CN112419425A - Anti-disturbance high-precision camera group measuring method for structural deformation measurement - Google Patents
Anti-disturbance high-precision camera group measuring method for structural deformation measurement Download PDFInfo
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Abstract
The invention relates to an anti-disturbance high-precision camera group measuring method for structural deformation measurement, which comprises the following steps: 1. the method comprises the following steps of (1) building a camera group system, assembling a portable measuring device, wherein the portable measuring device consists of a raspberry group, a camera, a wireless module, a GPS module and a power module, and connecting a plurality of sets of portable measuring devices with a computer to form the camera group system; 2. collecting an image; 3. calibrating system parameters of the camera group; 4. reconstructing three dimensions; 5. large area deformation measurement setup. The camera group system realizes wireless remote connection by utilizing the wireless module, ensures information transmission in a large range, and can realize signal coverage in a larger range by adding relays; the method adopts the combination of the distance between the measuring environment points and the scene points to accurately calibrate the external parameters, or adopts the combination of the distance between the measuring optical centers of the cameras and the scene points to accurately calibrate the external parameters without manually marking points; the invention can realize the global large-area measurement of the large-span structure.
Description
Technical Field
The invention relates to an anti-disturbance high-precision camera group measuring method for structural deformation measurement, and belongs to the technical field of optical measurement experimental mechanics.
Background
After outdoor facilities such as various bridges, power transmission towers, house buildings and the like are used for a certain period of time, in order to know whether the stability of the facilities meets the requirements and whether the facilities can be continuously used, regular inspection needs to be carried out on the facilities. However, the existing measurement technology for the large-scale structure is not mature enough, and no good method can realize high-precision and large-span structural deformation measurement. At present, in engineering application, displacement measurement of a small area can be realized by a monocular camera in a mode of pasting an identification point on an area to be measured. However, this method has a limited measurement area and can only measure in-plane displacement. The binocular measurement is mature, but the binocular mode is only three-dimensional measurement, and errors caused by environmental disturbance on imaging are not well solved. Moreover, most of the test devices are wired at present, which is disadvantageous for field test, and if the target to be tested is large, it is difficult to implement the test by wired connection.
Disclosure of Invention
In order to solve the technical problems, the invention provides an anti-disturbance high-precision camera group measuring method for structural deformation measurement, which has the following specific technical scheme:
the anti-disturbance high-precision camera group measuring method for structural deformation measurement comprises the following steps:
the method comprises the following steps: building a camera group system: assembling a portable measuring device, wherein the portable measuring device consists of a raspberry group, a camera, a wireless module, a GPS module and a power supply module, connecting a plurality of sets of portable measuring devices with a computer to form a camera group system, and assembling and building the camera group system before a measuring area;
step two: image acquisition: under a wireless network, a computer remotely controls a camera connected to the raspberry pi to perform image synchronous acquisition through a clock signal source of a GPS module, and the acquired image is stored in the raspberry pi and shared to the computer;
step three: calibrating camera group system parameters: calibrating external parameters of the camera by using different methods:
I. the method comprises the steps that the actual distance between the maximum two points in the field of view of a camera is measured, and external parameters are accurately calibrated by combining feature points in the field of view;
II, accurately fixing the parameters of the industrial camera by measuring the actual distance between the optical centers of the cameras and combining the characteristic points in the view field;
step four: reconstructing three dimensions: acquiring images by using three cameras according to the calibrated camera group parameters, performing three-dimensional reconstruction on a measurement area to obtain world coordinates of each point, and calculating the deformation in a camera field of view by combining a plurality of groups of pictures;
step five: large area deformation measurement setup: and (3) installing a plurality of sets of portable measuring devices in each subarea of the measuring area in a chain-type distribution manner, repeating the operation from the second step to the fourth step, and integrating and analyzing the measuring results of each subarea to realize wireless remote, disturbance-resistant, high-precision and global synchronous deformation measurement and monitoring of the large-span regional facility.
Further, the arrangement mode of the portable measuring devices in the first step includes a straight distribution mode, a triangular distribution mode and a chain distribution mode.
Further, the portable measuring device that the straight line distributes is provided with three cameras, the camera all shoots towards the measuring area syntropy, and the shooting contained angle between both sides camera and the middle camera is 15 to 20.
