get the system of equations:

[0057]

[0058] And by solving the equations, we can get the simplified image m of the ring point Iip , m Jip , which provide two constraints on the image of an absolute quadratic curve without principal point information:

[0059]

[0060] The least square solution of the constraint of the image of the absolute quadratic curve without the principal point information is the image ω of the absolute quadratic curve without the principal point information. p , specifically:

[0061]

[0062] Step 2042, the image ω of the absolute quadratic curve without principal point information is decomposed and then inverted by Cholesky decomposition. p Processing, restore the internal parameter matrix K without principal point information p , the internal parameter matrix K without principal point information p The manifestation is:

[0063]

[0064] Step 2043, the translation matrix containing the principal point information and the intrinsic parameter matrix without the principal point information are combined to obtain the intrinsic parameter K of the center catadioptric camera. The intrinsic parameter K of the center catadioptric camera is defined as:

[0065] K=T p K p (11).

[0066] Since the image of the absolute quadratic curve without the principal point information has only three degrees of freedom, the image of the absolute quadratic curve without the principal point information is restored by the images of at least two straight lines. Equation group (8) is equivalent to the following constraints on the image of the absolute quadratic curve, namely:

[0067]

[0068] Among them, Re and Im represent the real part and imaginary part of the number respectively. Let m Iip =(m i1 ,m i2 ,1) T , then we can write equation (12) as

[0069]

[0070] in, C 6×1 =[w 11 ,w 12 ,w 22 ,w 13 ,w 23 ,w 33 ] T The images of the two translated lines and the corresponding vanishing lines of the images of the two translated lines provide four constraints on the images of the absolute quadratic curves without the principal point information, that is, the least squares solution of the two equations (13) is to obtain the image of the absolute quadratic curve without the principal point information. According to formula (9), p Perform Cholesky decomposition and then invert it, that is, restore the intrinsic parameter matrix K without principal point information p ; Finally, the intrinsic parameter K of the center catadioptric camera is restored by formula (11).

[0071] Step 205: Based on the intrinsic parameters of the center catadioptric camera and using the algebraic properties of the image of a straight line, restore the mirror parameters of the center catadioptric camera.

[0072] Furthermore, based on the intrinsic parameters of the center catadioptric camera, the mirror parameters of the center catadioptric camera are restored by using the algebraic properties of the image of a straight line, which specifically includes:

[0073] Step 2051, the viewing cone of the image of the straight line is calculated from the intrinsic parameters of the central catadioptric camera and the equation of the image of the straight line, that is,

[0074] Q i =K T C iK(i=1,2) (14);

[0075] The mirror parameters of the central catadioptric camera are calculated based on the view cone of the image of the straight line. Since the image of each straight line has mirror parameters, the equation C of the image of the straight line is assumed to be i (i=1,2) The mirror parameter obtained is ξ i , then the mirror parameter ξ i satisfy

[0076]

[0077] Among them, Q i,j is the element in the i-th row and j-th column of Q.

[0078] And the mirror parameter ξ obtained from the image of each straight line i To optimize the mirror parameters of the center catadioptric camera, the mirror parameters of the center catadioptric camera are:

[0079]

[0080] This application proposes a method for solving the internal parameters and mirror parameters of an arbitrary center refractive-reflective camera by using the double contact principle of straight lines in space and the common self-polar three-point shape principle. The calibration template is at least two straight lines in space. The implementation scheme of this application is described in more detail below with reference to a specific example, which uses two straight lines as the calibration template. The specific calibration method is as follows:

[0081] The image equation of the straight line and the image equation of the mirror profile: The target image size used in this application is 4000×2000. Use a central catadioptric camera to shoot a target image including two straight lines in space, obtain the target image, use the Canny operator of the Edge function in MATLAB to extract the pixel coordinates of the edge points of the straight line image and the edge points of the mirror profile image, and use the least squares method to fit to obtain the image equation of the straight line and the image equation of the mirror profile. The image equation of the mirror profile C0 and the image equation of the two straight lines are C respectively. i (i=1,2), the calculation is performed in matrix form, and the results are as follows:

[0082]

[0083] Recover the intrinsic parameters and mirror parameters of the central catadioptric camera: According to the common self-polar triplet principle, the generalized eigenvalues ​​λ of C0 and C1 with different signs from other generalized eigenvalues ​​are solved by simultaneously using equations (1), (17) and (18) 01 =0.872604314052497, and its corresponding generalized eigenvector, which is the vertex of the common autopolar triplet of C0 and C1 on the vanishing line before translation:

[0084] E1=[-5.55144334231516e+16 -3.55286689321164e+16 1] T (20).

