CN112465912A - Three-dimensional camera calibration method and device - Google Patents
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Abstract
The invention discloses a method and a device for calibrating a stereo camera, wherein the method comprises the following steps: providing a speckle calibration plate; placing the speckle calibration plate in an imaging range of a binocular stereo camera to acquire at least 16 speckle calibration images; measuring the physical distances of the plurality of coding points, and dividing the speckle calibration plate into virtual grid lattices according to the physical distances to obtain coordinates of calibration three-dimensional points on the speckle calibration plate; taking any speckle calibration image as a reference image, extracting the center of a coding point on the reference image, and dividing according to pixel distance to obtain the coordinates of a calibration two-dimensional point on the reference image; calculating a pose transformation matrix of the whole image for other non-reference images; obtaining the coordinates of the calibration two-dimensional points on each non-reference image according to the pose transformation matrix; and establishing an imaging mapping relation by adopting the coordinates of the calibration three-dimensional points and the coordinates of the calibration two-dimensional points, and calculating the internal and external parameters of the binocular stereo camera. The invention realizes the calibration of the high-precision stereo camera.
Description
Technical Field
The invention relates to the technical field of three-dimensional camera calibration in machine vision, in particular to a three-dimensional camera calibration method and device based on speckle patterns.
Background
The calibration of stereo cameras is to determine the intrinsic and extrinsic parameters of each camera in a camera system and the relative extrinsic parameters between the cameras, and this process is usually performed by means of a specially made calibration target surface, also called calibration board. The calibration plate is provided with specially designed patterns, such as currently commonly used circular grid dot matrixes or coding feature points, and the stereo camera acquires calibration plate images with the feature point patterns in different directions during calibration, and parameter calculation of the stereo camera can be realized through corresponding image processing and optimization algorithms to complete calibration. However, the method based on feature point pattern calibration has some disadvantages, firstly, the requirement on the processing precision of the feature points on the calibration plate is very high, and the edge processing of the circular feature points has inherent discretization defects; secondly, the extraction precision of the feature points is low, and particularly, the problem is more prominent under the conditions of uneven illumination or environmental vibration and the like on a calibration image, so that the calibration is unstable; in addition, the number of feature points on each calibration board is limited due to the required manufacturing size of each feature point, which also causes a bottleneck in the calibration accuracy to some extent.
The above background disclosure is only for the purpose of assisting understanding of the concept and technical solution of the present invention and does not necessarily belong to the prior art of the present patent application, and should not be used for evaluating the novelty and inventive step of the present application in the case that there is no clear evidence that the above content is disclosed at the filing date of the present patent application.
Disclosure of Invention
In order to solve the technical problems, the invention provides a three-dimensional camera calibration method based on speckle patterns, and high-precision three-dimensional camera calibration and a device are realized.
In order to achieve the purpose, the invention provides the following technical scheme:
the invention discloses a three-dimensional camera calibration method based on speckle patterns, which comprises the following steps:
s1: providing a speckle calibration plate, wherein a speckle pattern and a plurality of coding points are arranged on the speckle calibration plate;
s2: placing the speckle calibration plate in an imaging range of a binocular stereo camera, and collecting at least 8 different directions by using the binocular stereo camera to obtain at least 16 speckle calibration images;
s3: measuring the physical distances of a plurality of coding points, and dividing the speckle calibration plate into virtual grid lattices of i rows by j columns according to the physical distances to obtain the coordinates of a calibration three-dimensional point Pw on the speckle calibration plate;
s4: taking any speckle calibration image of the at least 16 speckle calibration images obtained in the step S2 as a reference image, extracting the center of the encoding point on the reference image, and dividing the encoding point into i rows × j columns according to the pixel distance to obtain the coordinates of a calibration two-dimensional point Pm on the reference image;
s5: calculating a pose transformation matrix Q of the whole image according to the centers of the encoding points of the reference image and the current non-reference image for the other non-reference images except the reference image in the at least 16 speckle calibration images obtained in the step S2;
s6: obtaining the coordinates of a calibration two-dimensional point Pm on each non-reference image according to the pose transformation matrix Q;
s7: and establishing an imaging mapping relation by adopting the coordinates of the calibration three-dimensional point Pw on the speckle calibration plate and the coordinates of the calibration two-dimensional point Pm on all speckle calibration images, and calculating the internal and external parameters of the binocular stereo camera according to the imaging mapping relation.
Preferably, in step S1, the speckle calibration plate is rectangular, and the plurality of encoding points includes 4 encoding points located at four vertices of the speckle calibration plate.
Preferably, the at least 8 orientations include at least first to eighth orientations, wherein the center of the speckle calibration plate is used as a reference position, and when the optical axis of the binocular stereo camera is aligned with the center of the speckle calibration plate at a first position, the speckle calibration plate is moved back and forth within a depth of field range to form a first orientation and a second orientation, so that the optical axis of the binocular stereo camera and the center of the speckle calibration plate form a third orientation and a fourth orientation respectively at left and right within a tilt angle range of 5-15 degrees; and when the speckle calibration plate is vertically turned 180 degrees in a plane from the first position to the second position, the speckle calibration plate is moved back and forth within the depth of field range to form a fifth azimuth and a sixth azimuth, so that the optical axis of the binocular stereo camera and the center of the speckle calibration plate form a seventh azimuth and an eighth azimuth respectively at the left and right sides within the inclination angle range of 5-15 degrees.
Preferably, the step S3 further includes aligning a world coordinate system to the center of the speckle calibration plate, and obtaining coordinates of a calibration three-dimensional point Pw on the speckle calibration plate as (± i/2 · Δ w, ± j/2 · Δ h, 0), where Δ w ═ w/(i-1) is a horizontal equally-divided interval of the encoding points, Δ h ═ h/(j-1) is a vertical equally-divided interval of the encoding points, and w and h are horizontal physical distances and vertical physical distances of a plurality of the encoding points, respectively.
