Slope deformation monitoring method and device, electronic equipment, storage medium and product

Abstract

The invention provides a slope deformation monitoring method and device, electronic equipment, a storage medium and a product, and the method comprises the steps: obtaining first three-dimensional coordinates of a plurality of targets disposed on a to-be-monitored slope at a first moment; acquiring a first two-dimensional image of the target by using a binocular camera system to obtain a first two-dimensional coordinate of the target; calibrating a camera in a binocular camera system based on the first two-dimensional coordinate and the first three-dimensional coordinate of the target to obtain an internal parameter and an external parameter of the camera; at a second moment, collecting a second two-dimensional image of the target by using the binocular camera system, and converting a second two-dimensional coordinate of the target on the second two-dimensional image into a second three-dimensional coordinate based on the internal parameter and the external parameter of the camera; and if the second three-dimensional coordinate is different from the first three-dimensional coordinate, determining that the slope to be monitored is deformed.

Description

Technical Field

[0001] The present disclosure relates to the field of mine surveying technology, and in particular to a slope deformation monitoring method, device, electronic equipment, storage medium and product. Background Art

[0002] In the field of open-pit mining, slope stability is an important factor in ensuring safe production and construction. Slope deformation monitoring can provide early warning of potential geological disasters and avoid casualties and property losses. Existing slope monitoring technologies mostly rely on traditional measurement methods such as total stations and GPS. Although these methods have been well verified in terms of accuracy and reliability, they have some technical limitations, such as limited measurement points, long data collection cycles, and poor real-time performance. Especially under complex terrain conditions, it is impossible to effectively carry out large-scale high-precision real-time monitoring.

[0003] In response to these problems, the slope deformation monitoring method based on binocular vision technology has gradually attracted attention. Binocular vision technology simulates the stereoscopic vision principle of the human eye, uses two cameras to shoot the same scene from different angles, and then calculates the three-dimensional spatial position of the monitored object through a stereo matching algorithm. The slope deformation monitoring method based on binocular vision technology has the advantages of light equipment, flexible deployment, and a large monitoring range. It is especially suitable for continuous, real-time, and high-precision deformation monitoring of a large area in slope deformation monitoring. Therefore, how to use binocular vision technology for slope deformation monitoring is an urgent problem to be solved. Summary of the invention

[0004] The present disclosure provides a slope deformation monitoring method, device, electronic equipment, storage medium and product to solve the problems in the related art.

[0005] A first aspect of the present disclosure provides a slope deformation monitoring method, the method comprising:

[0006] At a first moment, obtaining first three-dimensional coordinates of a plurality of targets set on the slope to be monitored;

[0007] Using a binocular camera system to collect a first two-dimensional image of the target to obtain a first two-dimensional coordinate of the target;

[0008] Based on the first two-dimensional coordinates and the first three-dimensional coordinates of the target, calibrate the camera in the binocular camera system to obtain the intrinsic parameters and extrinsic parameters of the camera;

[0009] At a second moment, using a binocular camera system to collect a second two-dimensional image of the target, and based on the intrinsic parameters and extrinsic parameters of the camera, converting a second two-dimensional coordinate of the target on the second two-dimensional image into a second three-dimensional coordinate;

[0010] If the second three-dimensional coordinates are different from the first three-dimensional coordinates, it is determined that the slope to be monitored is deformed.

[0011] In one embodiment, calibrating a camera in a binocular camera system based on the first two-dimensional coordinates and the first three-dimensional coordinates of the target to obtain intrinsic parameters and extrinsic parameters of the camera includes:

[0012] Determine the intrinsic parameters and distortion coefficients of the camera in the binocular camera system by using the Zhang Zhengyou calibration method;

[0013] Based on the intrinsic parameters and the distortion coefficients, correcting the first two-dimensional coordinates to obtain corrected first two-dimensional coordinates;

[0014] The extrinsic parameters of the camera are determined based on the first three-dimensional coordinates and the corrected first two-dimensional corrected coordinates.