[0085] The simultaneous equations (1), (17) and (19) are used to solve the generalized eigenvalues ​​λ of C0 and C2 that have different signs from other generalized eigenvalues. 02 =5.18794539088453, and its corresponding generalized eigenvector, which is the vertex of the common autopolar triplet of C0 and C2 on the vanishing line before translation:

[0086] E2=[47650065078699.8 -19060216630384.1 1] T (twenty one).

[0087] Then, combining equations (2) and (20), the straight line passing through the principal point is:

[0088] l E1 =C0E1=[78202161.1787841 78200206.1249469 -234604528482.073] T (twenty two).

[0089] Combining equations (2) and (21), the straight line passing through the principal point is:

[0090] l E2 =C0E2=[-399085.247322148 249438.259477936 548732242.696992] T (twenty three).

[0091] Will l E1 and l E2 Connect, and use formula (3) to recover the main point:

[0092] O p = l E1 × E2 =[2000.00001160968 999.999988384379 1] T (twenty four).

[0093] Then according to formula (6), the translation matrix containing the principal point information is:

[0094]

[0095] Then, according to formula (4), the image C of the translated straight line is ip (i=1,2) are:

[0096]

[0097] And according to formula (5), the image C of the translated straight line is ip The corresponding vanishing line l ip They are:

[0098]

[0099] Combining equations (7), (26) to (29), we can get the image C of the translated line ip (i=1,2) and the corresponding vanishing line l ip Intersection is to restore the image ω of two pairs of absolute quadratic curves without principal point information p Constraints, that is, the system of equations:

[0100]

[0101] Where x is a three-dimensional column vector, and the solutions of equations (30) and (31) are two pairs of simplified images of circular points m Iip ,m Jip (i=1,2), that is

[0102]

[0103] Combining equations (8), (40) and (41), we obtain the image constraint of the absolute quadratic curve without principal point information, namely:

[0104]

[0105] Similarly, transforming equation (8) into equation (13), transform equation (34) and solve it. The least squares solution of equation (34) is the absolute quadratic curve without principal point information. p Like, that is

[0106]

[0107] According to formula (9), p Perform Cholesky decomposition and then invert to restore the intrinsic parameter matrix without principal point information, that is,

[0108]

[0109] Finally, the combined equations (11), (25) and (36) recover the intrinsic parameters of the central catadioptric camera, namely

[0110]

[0111] After restoring the camera internal parameter matrix, the image C of the straight line is obtained by equation (14): iThe viewing cone of (i=1,2)

[0112]

[0113] Then the image C of the straight line i The obtained mirror parameters are ξ1=0.200000001240735 and ξ2=0.200000000518902, so the final mirror parameter is ξ=(ξ1+ξ2) / 2=0.200000000879818.

[0114] The present application also provides an application scenario, and the application scenario applies the above-mentioned center catadioptric camera calibration method. Specifically: the center catadioptric camera calibration method provided in this embodiment can be applied in the center catadioptric camera calibration scenario.

[0115] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 5 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store calibration data of a center refractive index camera. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a calibration method for a center refractive index camera is implemented.

[0116] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0117] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0118] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0119] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0120] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0121] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0122] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A calibration method for a center catadioptric camera, characterized in that: The calibration method of the central catadioptric camera comprises: Processing the acquired target image to obtain a first pixel coordinate and a second pixel coordinate; the first pixel coordinate is a pixel coordinate of an edge point of an image of a straight line, and the second pixel coordinate is a pixel coordinate of an edge point of an image of a mirror contour; the target image includes at least two images of straight lines and an image of a mirror contour; Fitting the first pixel coordinate and the second pixel coordinate respectively to obtain the equation of the image of the straight line and the equation of the image of the mirror profile; Based on the equation of the image of the straight line and the equation of the image of the mirror contour, the common autopolar triad principle is used to obtain the image of the translated straight line and the corresponding vanishing line; According to the image of the translated straight line and the corresponding vanishing line, the intrinsic parameters of the center catadioptric camera are restored; Based on the intrinsic parameters of the center catadioptric camera and using the algebraic properties of the image of a straight line, the mirror parameters of the center catadioptric camera are restored.