Preferably, the coordinates of the calibrated two-dimensional point Pm on the reference image obtained in step S4 are (± i/2 · Δ l, ± j/2 · Δ b), where Δ l/(i-1) is the horizontal equally-divided interval of the encoded point on the reference image, Δ b/(b-1) is the vertical equally-divided interval of the encoded point on the reference image, and l and b are the horizontal pixel distance and the vertical pixel distance of the encoded point on the reference image, respectively.
Preferably, in step S5, the pose transformation matrix Q of the entire image is calculated from the centers of the encoding points of the reference image and the current non-reference image (a)TA)-1ATAnd B, wherein A is a matrix formed by the coding points on the reference image, and B is a matrix formed by the coding points on the current non-reference image.
Preferably, the step S6 specifically includes obtaining coordinates p ' (x ') of the estimated position of the calibrated two-dimensional point Pm on each non-reference image according to the pose transformation matrix Q 'i,j,y′i,j)＝p(xi,j,yi,j) Q, and searching and matching by digital image correlation, wherein p (x)i,j,yi,j) And the coordinates of the calibration two-dimensional points on the reference image are obtained.
Preferably, the searching and matching by the digital image correlation method specifically comprises:
obtaining the coordinates p ' (x ') of the calibration two-dimensional point Pm on each non-reference image by adopting the pose transformation matrix Q 'i,j,y′i,j) As an initial value of a calibration two-dimensional point Pm, performing search calculation by using a cross-correlation function to perform first matching; and then, taking the result of the first matching as an initial value, and combining a least square method square sum coefficient, a sub-pixel interpolation algorithm and a deformation affine transformation function to complete sub-pixel level matching and tracking of the calibration two-dimensional points to obtain the coordinates of the matched calibration two-dimensional points.
Preferably, in step S7, the imaging mapping relationship established by using the coordinates of the calibration three-dimensional point Pw on the speckle calibration plate and the coordinates of the calibration two-dimensional point Pm on all speckle calibration images is:
wherein eta is1～η8Is a vector parameter, (x)i,j，yi,j) Coordinates of a calibration three-dimensional point Pw on the speckle calibration plate, (X)i,j，Yi,j) Coordinates of a calibration two-dimensional point Pm on the speckle calibration image are obtained;
calculating to obtain a vector parameter eta according to the coordinates of the calibration three-dimensional point Pw on the speckle calibration plate and the coordinates of the calibration two-dimensional point Pm on all speckle calibration images1～η8According to the vector parameter η1～η8And calculating to obtain the internal and external parameters of the binocular stereo camera.
Preferably, step S7 further includes: and adjusting the calculated internal and external parameters of the binocular stereo camera by adopting a binding adjustment algorithm to obtain a calibration parameter result of the binocular stereo camera.
Preferably, the adjusting the calculated internal and external parameters of the binocular stereo camera by using the binding adjustment algorithm to obtain the calibration parameter result of the binocular stereo camera specifically includes: according to an error optimization equation of a reference camera and a non-reference camera, combining a nonlinear global binding adjustment algorithm, adding a scale, and iterating to obtain a calibration parameter result of the binocular stereo camera; wherein the error optimization equation of the reference camera is:
VL＝ALX1L+BLX2L+CLX3L-L
the error optimization equation of the non-reference camera is as follows:
VR＝ARX1R+BRX2R+CRX3R+DRX4R-L
in the formula, X1L,X2L,X3LRespectively an inner orientation parameter, an outer orientation parameter and a correction number of a calibration three-dimensional point coordinate of the reference camera; a. theL,BL,CLRespectively corresponding partial derivative matrixes of the internal parameter, the external parameter and the calibration three-dimensional point coordinate of the reference camera; l is the deviation of the actual value and the initial value of the observation; x1R,X2R,X3RRespectively the inner orientation parameter, the outer orientation parameter and the correction number of the coordinate of the calibrated three-dimensional point, X of the non-reference camera4RIs the number of corrections to the relative extrinsic parameters of the non-reference camera relative to the reference camera; a. theR,BR,CRPartial derivative matrixes of the coordinates of the image points of the non-reference camera to the coordinates of the internal parameters, the external parameters and the calibration three-dimensional points of the reference camera respectively, DRIs a matrix of partial derivatives of the coordinates of the image points of the non-reference camera with respect to their own relative extrinsic parameters.
The invention also discloses a calibration device of the stereo camera, which comprises:
the device comprises a first unit, a second unit and a third unit, wherein the first unit is configured to provide a speckle calibration plate, and a speckle pattern and a plurality of encoding points are arranged on the speckle calibration plate;
the second unit is configured to place the speckle calibration plate in an imaging range of a binocular stereo camera, and the binocular stereo camera is adopted to collect images in at least 8 different directions to obtain at least 16 speckle calibration images;
the third unit is configured to measure physical distances of the plurality of coding points, divide the speckle calibration plate into virtual grid lattices of i rows by j columns according to the physical distances, and obtain coordinates of calibration three-dimensional points Pw on the speckle calibration plate, wherein i and j are positive integers respectively;
a fourth unit, configured to take any one of the at least 16 speckle calibration images obtained by the second unit as a reference image, extract the center of the encoding point on the reference image, and divide the encoding point into i rows × j columns according to the pixel distance to obtain the coordinates of a calibration two-dimensional point Pm on the reference image;
a fifth unit, configured to calculate, for at least 16 speckle calibration images obtained by the second unit, a pose transformation matrix Q of the entire image according to centers of the encoding points of the reference image and the current non-reference image, for other non-reference images except the reference image;
a sixth unit, configured to obtain coordinates of a calibration two-dimensional point Pm on each non-reference image according to the pose transformation matrix Q;
and the seventh unit is configured to establish an imaging mapping relation by adopting the coordinates of the calibration three-dimensional point Pw on the speckle calibration plate and the coordinates of the calibration two-dimensional point Pm on all speckle calibration images, and calculate the internal and external parameters of the binocular stereo camera according to the imaging mapping relation.