[0015] In one embodiment, the determining the intrinsic parameters and distortion coefficients of the camera in the binocular camera system by the Zhang Zhengyou calibration method includes:

[0016] A projection perspective model is constructed, and the mathematical expression of the projection perspective model is:

[0017]

[0018] Where s is the scale factor, (X w ,Y w ,Z w ) is the first three-dimensional coordinate of the wth target among the multiple targets, (x w ,y w ) is the first two-dimensional coordinate of the w-th target, K is the intrinsic parameter matrix formed by the intrinsic parameters, R is the rotation matrix corresponding to the extrinsic parameters, and t is the translation vector corresponding to the extrinsic parameters;

[0019] The internal parameter matrix K is solved using the first three-dimensional coordinates and the first two-dimensional coordinates corresponding to the multiple targets. The mathematical expression of the internal parameter matrix K is:

[0020]

[0021] Among them, f x and f y is the focal length of the camera in the x-axis and y-axis directions, (c x , c y ) are the principal point coordinates of the camera;

[0022] The distortion coefficient of the camera is determined using a least squares method.

[0023] In one embodiment, determining the distortion coefficient of the camera by using the least square method includes:

[0024] Construct the radial distortion coefficient equation and the tangential distortion coefficient equation, where:

[0025] The mathematical expression of the radial distortion coefficient equation is:

[0026]

[0027] The mathematical expression of the tangential distortion coefficient equation is:

[0028]

[0029] in, is the first two-dimensional coordinate of the w-th target after distortion elimination, and r is The distance between the principal coordinates of the phase,

[0030] The radial distortion coefficient equation and the tangential distortion coefficient equation are solved to obtain the radial distortion coefficient (k1, k2, k3) and the tangential distortion coefficient (p1, p2) of the camera.

[0031] In one embodiment, determining the extrinsic parameters of the camera based on the first three-dimensional coordinates and the corrected first two-dimensional corrected coordinates includes:

[0032] Based on the first three-dimensional coordinates and the corrected first two-dimensional correction coordinates, the external parameters of the camera are determined by using a PnP calibration method.

[0033] In one embodiment, the field of view overlap between the two cameras in the binocular camera is greater than 80%, and the number of the targets is not less than six.

[0034] A second aspect of the present disclosure provides a slope deformation monitoring device, the device comprising:

[0035] A target actual coordinate acquisition unit, used for acquiring, at a first moment, first three-dimensional coordinates of a plurality of targets arranged on the slope to be monitored;

[0036] A target image coordinate acquisition unit, used for acquiring a first two-dimensional image of the target using a binocular camera system to obtain a first two-dimensional coordinate of the target;

[0037] A camera parameter acquisition unit, configured to calibrate a camera in a binocular camera system based on the first two-dimensional coordinates and the first three-dimensional coordinates of the target, and obtain intrinsic parameters and extrinsic parameters of the camera;

[0038] a target actual coordinate conversion unit, used for collecting a second two-dimensional image of the target by using a binocular camera system at a second moment, and converting a second two-dimensional coordinate of the target on the second two-dimensional image into a second three-dimensional coordinate based on the intrinsic parameters and extrinsic parameters of the camera;

[0039] A judgment unit is used to judge that the slope to be monitored is deformed if the second three-dimensional coordinate is different from the first three-dimensional coordinate.

[0040] A third aspect of the present disclosure provides an electronic device, including:

[0041] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method described in the embodiment of the first aspect of the present disclosure.

[0042] The fourth aspect embodiment of the present disclosure proposes a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the method described in the first aspect embodiment of the present disclosure.

[0043] A fifth aspect embodiment of the present disclosure provides a computer program product, including a computer program, which implements the method described in the first aspect embodiment of the present disclosure when executed by a processor.

[0044] In summary, the present disclosure proposes a slope deformation monitoring method, device, electronic device, storage medium and product, the method comprising: at a first moment, obtaining the first three-dimensional coordinates of multiple targets set on the slope to be monitored; using a binocular camera system to collect a first two-dimensional image of the target to obtain the first two-dimensional coordinates of the target; based on the first two-dimensional coordinates and the first three-dimensional coordinates of the target, calibrating the camera in the binocular camera system to obtain the intrinsic parameters and extrinsic parameters of the camera; at a second moment, using the binocular camera system to collect a second two-dimensional image of the target, and based on the intrinsic parameters and extrinsic parameters of the camera, converting the second two-dimensional coordinates of the target on the second two-dimensional image into a second three-dimensional coordinate; if the second three-dimensional coordinates are different from the first three-dimensional coordinates, it is determined that the slope to be monitored is deformed.