Further, in the third step, when the external parameters are accurately calibrated by measuring the actual distance between the maximum two points in the field of view of the camera and combining the feature points in the field of view, the derivation process is as follows:
sp=A[R t]P（1）
in the formulasThe method comprises the following steps that A is a scale factor, A is a camera internal parameter matrix, R is a rotation matrix between world coordinates and camera coordinates, t is a translation vector between the world coordinates and the camera coordinates, P is image coordinates of feature points, and P is the world coordinates of the feature points; defining a world coordinate system to coincide with a middle camera coordinate system by using a portable measuring device provided with three cameras linearly distributed, separating the world coordinates in order to standardize image pixel coordinates to image physical coordinates, and multiplying R at two ends simultaneously-1And A-1And extracting the intermediate camera by using a Surf algorithmAs image coordinates of a certain point of camera No. 0
And the camera at one side adjacent to the middle camera is the image coordinate of the corresponding point of the No. 1 camera
The other side camera adjacent to the middle camera is the image coordinate of the corresponding point of the No. 2 camera
And the world coordinates (X, Y, Z, 1) of the corresponding points are respectively substituted into the formula (1),
in the formula (I), the compound is shown in the specification,
respectively the projection of the distance from the object point to the optical center of No. 0, No. 1 and No. 2 cameras in the direction of the optical axis, R1And t1Is the rotation matrix and translation vector between world coordinates and camera No. 1, R2And t2Is the rotation matrix and translation vector between world coordinates and camera No. 2,
，
，
，
，
，
，
and, and
the image coordinates of the intersection points of the principal points of the images of the cameras No. 0, No. 1 and No. 2, namely the optical axes and the image plane respectively,
、
、
、
、
、
cameras 0, 1 and 2 respectivelyxAndyan equivalent focal length in the direction of
LIs the distance between the object and the ground,fis the focal length of the camera and,d x 、d y is the pixel size, simultaneous formulas (2) and (3), and world coordinates are eliminated
Wherein
In the formula (I), the compound is shown in the specification,
are the components of the translation vector in the x, y, z axes,
is the angle of rotation
The function of the trigonometric combination of (a),
defined as transformation of the world coordinate system to Euler angles, n, rotated about three coordinate axes respectively in conformity with the pose of the camera coordinate system1Is a rotation vector, and the relation between the rotation vector and the rotation matrix is a Reed-Solomon transform, eliminatings 0 Ands 1 so as to obtain the compound with the characteristics of,
the rotation vector and the translation vector are obtained by adopting an L-M iterative method to optimize a formula (8), wherein the initial value of the rotation vector is selected as
The translation vector is selected as
(ii) a As can be seen from equation (8), the simultaneous multiplication of both sides of the equation by a scaling factor has no effect on both sides of the equation, so that values of 1 are obtained in the iteration
Without involving in the iterative process, the translation vector determined at this time being about
A normalized translation vector that is multiplied from the true translation vector; three-dimensional reconstruction is carried out by adopting normalized translation vector, and the distance between certain two points is calculatedlThe actual distance between the two points is obtained by measurementLThe scale factor isL/lAnd multiplying the proportional factor by the normalized translation vector to obtain a real translation vector, and finishing accurate calibration of the external parameter.
Furthermore, in the third step, by measuring the actual distance between the optical centers of the cameras and then combining with the characteristic points in the field of view to accurately calibrate the external parameters of the cameras, a portable measuring device with three cameras linearly distributed is adopted, and the calculation formula is as follows:
whereindIs the actual distance between the optical centers of the two cameras,
is a translation vector calculated by a normalization method,
is the components of the normalized translation vector in the x, y and z axes, and the real translation vector is obtained by solving
，
The components of the real translation vector in the x, y and z axes are used for completing the accurate calibration of the external parameter.
Furthermore, a distance meter is arranged right above the camera at the central position, targets are arranged right above the cameras at two sides of the camera at the central position, and the targets reflect laser emitted by the distance meter to realize distance measurement between optical centers of the cameras.