Compared with the prior art, the invention has the beneficial effects that: the invention provides a three-dimensional camera calibration method and a device based on speckle patterns, which are characterized in that a small number of speckle calibration patterns of linear coding points are designed, and three-dimensional coordinates of dense scattered spots are utilized to form virtual grid angular points; the stereo camera system collects a plurality of speckle images in different directions, and tracks corresponding two-dimensional points on the images by using a digital image correlation matching algorithm, so that initial values of internal and external parameters of the camera can be calculated through the sequence three-dimensional points and the two-dimensional points; and then, integrally optimizing the initial value of the camera model under the relative external parameters by using a binding adjustment algorithm, thereby realizing high-precision calibration of the stereo camera. The invention effectively avoids the problems of feature point detection precision and limited calculation point number when the stereo camera is calibrated at different types and different zoom magnifications, and greatly improves the calibration precision and stability of the stereo camera.
On one hand, the three-dimensional camera calibration method and device based on the speckle patterns improve the calibration precision of the three-dimensional camera to a great extent; accurate initial values of internal and external parameters of the stereoscopic camera are obtained through calibration, and the average reprojection error of imaging is reduced; meanwhile, the processing precision requirement of the calibration plate is reduced, and the manufacturing cost of the calibration plate is saved. On the other hand, the three-dimensional camera calibration method and device based on the speckle patterns also improve the stability of the three-dimensional camera calibration; the method has strong resistance to the problems of uneven illumination and environmental vibration, is suitable for stereo camera systems with different zoom ratios, such as a stereo microscope system consisting of a binocular camera and a stereo microscope, and also has a certain fault tolerance to the problems of defocusing during imaging of telecentricity, long focus and small focal depth; in addition, a small number of linear coding points can improve the point matching speed and the calibration efficiency.
Drawings
FIG. 1 is a flow chart of a three-dimensional camera calibration method based on speckle patterns according to the preferred embodiment of the present invention;
FIG. 2 is an example of a speckle pattern for a method for calibrating a stereo camera based on a speckle pattern according to an embodiment of the present invention;
FIG. 3a is a coding method in the calibration method of the stereo camera based on the speckle pattern according to the embodiment of the present invention;
3 b-3 f are examples of various linear encoding point designs in the three-dimensional camera calibration method based on speckle patterns according to the embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating a calibration relationship of a stereo camera system of the speckle pattern-based stereo camera calibration method according to an embodiment of the present invention;
FIG. 5 is a calculation example of calibrating three-dimensional points in the calibration method of the stereo camera based on the speckle pattern according to the embodiment of the present invention;
FIG. 6 is a calculation example of calibrating two-dimensional points in the three-dimensional camera calibration method based on speckle patterns according to the embodiment of the present invention;
fig. 7 is a schematic diagram illustrating calculation of an affine transformation matrix between images in the speckle pattern-based stereo camera calibration method according to the embodiment of the present invention;
FIG. 8 is a schematic diagram illustrating the matching of speckle points in the calibration method for a stereo camera based on speckle patterns according to an embodiment of the present invention by a digital image correlation method;
fig. 9 is a schematic diagram illustrating a mapping relationship between a plurality of groups of calibration three-dimensional points and calibration two-dimensional points in the speckle pattern-based stereo camera calibration method according to the embodiment of the present invention.
Detailed Description
The invention will be further described with reference to the accompanying drawings and preferred embodiments.
As shown in fig. 1, a preferred embodiment of the present invention discloses a three-dimensional camera calibration method based on speckle patterns, which includes the following steps:
s1: preparing a planar speckle calibration plate, wherein the whole body consists of a speckle pattern and a small number of coding points;
specifically, the calibration plate is rectangular or square, black and white speckle patterns are sprayed on the surface of the calibration plate, the black and white proportion in the patterns is about 50% respectively, the diameters of the speckles are moderate (the actual diameters to be sprayed are different according to different breadths, but the optimal diameter on imaging is 3-6 pixels), and the calibration plate is free of agglomeration, light reflection and cracking. The number of the encoding points is required to be less, and generally is not more than 5 (namely, the encoding points are located at four vertexes of the speckle calibration plate and 5 encoding points located at the central point of the speckle calibration plate), each encoding point has a unique ID number, is easy to identify and has position, rotation and scale invariance.
S2: placing the speckle pattern of the planar speckle calibration plate in an imaging range of a binocular stereo camera, and collecting the speckle pattern in 8 different directions by using the binocular stereo camera to obtain at least 16 speckle calibration images;
specifically, according to the focal length and the measurement breadth of a binocular stereo camera system, the space, the solid angle and the like of a stereo camera are adjusted, firstly, a speckle calibration plate is placed in the depth of field range parallel to a camera base line, and the center Ow of the speckle calibration plate is used as a reference position, so that the optical axis of the stereo camera is aligned to the Ow; starting image acquisition by taking the alignment position as an initial position, acquiring more than 4 images by moving the calibration plate back and forth within the range of depth of field, and respectively acquiring more than 2 images at an inclination angle of 5-15 degrees with the optical axis; then vertically turning the calibration plate by 180 degrees in a plane, moving the calibration plate back and forth within the range of depth of field to collect more than 4 images, and respectively collecting more than 2 images at an inclination angle of 5-15 degrees with the optical axis; the above 16 images were acquired in a total of more than 8 different orientations.