[0045] The solution provided by the present invention monitors the three-dimensional coordinates of the target at different times through a binocular camera system, which can easily determine whether the slope is deformed. Compared with existing traditional measurement methods such as total stations and GPS, it has a wide range of applications, a short data collection cycle, and higher real-time performance. Especially under complex terrain conditions, it can perform large-scale high-precision real-time monitoring.

[0046] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute improper limitations on the present disclosure.

[0048] Figure 1 A schematic diagram of a process flow of a slope deformation monitoring method provided by an embodiment of the present disclosure;

[0049] Figure 2 A flowchart of a method for determining intrinsic parameters and extrinsic parameters provided in an embodiment of the present disclosure;

[0050] Figure 3 A schematic diagram of the structure of a slope deformation monitoring device provided in an embodiment of the present disclosure;

[0051] Figure 4 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0052] Embodiments of the present disclosure are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0053] In the field of open-pit mining, slope stability is an important factor in ensuring safe production and construction. Slope deformation monitoring can provide early warning of potential geological disasters and avoid casualties and property losses. Existing slope monitoring technologies mostly rely on traditional measurement methods such as total stations and GPS. Although these methods have been well verified in terms of accuracy and reliability, they have some technical limitations, such as limited measurement points, long data collection cycles, and poor real-time performance. Especially under complex terrain conditions, it is impossible to effectively carry out large-scale high-precision real-time monitoring.

[0054] In response to these problems, the slope monitoring method based on binocular vision technology has gradually attracted attention. Binocular vision technology simulates the stereoscopic vision principle of the human eye, uses two cameras to shoot the same scene from different angles, and then calculates the three-dimensional spatial position of the monitored object through a stereo matching algorithm. This technology has the advantages of light equipment, flexible deployment, and a large monitoring range. It is particularly suitable for continuous, real-time, and high-precision deformation monitoring of a large area in slope monitoring.

[0055] At present, although binocular vision-based slope monitoring has the above advantages, it still faces some problems and technical difficulties in practical applications. First, the layout and calibration of binocular cameras have high requirements. Since the monitoring accuracy of slope deformation directly depends on the layout accuracy of the camera and the three-dimensional coordinate measurement accuracy of the target, how to reasonably arrange the camera to ensure full coverage of the monitoring range while ensuring the stability of the camera is an urgent problem to be solved.

[0056] Secondly, the calibration process of the camera's internal and external parameters in the traditional binocular vision monitoring method is complex and easily affected by the environment. The natural environment of the slope varies greatly, such as strong light, rain, snow, wind and sand, which will affect the camera's shooting effect and reduce the monitoring accuracy. In addition, geological disaster monitoring requires high precision and real-time performance, while the existing visual matching algorithm and PnP solution have low computational efficiency under complex terrain conditions and are difficult to meet the requirements of real-time monitoring.

[0057] The reason for these problems is that the existing binocular vision technology lacks adaptability to complex natural environments. At the same time, target deployment, camera calibration and other links still rely on a lot of manual operations, making it difficult to achieve automated and efficient monitoring. In addition, the matching accuracy and calculation speed of binocular vision algorithms in large-scale scenes also have bottlenecks, especially in dynamic monitoring, which requires processing a large amount of video data, greatly increasing the computational complexity.

[0058] In order to solve the defects in the related technology, the solution provided by the present invention monitors the three-dimensional coordinates of the target at different times through a binocular camera system, which can easily determine whether the slope is deformed. Compared with existing traditional measurement methods such as total stations and GPS, it has a wide range of applications, a short data collection cycle, and higher real-time performance. Especially under complex terrain conditions, it can perform large-scale high-precision real-time monitoring.

[0059] The present disclosure is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0060] like Figure 1 As shown, Figure 1 The schematic diagram of the flow chart of the slope deformation monitoring method provided by the embodiment of the present disclosure. The slope deformation monitoring method provided by the embodiment of the present disclosure comprises the following steps:

[0061] Step 101, at a first moment, obtaining first three-dimensional coordinates of a plurality of targets set on a slope to be monitored;

[0062] In one embodiment, the first moment is the moment when the targets are arranged on the slope, that is, the moment before the slope deformation monitoring is formally carried out.