Further, the step four is to reconstruct the three-dimension by using the least square principle through the pixel coordinates of the feature points in the three images, a portable measuring device provided with three cameras is adopted, the central camera is defined as a No. 0 camera, and the cameras on the two sides of the central camera are respectively a No. 1 camera and a No. 2 camera; defining the world coordinate as coincident with a No. 0 camera coordinate system, wherein a rotation matrix of the coordinate system relative to the world coordinate system is a unit matrix, and a translation vector is a 0 vector; camera No. 1 calibrated for rotation matrix and translation vector relative to world coordinate systemR 1 Andt 1 with camera 2 calibrated to a rotation matrix and translation vector relative to the world coordinate systemR 2 Andt 2 according to formula (1), the projection equations of cameras No. 0, No. 1 and No. 2 can be written as:
in the above formula, the first and second carbon atoms are,
the image coordinates, the rotation matrix and the translation vector of the cameras No. 0, No. 1 and No. 2 are in the form of the formula (7) The internal reference matrix is A(0)、A(1)And A(2)：
In the formula
Is a tilt factor between two coordinate axes of No. 0, No. 1 and No. 2 camera image planes, and is converted into a matrix form
The three-dimensional coordinates of the point to be solved are solved by a least square method, and the expressions of M and Q are as follows:
the working principle of the invention is as follows:
the invention designs a portable measuring device, which consists of a raspberry group, an industrial camera, a wireless module, a GPS module and a power module, wherein a plurality of sets of portable measuring devices and a computer form a camera group system. Covering a wireless network in a measurement area by using a wireless module, and remotely controlling a camera to shoot a field picture; accurately calibrating the external parameter by measuring the actual distance between the maximum two points in the field of view of the camera and combining the characteristic points in the field of view, or accurately calibrating the industrial camera by measuring the actual distance between the optical centers of the camera and combining the characteristic points in the field of view; and then three-dimensional reconstruction is carried out, and further the deformation and displacement of the structure to be measured are calculated.
The invention has the beneficial effects that:
the camera group system realizes wireless remote connection by utilizing the wireless module, ensures information transmission in a large range, and can realize signal coverage in a larger range by adding relays; the method adopts the combination of the distance between the measuring environment points and the scene points to accurately calibrate the external parameters, or adopts the combination of the distance between the measuring optical centers of the cameras and the scene points to accurately calibrate the external parameters without manually marking points; compared with binocular measurement, the method can reduce the influence of environmental disturbance on imaging and realize high-precision measurement; the invention can realize the global large-area measurement of the large-span structure.
Drawings
Figure 1 is a schematic flow diagram of the present invention,
figure 2 is a schematic diagram of the portable measuring device of the present invention,
FIG. 3 is a schematic view of the arrangement of the camera groups in a straight line,
FIG. 4 is a top view of the camera group of the present invention arranged in a straight line,
FIG. 5 is a schematic view of the triangular arrangement of the camera group according to the present invention,
fig. 6 is a schematic diagram of the camera group system of the present invention measuring a large bridge structure.
Detailed Description
The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic views illustrating only the basic structure of the present invention in a schematic manner, and thus show only the constitution related to the present invention.
As shown in fig. 2, the portable measuring device of the present invention is mainly composed of five modules, which are raspberry pi 4, IDS industrial camera, wireless module, GPS module and power module. The processor of the raspberry pi 4 is a Boradcom BCM 271164-bit ARM Cortex-A72 processor based on an ARMv8 architecture, the working dominant frequency is 1.5GHz, and the processor carries a 1GB memory. The IDS industrial camera model is UI-3370CP-M-GL Rev.2.
As shown in FIG. 1, the disturbance-resistant high-precision camera group measuring method for structural deformation measurement comprises the following steps
Building a camera group system: assembling a portable measuring device, wherein the portable measuring device consists of a raspberry group, a camera, a wireless module, a GPS module and a power supply module, connecting a plurality of sets of portable measuring devices with a computer to form a camera group system, and assembling and building the camera group system before a measuring area. Firstly, the wireless module constructs a wireless local area network through a wireless router, and can select whether to add relays according to actual conditions so as to obtain a larger signal coverage range and ensure normal communication between the measuring equipment and a computer host; then, according to the selected camera type, the camera is connected with the raspberry pie by adopting interfaces such as a USB (universal serial bus) or a network cable; then, opening a driving program of the camera, acquiring a real-time image collected by the camera, and adjusting a focal length, an aperture and the like until the image is clear; then, when a certain specific area is measured, the camera group is set up in a straight line mode, such as fig. 3 and 4, or in a triangular distribution mode, such as fig. 5, and the included angle between any one camera and the central camera is 15-20 degrees; finally, when deformation measurement is carried out on a large area, such as large-span bridge structure measurement, the portable measuring devices are distributed in a chain manner, and as shown in fig. 6, the fact that the view field of the camera group system comprises the whole measuring structure is guaranteed.