2. The calibration method of the center catadioptric camera according to claim 1, characterized in that: The processing of the acquired target image to obtain the first pixel coordinate and the second pixel coordinate specifically includes: Acquire a target image; the target image is an image obtained by photographing the target using a center catadioptric camera, and the target includes at least two straight lines in space; The Edge function in the MATLAB program is used to extract the first pixel coordinates and the second pixel coordinates in the target image.

3. The calibration method of the center catadioptric camera according to claim 1, characterized in that: The first pixel coordinate and the second pixel coordinate are fitted respectively to obtain the equation of the image of the straight line and the equation of the image of the mirror profile, specifically including: The first pixel coordinate and the second pixel coordinate are fitted respectively by using the least square method to obtain the equation of the image of the straight line and the equation of the image of the mirror profile.

4. The calibration method of a center catadioptric camera according to claim 1, characterized in that: The image equation of the straight line includes the image equation of the first straight line and the image equation of the second straight line; the image equation of the straight line and the image equation of the mirror profile are based on the common autopolar tripoint principle to obtain the image of the translated straight line and the corresponding vanishing line, specifically including: According to the common autopolar triad principle, the equation of the image of the first straight line, the equation of the image of the second straight line and the equation of the image of the mirror profile are processed to obtain the first straight line and the second straight line; the first straight line and the second straight line intersect at the principal point; Determine principal point information according to the first straight line and the second straight line, and construct a translation matrix containing the principal point information according to the principal point information; According to the translation matrix containing the principal point information, the image of the translated straight line and the corresponding vanishing line are determined.

5. The calibration method of the center catadioptric camera according to claim 4, characterized in that: The method of processing the image equation of the first straight line, the image equation of the second straight line and the image equation of the mirror profile according to the common self-polar three-point principle to obtain the first straight line and the second straight line specifically includes: According to the common autopolar triad principle, the equation of the image of the first straight line, the equation of the image of the second straight line and the equation of the image of the mirror profile are processed to obtain the first generalized eigenvector and the second generalized eigenvector; Calculating the equation of the image of the mirror profile and the first generalized eigenvector to obtain a first straight line; The equation of the image of the mirror profile and the second generalized eigenvector are calculated to obtain a second straight line.

6. The calibration method of a center catadioptric camera according to claim 5, characterized in that: The method of restoring the intrinsic parameters of the center catadioptric camera according to the image of the translated straight line and the corresponding vanishing line specifically includes: The image of the translated straight line is intersected with the vanishing line corresponding to the image of the translated straight line to obtain the image constraint of the absolute quadratic curve without the principal point information; The image of the absolute quadratic curve without principal point information is processed by using a Cholesky decomposition and then inversion method to restore the internal parameter matrix without principal point information; the image of the absolute quadratic curve without principal point information is a constrained least square solution of the image of the absolute quadratic curve without principal point information; The translation matrix containing the principal point information and the intrinsic parameter matrix not containing the principal point information are combined to restore the intrinsic parameters of the center catadioptric camera.

7. The calibration method of a center catadioptric camera according to claim 1, characterized in that: The method of restoring the mirror parameters of the center catadioptric camera based on the intrinsic parameters of the center catadioptric camera and utilizing the algebraic properties of the image of a straight line specifically includes: According to the internal parameters of the central catadioptric camera and the equation of the image of the straight line, the viewing cone of the image of the straight line is calculated, and the mirror parameters of the central catadioptric camera are restored according to the viewing cone of the image of the straight line.

8. The calibration method of a center catadioptric camera according to claim 7, characterized in that: The visual cone of the image of the straight line is calculated by the internal parameters of the central catadioptric camera and the equation of the image of the straight line. The specific process is: According to the formula Q i =K T C i K(i=1,2) calculates the viewing cone of the image of the straight line; Among them, Q i is the viewing cone of the image of the straight line, C i is the image equation of the i-th line, K is the internal parameter of the central catadioptric camera, K T is the transpose of the intrinsic parameters of the center catadioptric camera.

9. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the calibration method for a center catadioptric camera according to any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the calibration method of the center catadioptric camera described in any one of claims 1 to 7 is implemented.

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