[0063] In one embodiment, the number of the targets is not less than six. Preferably, the number of the targets is sixty. The sixty targets can be evenly or unevenly arranged at different positions of the slope. For example, if there are multiple different contour lines on the slope, the sixty targets can be evenly arranged on each contour line.

[0064] In one embodiment, the first three-dimensional coordinates of the target may be acquired by using a total station or a traditional measurement method such as a GPS.

[0065] Step 102, using a binocular camera system to capture a first two-dimensional image of the target to obtain a first two-dimensional coordinate of the target;

[0066] In one embodiment, the binocular acquisition system is composed of two identical high-definition cameras, and the overlap of the fields of view of the two high-definition cameras is greater than eighty percent.

[0067] In one embodiment, the baseline length between the two high-definition cameras constituting the binocular camera system is defined as the first length, and the average distance between the two high-definition cameras and the center of the slope is defined as the second length. The setting positions of the two high-definition cameras should meet the following conditions: the ratio of the first length to the second length is within a preset base-to-depth ratio threshold range, and the preset base-to-depth ratio threshold range can be between 0.1 and 0.3.

[0068] In one embodiment, two high-definition cameras should be set at the commanding heights of the slope.

[0069] In one embodiment, a wire steel raised by 60 centimeters can be set at the commanding height of the high-definition camera to fix the high-definition camera to prevent the high-definition camera from becoming unstable due to environmental factors such as strong winds, which directly leads to inaccurate and unreliable slope deformation monitoring results.

[0070] Step 103, calibrating a camera in a binocular camera system based on the first two-dimensional coordinates and the first three-dimensional coordinates of the target to obtain intrinsic parameters and extrinsic parameters of the camera;

[0071] In one embodiment, if Figure 2 As shown, step 103 includes:

[0072] Step 201, determining the intrinsic parameters and distortion coefficients of the camera in the binocular camera system by Zhang Zhengyou calibration method;

[0073] In one embodiment, the Zhang Zhengyou calibration method is an existing mature technology. Specifically, step 201 includes:

[0074] A projection perspective model is constructed, and the mathematical expression of the projection perspective model is:

[0075]

[0076] Where s is the scale factor, (X w ,Y w ,Z w ) is the first three-dimensional coordinate of the wth target among the multiple targets, (x w ,y m ) is the first two-dimensional coordinate of the w-th target, K is the intrinsic parameter matrix formed by the intrinsic parameters, R is the rotation matrix corresponding to the extrinsic parameters, and t is the translation vector corresponding to the extrinsic parameters;

[0077] The internal parameter matrix K is solved using the first three-dimensional coordinates and the first two-dimensional coordinates corresponding to the multiple targets. The mathematical expression of the internal parameter matrix K is:

[0078]

[0079] Among them, f x and f y is the focal length of the camera in the x-axis and y-axis directions, (c x , c y ) are the principal point coordinates of the camera;

[0080] The distortion coefficient of the camera is determined using a least squares method.

[0081] In one embodiment, determining the distortion coefficient of the camera by using the least square method includes:

[0082] Construct the radial distortion coefficient equation and the tangential distortion coefficient equation, where:

[0083] The mathematical expression of the radial distortion coefficient equation is:

[0084]

[0085] The mathematical expression of the tangential distortion coefficient equation is:

[0086]

[0087] in, is the first two-dimensional coordinate of the w-th target after distortion elimination, and r is The distance between the principal coordinates of the phase,

[0088] The radial distortion coefficient equation and the tangential distortion coefficient equation are solved to obtain the radial distortion coefficient (k1, k2, k3) and the tangential distortion coefficient (p1, p2) of the camera.

[0089] Step 202, based on the intrinsic parameters and the distortion coefficients, correct the first two-dimensional coordinates to obtain corrected first two-dimensional coordinates;

[0090] In one embodiment, the coordinates in the image are corrected using the intrinsic parameters and the distortion coefficients, which is a well-known existing technology and will not be described in detail here.