Image acquisition: under a wireless network, a computer remotely controls a camera connected to the raspberry pi to synchronously acquire images through a clock signal source of a GPS module, and the acquired images are stored in the raspberry pi and shared with the computer. The computer controls each raspberry sending camera system to synchronously pick images and shares the images to the console computer. And the time synchronization function of each measuring device is realized by introducing a GPS clock signal source. The camera's photographing function can be triggered by software through the SDK of the camera provided by the IDS company, and various parameters of the camera can be freely configured. The wireless module can establish stable connection with the base station at a longer distance. The Samba service is installed and opened on the raspberry, file sharing of a server side can be achieved, and shot pictures can be freely downloaded.
Calibrating camera group system parameters: calibrating external parameters of the camera by using different methods: I. the external parameters are accurately calibrated by measuring the actual distance between the maximum two points in the field of view of the camera and combining the characteristic points in the field of view. The method is carried out by measuring the actual distance between the maximum two points in the field of view of the camera and selecting a proper mode according to the size of the field of view. When the field of view is small, the measurement can be carried out by using a meter ruler; when the field of view is large, the distance measuring instrument is fixed at one point, and a supporting target is arranged at the other point and can reflect laser emitted by the distance measuring instrument to realize measurement. When the external parameters are accurately calibrated by combining the characteristic points in the view field, the derivation process is as follows:
sp=A[R t]P（1）
in the formulasThe method comprises the following steps that A is a scale factor, A is a camera internal parameter matrix, R is a rotation matrix between world coordinates and camera coordinates, t is a translation vector between the world coordinates and the camera coordinates, P is image coordinates of feature points, and P is the world coordinates of the feature points; defining a world coordinate system to coincide with a middle camera coordinate system by using a portable measuring device provided with three cameras linearly distributed, separating the world coordinates in order to standardize image pixel coordinates to image physical coordinates, and multiplying R at two ends simultaneously-1And A-1And using the intermediate camera extracted by the Surf algorithm as the image coordinate of a certain point of the No. 0 camera
And the camera at one side adjacent to the middle camera is the image coordinate of the corresponding point of the No. 1 camera
The other side camera adjacent to the middle camera is the image coordinate of the corresponding point of the No. 2 camera
And the world coordinates (X, Y, Z, 1) of the corresponding points are respectively substituted into the formula (1),
in the formula (I), the compound is shown in the specification,
the projection of the distances from the object point to the optical centers of No. 0, No. 1 and No. 2 cameras in the direction of the optical axis, R1And t1Is the rotation matrix and translation vector between world coordinates and camera No. 1, R2And t2Is the rotation matrix and translation vector between world coordinates and camera No. 2,
，
，
，
，
，
，
and, and
the image coordinates of the intersection points of the principal points of the images of the cameras No. 0, No. 1 and No. 2, namely the optical axes and the image plane respectively,
、
、
、
、
、
cameras 0, 1 and 2 respectivelyxAndyan equivalent focal length in the direction of
LIs the distance between the object and the ground,fis the focal length of the camera, the camera adopts a fixed-focus lens,d x 、d y is the pixel size, simultaneous formulas (2) and (3), and world coordinates are eliminated
Wherein
In the formula (I), the compound is shown in the specification,
are the components of the translation vector in the x, y, z axes,
is the angle of rotation
The function of the trigonometric combination of (a),
defined as transformation of the world coordinate system to Euler angles, n, rotated about three coordinate axes respectively in conformity with the pose of the camera coordinate system1Is a rotation vector, and the relation between the rotation vector and the rotation matrix is a Reed-Solomon transform, eliminatings 0 Ands 1 to obtain
The rotation vector and the translation vector are obtained by adopting an L-M iterative method to optimize a formula (8), wherein the initial value of the rotation vector is selected as
The translation vector is selected as
(ii) a As can be seen from equation (8), the simultaneous multiplication of both sides of the equation by a scaling factor has no effect on both sides of the equation, so that values of 1 are obtained in the iteration
The translation vector is obtained in the case of normalization without participating in the iterative process, and is different from the real translation vector
Doubling; three-dimensional reconstruction is carried out by adopting normalized translation vector, and the distance between certain two points is calculatedlThe actual distance between the two points is obtained by measurementLThe scale factor isL/lAnd multiplying the proportional factor by the normalized translation vector to obtain a real translation vector, and finishing accurate calibration of the external parameter.