S3: aligning a world coordinate system to the center of a speckle calibration plate, measuring the physical distance of coding points, dividing the calibration plate into virtual grid lattices of i rows multiplied by j columns according to the physical distance, and calculating to obtain calibration three-dimensional points Pw, wherein i and j are respectively positive integers, theoretically, i and j can be arbitrarily valued according to actual conditions, and in a specific embodiment, i and j are respectively preferably 23-50;
and recording a world coordinate system W, aligning the world coordinate system of the speckle calibration plate to the center of the plane of the speckle calibration plate, wherein the normal direction of the plane is a Z axis, and then coordinates of all points on the speckle calibration plate are as follows:
W＝(XW,YW,0)
defining the relationship from the world coordinate system W to the optical center coordinate system O of the camera as:
O＝RW+t
wherein R is a rotation parameter, and t is a translation parameter;
recording that the horizontal physical distance and the vertical physical distance of the code point obtained by measurement are w and h respectively, and the halving array is i multiplied by j, then the horizontal halving interval delta w and the vertical halving interval delta h are as follows:
the obtained point three-dimensional coordinate Pw of any index number i, j is:
s4: extracting the center of a coding point of the first image, and dividing the coding point into i rows and x j columns according to the pixel distance to obtain a calibration two-dimensional point Pm to be matched on the two-dimensional image;
in the same way as the calculation method of the three-dimensional coordinate Pw, the horizontal pixel distance and the vertical pixel distance between the coding points on the image are respectively l and b, the equal division array is i × j, and then the horizontal equal division distance Δ l and the vertical equal division distance Δ b are:
the coordinate of the two-dimensional coordinate Pm of the index point with any index number i, j is obtained as follows:
s5: for speckle calibration images obtained from other different directions, calculating a pose transformation matrix Q of the whole image by using the first image and the coding center point of the current image;
for more than 16 calibration images acquired in step S2, because the images are acquired at different orientations, there exists an approximate affine transformation between the images as a whole, and the transformation parameter matrix is denoted as Q and includes a rotation parameter matrix M and a translation parameter matrix d, that is:
Q＝[M|d]
extracting image coordinates of the coding points on the images, if the images have n coding points, obtaining two-dimensional coordinates of the n coding points on the two images, and respectively recording the two-dimensional coordinates as (x)f1,yf1)～(xfn,yfn) And (x'f1,y′f1)～(x′fn,y′fn) (ii) a The calibration plate can be regarded as a transmission projection relation among the encoding points on the images shot at different angles, namely, a mapping relation can be obtained through affine transformation, so that affine transformation exists among n encoding points on each image:
the above formula can be abbreviated as:
AQ＝B
wherein the content of the first and second substances,
a is a matrix formed by encoding points on the first image, B is a matrix formed by encoding points on the current image, Q is a transformation matrix between the matrixes A and B, and a pose transformation matrix Q containing parameters M and d can be solved according to a least square method:
Q＝(ATA)-1ATB。
s6: obtaining the position estimation of Pm on each image by using a pose transformation matrix Q, and accurately searching and matching by using a digital image correlation method;
for a scattered spot p (x) on the reference imagei,j,yi,j) In other words, the estimated position in the next image is:
p'(x′i,j,y′i,j)＝p(xi,j,yi,j)·Q
the estimated position can provide a more accurate matching initial value for searching scattered spots, and the decorrelation problem caused by overlarge image rotation angle in the calibration process is avoided.
The tracking of the corresponding points on the speckle calibration image is completed by digital image correlation matching, and the matching efficiency and precision are ensured mainly by coarse matching at the whole pixel level and fine matching at the sub-pixel level.
First, coarse matching is performed. Providing initial values of the points by using a conversion matrix Q of the coding points, and performing search calculation by using a cross-correlation function, wherein the search calculation comprises parameter setting items such as matching subarea size, search range and the like. Cross correlation function CNCCComprises the following steps:
wherein f (x)i,yj) Is the gray value g (x) on the first image (reference image)i',yj') grayscale value on the current image to be estimated, S represents the radius of the sub-area in pixels, f, g represent the first image (reference image) and the current image to be estimated respectivelyThe average value of the gray levels of the sub-regions;
and then carrying out fine matching. The result of the rough matching is used as an initial value of the fine matching, and then a least square distance Sum of Squares (SSD) and a bilinear interpolation algorithm (one of sub-pixel interpolation algorithms) are combined, a first-order deformation affine transformation function is used for completing sub-pixel level matching and tracking of points, and corresponding expressions are respectively as follows:
G(x',y')＝a10x'+a01y'+a11x'y'+a00,0＜x'＜1,0＜y'＜1
wherein, f (x)i,yj)、g(xi',yj') Gray-values, r, on the first image (reference image) and the image to be currently estimated, respectively0、r1Is a compensation coefficient; a is10、a01、a11、a00Respectively are sub-pixel interpolation coefficients, and G (x ', y') is a sub-pixel gray value obtained by interpolation; (x)i,j',yi,j') is the two-dimensional point obtained after matching, u, v are the integer pixel displacement in x, y directions, respectively, ux、uyThe partial derivatives of the u displacement in the x and y directions, vx、vyThe partial derivatives of the v displacement in the x direction and the y direction are respectively, and the Δ x and the Δ y are respectively the difference values of the current coordinate and the coordinate of the center of the subarea in the x direction and the y direction.
S7: establishing an imaging mapping relation by using the positions of the calibration three-dimensional point Pw and all the calibration two-dimensional points Pm, and calculating initial values of internal and external parameters of the stereoscopic camera according to the mapping relation; and finally, finishing the optimization adjustment of the initial value by using a binding adjustment algorithm to obtain an accurate calibration parameter result of the stereo camera.