[0091] In one embodiment, the first minimization reprojection error may also be used to optimize the intrinsic parameters of the camera. The mathematical expression of the first minimization reprojection error is:

[0092]

[0093] in, The first two-dimensional coordinate of the wth pixel in the first two-dimensional image before correction, p w is the first two-dimensional coordinate of the corresponding pixel in the first two-dimensional image calculated according to the first three-dimensional coordinate. The intrinsic parameters of the camera can be optimized by first minimizing the reprojection error.

[0094] Step 203: Determine the extrinsic parameters of the camera based on the first three-dimensional coordinates and the corrected first two-dimensional coordinates.

[0095] In one embodiment, step 203 includes:

[0096] Based on the first three-dimensional coordinates and the corrected first two-dimensional correction coordinates, the external parameters of the camera are determined by using a PnP calibration method.

[0097] Specifically, when the external parameters of the camera are determined using the PnP calibration method, the first three-dimensional coordinates need to be paired with the corrected first two-dimensional coordinates. w is the first two-dimensional coordinate after correction, M w is the corresponding first three-dimensional coordinate, then the PnP algorithm is used to solve the rotation matrix R and displacement vector t of the camera using the first three-dimensional coordinate and the corrected first two-dimensional coordinate, and then the optimal solution is obtained by minimizing the reprojection error. The second reprojection error is defined as:

[0098]

[0099] Among them, K is the matrix corresponding to the intrinsic parameters of the camera, (RM w +t) is the representation of the first three-dimensional coordinate in the camera coordinate system, (RM w +t) z is the depth value of the first three-dimensional coordinate.

[0100] In the process of solving the rotation matrix R and displacement vector t of the camera, the rotation matrix R is given in the form of a rotation vector. In this case, the rotation vector rvec can be converted to the rotation matrix R using the Rodrigues formula.

[0101] Step 104, at a second moment, using a binocular camera system to collect a second two-dimensional image of the target, and based on the intrinsic parameters and extrinsic parameters of the camera, converting the second two-dimensional coordinates of the target on the second two-dimensional image into second three-dimensional coordinates;

[0102] Step 105: If the second three-dimensional coordinates are different from the first three-dimensional coordinates, it is determined that the slope to be monitored is deformed.

[0103] In summary, the present disclosure proposes a slope deformation monitoring method including: at a first moment, obtaining first three-dimensional coordinates of multiple targets set on the slope to be monitored; using a binocular camera system to collect a first two-dimensional image of the target to obtain the first two-dimensional coordinates of the target; based on the first two-dimensional coordinates and the first three-dimensional coordinates of the target, calibrating the camera in the binocular camera system to obtain the intrinsic parameters and extrinsic parameters of the camera; at a second moment, using the binocular camera system to collect a second two-dimensional image of the target, and based on the intrinsic parameters and extrinsic parameters of the camera, converting the second two-dimensional coordinates of the target on the second two-dimensional image into second three-dimensional coordinates; if the second three-dimensional coordinates are different from the first three-dimensional coordinates, it is determined that the slope to be monitored is deformed.

[0104] The solution provided by the present invention monitors the three-dimensional coordinates of the target at different times through a binocular camera system, which can easily determine whether the slope is deformed. Compared with existing traditional measurement methods such as total stations and GPS, it has a wide range of applications, a short data collection cycle, and higher real-time performance. Especially under complex terrain conditions, it can perform large-scale high-precision real-time monitoring.

[0105] In order to implement the slope deformation monitoring method provided by the embodiment of the present disclosure, the embodiment of the present disclosure also provides a slope deformation monitoring device, such as Figure 3 shown. Figure 3 The schematic diagram of the structure of the slope deformation monitoring device provided in the embodiment of the present disclosure is as follows. The slope deformation monitoring device 300 comprises:

[0106] The target actual coordinate acquisition unit 301 is used to acquire, at a first moment, first three-dimensional coordinates of a plurality of targets set on the slope to be monitored;

[0107] A target image coordinate acquisition unit 302 is used to collect a first two-dimensional image of the target using a binocular camera system to obtain a first two-dimensional coordinate of the target;

[0108] A camera parameter acquisition unit 303 is used to calibrate the camera in the binocular camera system based on the first two-dimensional coordinates and the first three-dimensional coordinates of the target to obtain the intrinsic parameters and extrinsic parameters of the camera;

[0109] The target actual coordinate conversion unit 304 is used to collect a second two-dimensional image of the target by using a binocular camera system at a second moment, and convert the second two-dimensional coordinates of the target on the second two-dimensional image into second three-dimensional coordinates based on the intrinsic parameters and extrinsic parameters of the camera;

[0110] The judging unit 305 is configured to judge that deformation occurs on the slope to be monitored if the second three-dimensional coordinates are different from the first three-dimensional coordinates.