And II, accurately fixing the parameters of the industrial camera by measuring the actual distance between the optical centers of the cameras and combining the characteristic points in the view field. The measurement of the optical center distance is realized by fixing the distance measuring instrument at one point and setting a supporting target at the other point, and the supporting target can reflect laser emitted by the distance measuring instrument. The portable measuring device with three linearly distributed cameras is adopted, and the calculation formula is as follows:
whereindIs the actual distance between the optical centers of the two cameras,
is a translation vector calculated by a normalization method,
is the components of the normalized translation vector in the x, y and z axes, and the real translation vector is obtained by solving
，
The components of the real translation vector in the x, y and z axes are used for completing the accurate calibration of the external parameter.
Reconstructing three dimensions: and acquiring images by using three cameras according to the calibrated camera group parameters, performing three-dimensional reconstruction on the measurement area to obtain world coordinates of each point, and calculating the deformation in the camera field of view by combining a plurality of groups of pictures. Reconstructing by using a least square principle through feature point pixel coordinates in three images, and defining a central camera as a No. 0 camera and cameras on two sides of the central camera as a No. 1 camera and a No. 2 camera by adopting a portable measuring device provided with three cameras; defining the world coordinate as coincident with a No. 0 camera coordinate system, wherein a rotation matrix of the coordinate system relative to the world coordinate system is a unit matrix, and a translation vector is a 0 vector; camera No. 1 calibrated for rotation matrix and translation vector relative to world coordinate systemR 1 Andt 1 rotation matrix sum of No. 2 camera direction relative to world coordinate systemThe translation vector being calibratedR 2 Andt 2 according to formula (1), the projection equations of cameras No. 0, No. 1 and No. 2 can be written as:
in the above formula, the first and second carbon atoms are,
the image coordinates of No. 0, No. 1 and No. 2 cameras, the forms of the rotation matrix and the translation vector are shown in formula (7), and the internal reference matrix is A(0)、A(1)And A(2)：
In the formula
And, and
the image coordinates of the intersection points of the principal points of the images of the cameras No. 0, No. 1 and No. 2, namely the optical axes and the image plane respectively,
、
、
、
、
、
cameras 0, 1 and 2 respectivelyxAndythe equivalent focal length in the direction of the lens,
is a tilt factor between two coordinate axes of No. 0, No. 1 and No. 2 camera image planes, and is converted into a matrix form
The three-dimensional coordinates of the point to be solved are solved by a least square method, and the expressions of M and Q are as follows:
large area deformation measurement setup: the method comprises the steps of installing a plurality of sets of portable measuring devices in each subarea of a measuring area in a chain-type distribution mode, sequentially repeating the steps of image acquisition, camera group system parameter calibration and three-dimensional reconstruction, integrating and analyzing measuring results of each subarea, reconstructing three-dimensional coordinates at different moments according to pictures at different moments, and finding out the positions of deformed feature points through feature point matching so as to calculate the deformation condition. And combining the calculation results of all the camera groups to obtain the continuous deformation measurement result of the whole large-span bridge structure. The wireless remote, disturbance-resistant, high-precision and global synchronous deformation measurement and monitoring of large-span regional facilities are realized.
The camera group system realizes wireless remote connection by utilizing the wireless module, ensures information transmission in a large range, and can realize signal coverage in a larger range by adding relays; the method adopts the combination of the distance between the measuring environment points and the scene points to accurately calibrate the external parameters, or adopts the combination of the distance between the measuring optical centers of the cameras and the scene points to accurately calibrate the external parameters without manually marking points; compared with binocular measurement, the method can reduce the influence of environmental disturbance on imaging and realize high-precision measurement; the invention can realize the global large-area measurement of the large-span structure.
In light of the foregoing description of the preferred embodiment of the present invention, many modifications and variations will be apparent to those skilled in the art without departing from the spirit and scope of the invention. The technical scope of the present invention is not limited to the content of the specification, and must be determined according to the scope of the claims.