A stereo camera model under relative external parameters is used, namely one camera is a reference camera, and the other camera is a non-reference camera. I.e. the intrinsic parameters of the camera includeProjection parameters of the camera (i.e. focal length f, principal point c)x,cy) And distortion parameter (i.e. radial distortion K)1,K2,K3Tangential distortion B1,B2Eccentric distortion E1,E2) And conversion parameters between cameras; the extrinsic parameters of the camera system include the transformation parameter [ R | t ] with the world coordinate system]。
Because of the initial value estimation, the distortion of the image is temporarily not considered, so that a recursive imaging collinear equation is formed by the calibration three-dimensional points and the calibration two-dimensional points, namely the imaging mapping relation between Pw and all Pm is as follows:
wherein eta is1～η8Are vector parameters.
The nonlinear equations listed in the above equations can be solved linearly by a two-step transformation. First, the linear equation containing the vector parameters is solved for all images, and then the { η [ ] of all images is passedmSolving the internal parameters of the camera and the external parameters of each image. Each image has 8 unknowns, so as long as there are 4 object points on the calibration plate and there are corresponding 4 image points on the image that can be identified, 8 unknowns can be solved by the least squares method. The above equation can be simplified to the matrix form as follows:
Dη＝E
by matrix solving, it can be obtained:
η＝(DTD)-1DTE
at this time, all { ηmAre obtained according to { eta }mAnd m is 1-8, an initial value calculation formula of the internal and external parameters of the camera can be established, and a parameter separation method can be deduced through factorization:
namely:
ξj(j ═ 1,2,3,4) represents a function of the initial values of all the parameters of the camera; according to xij(j ═ 1,2,3,4) can be deduced as the initial value f of the focal length of the camera0And principal point cx0,cy0Is composed of
Combining the existing internal parameters and { etamSolving for an initial value of an extrinsic parameter, i.e. R0[3×3]|t0[3×1]Matrix array
That is, the initial values of all the parameters of the camera are obtained as follows:
F1[ξj(j＝1,2,3,4)]＝[f0,cx0,cy0,K01,K02,K03,B01,B02,E01,E02；R0,t0]
internal parameters: f. of0,cx0,cy0,K01,K02,K03,B01,B02,B03；
External parameters: r0,T0。
And finally, finishing the optimization adjustment of the initial value by using a binding adjustment algorithm to obtain an accurate calibration parameter result of the stereo camera.
Under the reference camera, the error equation for each image point remains unchanged, with:
VL＝ALX1L+BLX2L+CLX3L-L
in the case of a non-reference camera, the error equation for each image point is:
VR＝ARX1R+BRX2R+CRX3R+DRX4R-L
in the formula: x1L,X2L,X3LRespectively an inner orientation parameter, an outer orientation parameter and a correction number of a calibration three-dimensional point coordinate of the reference camera; a. theL,BL,CLRespectively corresponding partial derivative matrixes of the internal parameter, the external parameter and the calibration three-dimensional point coordinate of the reference camera; and L is the deviation of the observed true value and the initial value. X1R,X2R,X3RRespectively the inner orientation parameter, the outer orientation parameter and the correction number of the coordinate of the calibrated three-dimensional point, X of the non-reference camera4RIs the number of corrections to the relative extrinsic parameters of the non-reference camera relative to the reference camera; a. theR,BR,CRPartial derivative matrixes of the coordinates of the image points of the non-reference camera to the coordinates of the internal parameters, the external parameters and the calibration three-dimensional points of the reference camera respectively, DRA partial derivative matrix of the image point coordinates of the non-reference camera to its own relative extrinsic parameters; and by combining the error optimization equation with a nonlinear global binding adjustment algorithm and adding a scale, iteration can be performed to obtain an accurate calibration result. The final output accurate calibration result is:
F2[VL；VR]＝[f,cx,cy,K1,K2,K3,B1,B2,E1,E2；R,t]
through the error optimization equation and the combination of a nonlinear optimization algorithm, global binding adjustment is carried out, and an accurate calibration result can be obtained through iteration, such as a Levenberg-Marquardt algorithm. The final output accurate calibration result is: the internal parameters are f, cx,cy,K1,K2,K3,B1,B2,B3(ii) a The external parameters are R and T.
In the above preferred embodiment, the first image is used as the reference image, and in other embodiments, any other captured image may be used as the reference image.
On one hand, the three-dimensional camera calibration method based on the speckle pattern provided by the preferred embodiment of the invention improves the calibration precision of the three-dimensional camera to a great extent; accurate initial values of internal and external parameters of the stereoscopic camera are obtained through calibration, and the average reprojection error of imaging is reduced; meanwhile, the processing precision requirement of the calibration plate is reduced, and the manufacturing cost of the calibration plate is saved. On the other hand, the three-dimensional camera calibration method based on the speckle pattern provided by the preferred embodiment of the invention also improves the stability of the three-dimensional camera calibration; the method has strong resistance to the problems of uneven illumination and environmental vibration, is suitable for stereo camera systems with different zoom ratios, such as a stereo microscope system consisting of a binocular camera and a stereo microscope, and also has a certain fault tolerance to the problems of defocusing during imaging of telecentricity, long focus and small focal depth; in addition, a small number of linear coding points can improve the point matching speed and the calibration efficiency.
The following description applies the method for calibrating a stereo camera based on a speckle pattern according to a preferred embodiment of the present invention with reference to specific examples.
The three-dimensional camera calibration method based on the speckle pattern in the specific embodiment of the invention comprises the following steps:
s1, preparing a planar speckle calibration plate, wherein the whole body consists of a speckle pattern and a small number of encoding points;
the calibration plate is made of aluminum alloy, speckles can be sprayed manually, a substrate is sprayed by white matte paint, the speckles are sprayed by black paint, the black and white proportion accounts for about 50% respectively, and the coding points can be manufactured by a laser etching method; or generating a digital speckle pattern by computer simulation, randomly distributing the speckles according to gaussian distribution, and drawing the coding points by a computer, as shown in fig. 2, the design examples of the linear coding points are shown in fig. 3a to 3f, where fig. 3a shows the coding mode, and fig. 3b to 3f respectively represent one linear coding point.