[0111] In one embodiment, the camera parameter acquisition unit 303 is specifically used to:

[0112] Determine the intrinsic parameters and distortion coefficients of the camera in the binocular camera system by using the Zhang Zhengyou calibration method;

[0113] Based on the intrinsic parameters and the distortion coefficients, correcting the first two-dimensional coordinates to obtain corrected first two-dimensional coordinates;

[0114] The extrinsic parameters of the camera are determined based on the first three-dimensional coordinates and the corrected first two-dimensional corrected coordinates.

[0115] In one embodiment, the camera parameter acquisition unit 303 is further specifically configured to:

[0116] A projection perspective model is constructed, and the mathematical expression of the projection perspective model is:

[0117]

[0118] Where s is the scale factor, (X w ,Y w , w ) is the first three-dimensional coordinate of the wth target among the multiple targets, (x w ,y w ) is the first two-dimensional coordinate of the w-th target, K is the intrinsic parameter matrix formed by the intrinsic parameters, R is the rotation matrix corresponding to the extrinsic parameters, and t is the translation vector corresponding to the extrinsic parameters;

[0119] The internal parameter matrix K is solved using the first three-dimensional coordinates and the first two-dimensional coordinates corresponding to the multiple targets. The mathematical expression of the internal parameter matrix K is:

[0120]

[0121] Among them, f x and f y is the focal length of the camera in the x-axis and y-axis directions, (c x , c y ) are the principal point coordinates of the camera;

[0122] The distortion coefficient of the camera is determined using a least squares method.

[0123] In one embodiment, the camera parameter acquisition unit 303 is further specifically configured to:

[0124] Construct the radial distortion coefficient equation and the tangential distortion coefficient equation, where:

[0125] The mathematical expression of the radial distortion coefficient equation is:

[0126]

[0127] The mathematical expression of the tangential distortion coefficient equation is:

[0128]

[0129] in, is the first two-dimensional coordinate of the w-th target after distortion elimination, and r is The distance between the principal coordinates of the phase,

[0130] The radial distortion coefficient equation and the tangential distortion coefficient equation are solved to obtain the radial distortion coefficient (k1, k2, k3) and the tangential distortion coefficient (p1, p2) of the camera.

[0131] In one embodiment, the camera parameter acquisition unit 303 is further specifically configured to:

[0132] Based on the first three-dimensional coordinates and the corrected first two-dimensional correction coordinates, the external parameters of the camera are determined by using a PnP calibration method.

[0133] In one embodiment, the field of view overlap between the two cameras in the binocular camera is greater than 80%, and the number of the targets is not less than six.

[0134] It should be noted that: the slope deformation monitoring device provided in the above embodiment only uses the division of the above program modules as an example when performing slope deformation monitoring. In actual applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the slope deformation monitoring device is divided into different program modules to complete all or part of the processing described above. In addition, the slope deformation monitoring device provided in the above embodiment and the slope deformation monitoring method embodiment provided in the embodiment of the present disclosure belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0135] Figure 4 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present disclosure is shown in FIG. Figure 4As shown, the electronic device 400 includes at least one processor 402; and a memory 401 communicatively connected to the at least one processor 402; wherein the memory 401 stores instructions executable by the at least one processor 402, and the instructions are executed by the at least one processor 402 to implement the steps of the slope deformation monitoring method described in the embodiment of the present disclosure.

[0136] Optionally, the electronic device may specifically be the slope deformation monitoring device of the embodiment of the present application, and the electronic device may implement the corresponding processes implemented by the slope deformation monitoring device in each method of the embodiment of the present application, which will not be described in detail here for the sake of brevity.