Claims (7)
1. An anti-disturbance high-precision camera group measuring method for structural deformation measurement is characterized in that: the method comprises the following steps:
the method comprises the following steps: building a camera group system: assembling a portable measuring device, wherein the portable measuring device consists of a raspberry group, a camera, a wireless module, a GPS module and a power supply module, connecting a plurality of sets of portable measuring devices with a computer to form a camera group system, and assembling and building the camera group system before a measuring area;
step two: image acquisition: under a wireless network, a computer remotely controls a camera connected to the raspberry pi to perform image synchronous acquisition through a clock signal source of a GPS module, and the acquired image is stored in the raspberry pi and shared to the computer;
step three: calibrating camera group system parameters: calibrating external parameters of the camera by using different methods:
I. the method comprises the steps that the actual distance between the maximum two points in the field of view of a camera is measured, and external parameters are accurately calibrated by combining feature points in the field of view;
II, accurately fixing the parameters of the industrial camera by measuring the actual distance between the optical centers of the cameras and combining the characteristic points in the view field;
step four: reconstructing three dimensions: acquiring images by using three cameras according to the calibrated camera group parameters, performing three-dimensional reconstruction on a measurement area to obtain world coordinates of each point, and calculating the deformation in a camera field of view by combining a plurality of groups of pictures;
step five: large area deformation measurement setup: and (3) installing a plurality of sets of portable measuring devices in each subarea of the measuring area in a chain-type distribution manner, repeating the operation from the second step to the fourth step, and integrating and analyzing the measuring results of each subarea to realize wireless remote, disturbance-resistant, high-precision and global synchronous deformation measurement and monitoring of the large-span regional facility.
2. The disturbance-resistant high-precision camera group measurement method for structural deformation measurement according to claim 1, wherein: the arrangement mode of the portable measuring devices in the first step comprises linear distribution, triangular distribution and chain distribution.
3. The disturbance-resistant high-precision camera group measurement method for structural deformation measurement according to claim 2, wherein: the portable measuring device that the straight line distributes is provided with three camera, the camera all shoots towards the measuring area syntropy, and the shooting contained angle between both sides camera and the middle camera is 15 to 20.
4. The disturbance-resistant high-precision camera group measurement method for structural deformation measurement according to claim 1, wherein: in the third step, when the external parameters are accurately calibrated by measuring the actual distance between the maximum two points in the field of view of the camera and combining the characteristic points in the field of view, the derivation process is as follows:
sp=A[R t]P（1）
in the formulasIs a scale factor, A is a camera internal parameter matrix, and R is world sittingA rotation matrix between the target and the camera coordinates, t is a translation vector between the world coordinates and the camera coordinates, P is image coordinates of the feature points, and P is the world coordinates of the feature points; defining a world coordinate system to coincide with a middle camera coordinate system by using a portable measuring device provided with three cameras linearly distributed, separating the world coordinates in order to standardize image pixel coordinates to image physical coordinates, and multiplying R at two ends simultaneously-1And A-1And using the intermediate camera extracted by the Surf algorithm as the image coordinate of a certain point of the No. 0 camera
And the camera at one side adjacent to the middle camera is the image coordinate of the corresponding point of the No. 1 camera
The other side camera adjacent to the middle camera is the image coordinate of the corresponding point of the No. 2 camera
And the world coordinates (X, Y, Z, 1) of the corresponding points are respectively substituted into the formula (1),
in the formula (I), the compound is shown in the specification,
respectively the projection of the distance from the object point to the optical center of No. 0, No. 1 and No. 2 cameras in the direction of the optical axis, R1And t1Is the rotation matrix and translation vector between world coordinates and camera No. 1, R2And t2Is the rotation matrix and translation vector between world coordinates and camera No. 2,
，
，
，
，
，
，
and, and
the image coordinates of the intersection points of the principal points of the images of the cameras No. 0, No. 1 and No. 2, namely the optical axes and the image plane respectively,
、
、
、
、
、
cameras 0, 1 and 2 respectivelyxAndyan equivalent focal length in the direction of
LIs the distance between the object and the ground,fis the focal length of the camera and,d x 、d y is the pixel size, simultaneous formulas (2) and (3), and world coordinates are eliminated
Wherein
In the formula (I), the compound is shown in the specification,
are the components of the translation vector in the x, y, z axes,
is the angle of rotation
The function of the trigonometric combination of (a),
defined as transformation of the world coordinate system to Euler angles, n, rotated about three coordinate axes respectively in conformity with the pose of the camera coordinate system1Is a rotation vector, and the relation between the rotation vector and the rotation matrix is a Reed-Solomon transform, eliminatings 0 Ands 1 so as to obtain the compound with the characteristics of,
the rotation vector and the translation vector are obtained by adopting an L-M iterative method to optimize a formula (8), wherein the initial value of the rotation vector is selected as
The translation vector is selected as
(ii) a As can be seen from equation (8), the simultaneous multiplication of both sides of the equation by a scaling factor has no effect on both sides of the equation, so that values of 1 are obtained in the iteration
The iteration process is not involved, and the obtained translation vector is about the normalized translation vector and is different from the real translation vector by times; three-dimensional reconstruction is carried out by adopting normalized translation vector, and the distance between certain two points is calculatedlThe actual distance between the two points is obtained by measurementLThe scale factor isL/lAnd multiplying the proportional factor by the normalized translation vector to obtain a real translation vector, and finishing accurate calibration of the external parameter.