S2, placing the speckle calibration pattern in the imaging range of the stereo camera, and collecting at least 8 speckle calibration images in different directions by using a binocular stereo camera;
a stereo imaging system is built by two cameras, the model of the camera is Basler Usb3.0, the resolution is 500 ten thousand pixels (2448 pixels multiplied by 2048 pixels), the size of a sensor pixel is 3.45um/pixel, and a 25mm lens is equipped.
After the calibration plate is aligned with the optical axis of the stereo imaging system as described in the above preferred embodiment, more than 8 speckle calibration images with different orientations are collected, as shown in fig. 4.
S3, aligning a world coordinate system to the center of the speckle calibration plate, measuring the physical distance of the coding points, dividing the calibration plate into i rows and j columns of virtual grid lattices according to the physical distance, and calculating to obtain a calibration three-dimensional point Pw;
as shown in fig. 5, the horizontal distance and the vertical distance of the code point are 179.8738mm and 139.9387mm, respectively, the calibration board calculation area is divided into 23 rows × 23 columns, the coordinate values of each point are calculated, and 4 non-collinear calibration three-dimensional points Pw are selected, as shown in table 1.
TABLE 1 calibration of three-dimensional Point examples
S4, extracting the center of a coding point of the first image, and dividing the coding point into i rows and j columns according to the pixel distance to obtain a calibration two-dimensional point Pm to be matched on the two-dimensional image;
as shown in fig. 6, the calibration board calculation area is divided into 23 rows × 23 columns, the coordinate values of each point are calculated, and 4 calibration two-dimensional points Pm that are not collinear are selected. Table 2 is an example of selected calibration two-dimensional points.
TABLE 2 calibration two-dimensional Point example
S5, calculating the integral position transformation matrix Q of the images by using the coding point centers of the first image and the current image for the speckle calibration images obtained from other different directions;
as shown in fig. 7, a conversion parameter calculation matrix X is created from the coordinates of the encoding points on the image 1 and the coordinates of the encoding points on the image 2, and the affine conversion parameters are obtained by solving X. The calculation results are shown in Table 3.
Table 3 affine transformation matrix calculation example
Affine transformation parameters between images 1-2
S6, obtaining the position estimation of Pm on each image by using the Q matrix, and accurately searching and matching by using a digital image correlation method;
as shown in fig. 8 and 9, the calibration two-dimensional points in the table 2 are integrally mapped to obtain initial values of the calibration two-dimensional points Pm according to affine transformation parameters between the images 1-2, and then coarse and fine matching is performed by using a digital image correlation method to obtain accurate matching points. The exact values of the calibration two-dimensional points are shown in table 4.
TABLE 4 calibrating two-dimensional point exact match Pm example
S7, establishing an imaging mapping relation by using the calibration three-dimensional point Pw and all calibration two-dimensional points Pm, and calculating initial values of internal and external parameters of the stereo camera according to the mapping relation; and finally, finishing the optimization adjustment of the initial value by using a binding adjustment algorithm to obtain an accurate calibration parameter result of the stereo camera.
According to the examples in tables 1-4, all the calibrated three-dimensional points Pw and the calibrated two-dimensional points on all the images are tracked and calculated. Taking the collection of 8 images as an example, 5 coding points are removed, the total number of Pw is 524, and the total number of Pm is 524 multiplied by 8, so as to establish a mapping equation, and then an initial value resolving method is utilized in combination with initial values of configuration parameters of the camera and the lens, such as focal length, resolution, pixel size and the like, to obtain internal and external parameters of the stereo camera;
and binding and adjusting all parameters by using a nonlinear optimization algorithm, such as a Levenberg-Marquardt algorithm, and adding a scale to obtain an accurate optimization result. The calibration results obtained are shown in table 5.
TABLE 5 calibration result examples after optimization
The external parameters of the camera 1 relative to the world coordinate system are
Obtaining a relative external parameter of the camera 2 relative to the camera 1 as
Another preferred embodiment of the present invention further discloses a stereoscopic camera calibration apparatus, including:
the device comprises a first unit, a second unit and a third unit, wherein the first unit is configured to provide a speckle calibration plate, and a speckle pattern and a plurality of encoding points are arranged on the speckle calibration plate;
the second unit is configured to place the speckle calibration plate in an imaging range of a binocular stereo camera, and the binocular stereo camera is adopted to collect images in at least 8 different directions to obtain at least 16 speckle calibration images;
the third unit is configured to measure physical distances of the plurality of coding points, divide the speckle calibration plate into virtual grid lattices of i rows by j columns according to the physical distances, and obtain coordinates of calibration three-dimensional points Pw on the speckle calibration plate, wherein i and j are positive integers respectively;
a fourth unit, configured to take any one of the at least 16 speckle calibration images obtained by the second unit as a reference image, extract the center of the encoding point on the reference image, and divide the encoding point into i rows × j columns according to the pixel distance to obtain the coordinates of a calibration two-dimensional point Pm on the reference image;
a fifth unit, configured to calculate, for at least 16 speckle calibration images obtained by the second unit, a pose transformation matrix Q of the entire image according to centers of the encoding points of the reference image and the current non-reference image, for other non-reference images except the reference image;
a sixth unit, configured to obtain coordinates of a calibration two-dimensional point Pm on each non-reference image according to the pose transformation matrix Q;
and the seventh unit is configured to establish an imaging mapping relation by adopting the coordinates of the calibration three-dimensional point Pw on the speckle calibration plate and the coordinates of the calibration two-dimensional point Pm on all speckle calibration images, and calculate the internal and external parameters of the binocular stereo camera according to the imaging mapping relation.
All or part of the flow of the method of the embodiments may be implemented by a computer program, which may be stored in a computer readable storage medium and executed by a processor, to instruct related hardware to implement the steps of the embodiments of the methods. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several equivalent substitutions or obvious modifications can be made without departing from the spirit of the invention, and all the properties or uses are considered to be within the scope of the invention.
Claims (12)
1. A calibration method for a stereo camera is characterized by comprising the following steps:
s1: providing a speckle calibration plate, wherein a speckle pattern and a plurality of coding points are arranged on the speckle calibration plate;
s2: placing the speckle calibration plate in an imaging range of a binocular stereo camera, and collecting at least 8 different directions by using the binocular stereo camera to obtain at least 16 speckle calibration images;
s3: measuring the physical distances of a plurality of coding points, and dividing the speckle calibration plate into virtual grid lattices of i rows by j columns according to the physical distances to obtain coordinates of calibration three-dimensional points Pw on the speckle calibration plate, wherein i and j are positive integers respectively;
s4: taking any speckle calibration image of the at least 16 speckle calibration images obtained in the step S2 as a reference image, extracting the center of the encoding point on the reference image, and dividing the encoding point into i rows × j columns according to the pixel distance to obtain the coordinates of a calibration two-dimensional point Pm on the reference image;
s5: calculating a pose transformation matrix Q of the whole image according to the centers of the encoding points of the reference image and the current non-reference image for the other non-reference images except the reference image in the at least 16 speckle calibration images obtained in the step S2;
s6: obtaining the coordinates of a calibration two-dimensional point Pm on each non-reference image according to the pose transformation matrix Q;
s7: and establishing an imaging mapping relation by adopting the coordinates of the calibration three-dimensional point Pw on the speckle calibration plate and the coordinates of the calibration two-dimensional point Pm on all speckle calibration images, and calculating the internal and external parameters of the binocular stereo camera according to the imaging mapping relation.
2. The method for calibrating a stereoscopic camera according to claim 1, wherein the speckle calibration plate is rectangular in step S1, and the plurality of encoding points includes 4 encoding points located at four vertices of the speckle calibration plate.
3. The calibration method of the stereo camera according to claim 1, wherein the at least 8 orientations include at least first to eighth orientations, wherein the first orientation and the second orientation are formed by moving the speckle calibration plate back and forth within a depth of field range at a first position where the optical axis of the binocular stereo camera is aligned with the center of the speckle calibration plate as a reference position, so that the optical axis of the binocular stereo camera and the center of the speckle calibration plate form a third orientation and a fourth orientation, respectively, left and right, within an inclination angle range of 5-15 °; and when the speckle calibration plate is vertically turned 180 degrees in a plane from the first position to the second position, the speckle calibration plate is moved back and forth within the depth of field range to form a fifth azimuth and a sixth azimuth, so that the optical axis of the binocular stereo camera and the center of the speckle calibration plate form a seventh azimuth and an eighth azimuth respectively at the left and right sides within the inclination angle range of 5-15 degrees.
4. The calibration method of the stereo camera according to claim 1, wherein the step S3 further includes aligning a world coordinate system to a center of the speckle calibration plate, and obtaining coordinates of a calibration three-dimensional point Pw on the speckle calibration plate as (± i/2 · Δ w, ± j/2 · Δ h, 0), where Δ w/(i-1) is a horizontal equally-divided interval of the encoding points, Δ h (j-1) is a vertical equally-divided interval of the encoding points, and w and h are horizontal physical distances and vertical physical distances of a plurality of the encoding points, respectively.
5. The method for calibrating a stereo camera according to claim 1, wherein coordinates of the calibrated two-dimensional point Pm on the reference image obtained in step S4 are (± i/2 · Δ l, ± j/2 · Δ b), where Δ l/(i-1) is a horizontal equally-divided interval of the encoded point on the reference image, Δ b/(b-1) is a vertical equally-divided interval of the encoded point on the reference image, and l and b are a horizontal pixel distance and a vertical pixel distance of the encoded point on the reference image, respectively.
6. The method for calibrating a stereo camera according to claim 1, wherein a pose transformation matrix Q of the whole image is calculated according to the centers of the encoding points of the reference image and the current non-reference image in step S5 (a ═ a)TA)- 1ATAnd B, wherein A is a matrix formed by the coding points on the reference image, and B is a matrix formed by the coding points on the current non-reference image.
7. The calibration method for the stereo camera according to claim 1, wherein the step S6 specifically includes obtaining coordinates p '(x'i,j,y'i,j)＝p(xi,j,yi,j) Q, and searching and matching by digital image correlation, wherein p (x)i,j,yi,j) And the coordinates of the calibration two-dimensional points on the reference image are obtained.
8. The calibration method of the stereo camera according to claim 7, wherein the searching and matching by the digital image correlation method specifically comprises:
each using the pose transformation matrix QCoordinates p ' (x ') of a calibration two-dimensional point Pm on the non-reference image 'i,j,y'i,j) As an initial value of a calibration two-dimensional point Pm, performing search calculation by using a cross-correlation function to perform first matching; and then, taking the result of the first matching as an initial value, and combining a least square method square sum coefficient, a sub-pixel interpolation algorithm and a deformation affine transformation function to complete sub-pixel level matching and tracking of the calibration two-dimensional points to obtain the coordinates of the matched calibration two-dimensional points.