5. The disturbance-resistant high-precision camera group measurement method for structural deformation measurement according to claim 1, wherein: in the third step, by measuring the actual distance between the optical centers of the cameras and combining with the characteristic points in the view field to accurately calibrate the external parameters of the cameras, a portable measuring device with three cameras linearly distributed is adopted, and the calculation formula is as follows:
whereindIs the actual distance between the optical centers of the two cameras,
is a translation vector calculated by a normalization method,
is the components of the normalized translation vector in the x, y and z axes, and the real translation vector is obtained by solving
，
The components of the real translation vector in the x, y and z axes are used for completing the accurate calibration of the external parameter.
6. The disturbance-resistant high-precision camera group measurement method for structural deformation measurement according to claim 5, wherein: the distance measuring device is arranged right above the camera at the central position, targets are arranged right above the cameras at two sides of the camera at the central position, and the targets reflect laser emitted by the distance measuring device to realize distance measurement between optical centers of the cameras.
7. The disturbance-resistant high-precision camera group measurement method for structural deformation measurement according to claim 1, wherein: the step four is to reconstruct the three-dimension by using the least square principle through the pixel coordinates of the feature points in the three images, a portable measuring device provided with three cameras is adopted, the central camera is defined as a No. 0 camera, and the cameras on the two sides of the central camera are respectively a No. 1 camera and a No. 2 camera; the world coordinates are defined to coincide with the camera coordinate system No. 0, the rotation of which relative to the world coordinate systemThe matrix is an identity matrix, and the translation vector is a 0 vector; camera No. 1 calibrated for rotation matrix and translation vector relative to world coordinate systemR 1 Andt 1 with camera 2 calibrated to a rotation matrix and translation vector relative to the world coordinate systemR 2 Andt 2 according to formula (1), the projection equations of cameras No. 0, No. 1 and No. 2 can be written as:
in the above formula, the first and second carbon atoms are,
the image coordinates of No. 0, No. 1 and No. 2 cameras, the forms of the rotation matrix and the translation vector are shown in formula (7), and the internal reference matrix is A(0)、A(1)And A(2)：
In the formula
Is a tilt factor between two coordinate axes of No. 0, No. 1 and No. 2 camera image planes, and is converted into a matrix form
Is the three-dimensional coordinate of the point to be solvedThe three-dimensional coordinates of the solution point are solved by the method of least squares, and the expressions of M and Q are as follows:
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN112964193A (en) * | 2021-04-14 | 2021-06-15 | 广州大学 | Novel bridge deformation monitoring method and system |
| CN113628283A (en) * | 2021-08-10 | 2021-11-09 | 地平线征程(杭州)人工智能科技有限公司 | Parameter calibration method and device for camera device, medium and electronic equipment |
| CN113674347A (en) * | 2021-05-18 | 2021-11-19 | 南京理工大学 | Deformation measuring device and method for three-dimensional morphology based on camera and projection group array |
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| CN113674347A (en) * | 2021-05-18 | 2021-11-19 | 南京理工大学 | Deformation measuring device and method for three-dimensional morphology based on camera and projection group array |
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