9. The calibration method for the stereo camera according to claim 1, wherein an imaging mapping relationship established in step S7 by using the coordinates of the calibration three-dimensional point Pw on the speckle calibration plate and the coordinates of the calibration two-dimensional point Pm on all speckle calibration images is as follows:
wherein eta is1～η8Is a vector parameter, (x)i,j，yi,j) Coordinates of a calibration three-dimensional point Pw on the speckle calibration plate, (X)i,j，Yi,j) Coordinates of a calibration two-dimensional point Pm on the speckle calibration image are obtained;
calculating to obtain a vector parameter eta according to the coordinates of the calibration three-dimensional point Pw on the speckle calibration plate and the coordinates of the calibration two-dimensional point Pm on all speckle calibration images1～η8According to the vector parameter η1～η8And calculating to obtain the internal and external parameters of the binocular stereo camera.
10. The calibration method of the stereo camera according to claim 1, wherein the step S7 further includes: and adjusting the calculated internal and external parameters of the binocular stereo camera by adopting a binding adjustment algorithm to obtain a calibration parameter result of the binocular stereo camera.
11. The calibration method of the stereo camera according to claim 10, wherein the adjusting the calculated internal and external parameters of the binocular stereo camera by using the binding adjustment algorithm to obtain the calibration parameter result of the binocular stereo camera specifically comprises: according to an error optimization equation of a reference camera and a non-reference camera, combining a nonlinear global binding adjustment algorithm, adding a scale, and iterating to obtain a calibration parameter result of the binocular stereo camera; wherein the error optimization equation of the reference camera is:
VL＝ALX1L+BLX2L+CLX3L-L
the error optimization equation of the non-reference camera is as follows:
VR＝ARX1R+BRX2R+CRX3R+DRX4R-L
in the formula, X1L,X2L,X3LRespectively an inner orientation parameter, an outer orientation parameter and a correction number of a calibration three-dimensional point coordinate of the reference camera; a. theL,BL,CLRespectively corresponding partial derivative matrixes of the internal parameter, the external parameter and the calibration three-dimensional point coordinate of the reference camera; l is the deviation of the actual value and the initial value of the observation; x1R,X2R,X3RRespectively the inner orientation parameter, the outer orientation parameter and the correction number of the coordinate of the calibrated three-dimensional point, X of the non-reference camera4RIs the number of corrections to the relative extrinsic parameters of the non-reference camera relative to the reference camera; a. theR,BR,CRPartial derivative matrixes of the coordinates of the image points of the non-reference camera to the coordinates of the internal parameters, the external parameters and the calibration three-dimensional points of the reference camera respectively, DRIs a matrix of partial derivatives of the coordinates of the image points of the non-reference camera with respect to their own relative extrinsic parameters.
12. A calibration device for a stereo camera is characterized by comprising:
the device comprises a first unit, a second unit and a third unit, wherein the first unit is configured to provide a speckle calibration plate, and a speckle pattern and a plurality of encoding points are arranged on the speckle calibration plate;
the second unit is configured to place the speckle calibration plate in an imaging range of a binocular stereo camera, and the binocular stereo camera is adopted to collect images in at least 8 different directions to obtain at least 16 speckle calibration images;
the third unit is configured to measure physical distances of the plurality of coding points, divide the speckle calibration plate into virtual grid lattices of i rows by j columns according to the physical distances, and obtain coordinates of calibration three-dimensional points Pw on the speckle calibration plate, wherein i and j are positive integers respectively;
a fourth unit, configured to take any one of the at least 16 speckle calibration images obtained by the second unit as a reference image, extract the center of the encoding point on the reference image, and divide the encoding point into i rows × j columns according to the pixel distance to obtain the coordinates of a calibration two-dimensional point Pm on the reference image;
a fifth unit, configured to calculate, for at least 16 speckle calibration images obtained by the second unit, a pose transformation matrix Q of the entire image according to centers of the encoding points of the reference image and the current non-reference image, for other non-reference images except the reference image;
a sixth unit, configured to obtain coordinates of a calibration two-dimensional point Pm on each non-reference image according to the pose transformation matrix Q;
and the seventh unit is configured to establish an imaging mapping relation by adopting the coordinates of the calibration three-dimensional point Pw on the speckle calibration plate and the coordinates of the calibration two-dimensional point Pm on all speckle calibration images, and calculate the internal and external parameters of the binocular stereo camera according to the imaging mapping relation.
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| CN113155756B (en) * | 2021-03-31 | 2022-10-04 | 中国科学院长春光学精密机械与物理研究所 | Light spot online calibration method |
| CN112905831A (en) * | 2021-04-02 | 2021-06-04 | 上海国际汽车城（集团）有限公司 | Method and system for acquiring coordinates of object in virtual scene and electronic equipment |
| CN113538592A (en) * | 2021-06-18 | 2021-10-22 | 深圳奥锐达科技有限公司 | Calibration method and device for distance measuring device and camera fusion system |
| CN113538592B (en) * | 2021-06-18 | 2023-10-27 | 深圳奥锐达科技有限公司 | Calibration method and device for distance measuring device and camera fusion system |
| CN113504110A (en) * | 2021-07-14 | 2021-10-15 | 北京理工大学 | Composite material mechanical property parameter measuring method based on standard speckle paster |
| CN115131444A (en) * | 2022-08-30 | 2022-09-30 | 常州铭赛机器人科技股份有限公司 | Calibration method based on monocular vision dispensing platform |
| CN115131444B (en) * | 2022-08-30 | 2022-11-15 | 常州铭赛机器人科技股份有限公司 | Calibration method based on monocular vision dispensing platform |
| CN115988343A (en) * | 2022-11-21 | 2023-04-18 | 中国联合网络通信集团有限公司 | Image generation method and device and readable storage medium |
| CN116228889A (en) * | 2023-04-27 | 2023-06-06 | 合肥工业大学 | Mobile calibration device, camera array system calibration device and method |
| CN116228889B (en) * | 2023-04-27 | 2023-08-15 | 合肥工业大学 | Mobile calibration device, camera array system calibration device and method |
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