[0137] It is understood that the electronic device also includes a communication interface 403. The various components in the electronic device are coupled together through a bus system 404. It is understood that the bus system 404 is used to achieve connection and communication between these components. In addition to the data bus, the bus system 404 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Figure 4 Various buses are labeled as bus system 404 .

[0138] It can be understood that the memory 401 can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disk, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), direct memory bus random access memory (DRRAM). The memory 401 described in the embodiments of the present invention is intended to include but is not limited to these and any other suitable types of memory.

[0139] The method disclosed in the above embodiment of the present disclosure can be applied to the processor 402, or implemented by the processor 402. The processor 402 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit in the processor 402 or the instruction in the form of software. The above processor 402 may be a general-purpose processor, a DSP, or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor 402 can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or any conventional processor, etc. In combination with the steps of the method disclosed in the embodiment of the present invention, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in the memory 401, and the processor 402 reads the information in the memory 401 and completes the steps of the above method in combination with its hardware.

[0140] In an exemplary embodiment, the electronic device may be implemented by one or more application specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), FPGAs, general purpose processors, controllers, MCUs, microprocessors, or other electronic components to execute the aforementioned method.

[0141] The embodiment of the present disclosure also provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable the computer to implement the steps of the slope deformation monitoring method described in the embodiment of the present disclosure when executed.

[0142] The embodiment of the present disclosure also provides a computer program product, including a computer program, which implements the steps of the slope deformation monitoring method described in the embodiment of the present disclosure when executed by a processor.

[0143] Optionally, the computer-readable storage medium can be applied to the slope deformation monitoring device in the embodiments of the present application, and the computer instructions enable the computer to execute the corresponding processes implemented by the slope deformation monitoring device in the various methods of the embodiments of the present application. For the sake of brevity, they will not be repeated here.

[0144] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0145] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0146] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0147] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above-mentioned method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium, which, when executed, executes the steps of the above-mentioned method embodiment; and the aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, disks or optical disks.

[0148] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0149] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A slope deformation monitoring method, characterized in that: include: At a first moment, obtaining first three-dimensional coordinates of a plurality of targets set on the slope to be monitored; Using a binocular camera system to collect a first two-dimensional image of the target to obtain a first two-dimensional coordinate of the target; Based on the first two-dimensional coordinates and the first three-dimensional coordinates of the target, calibrate the camera in the binocular camera system to obtain the intrinsic parameters and extrinsic parameters of the camera; At a second moment, using a binocular camera system to collect a second two-dimensional image of the target, and based on the intrinsic parameters and extrinsic parameters of the camera, converting a second two-dimensional coordinate of the target on the second two-dimensional image into a second three-dimensional coordinate; If the second three-dimensional coordinates are different from the first three-dimensional coordinates, it is determined that the slope to be monitored is deformed.

2. The method according to claim 1, characterized in that The step of calibrating a camera in a binocular camera system based on the first two-dimensional coordinates and the first three-dimensional coordinates of the target to obtain intrinsic parameters and extrinsic parameters of the camera includes: Determine the intrinsic parameters and distortion coefficients of the camera in the binocular camera system by using the Zhang Zhengyou calibration method; Based on the intrinsic parameters and the distortion coefficients, correcting the first two-dimensional coordinates to obtain corrected first two-dimensional coordinates; The extrinsic parameters of the camera are determined based on the first three-dimensional coordinates and the corrected first two-dimensional corrected coordinates.

3. The method according to claim 2, characterized in that The method of determining the intrinsic parameters and distortion coefficients of the camera in the binocular camera system by using the Zhang Zhengyou calibration method includes: A projection perspective model is constructed, and the mathematical expression of the projection perspective model is: Where s is the scale factor, (X w ,Y w ,Z w ) is the first three-dimensional coordinate of the wth target among the multiple targets, (x w ,y w ) is the first two-dimensional coordinate of the w-th target, K is the intrinsic parameter matrix formed by the intrinsic parameters, R is the rotation matrix corresponding to the extrinsic parameters, and t is the translation vector corresponding to the extrinsic parameters; The internal parameter matrix K is solved using the first three-dimensional coordinates and the first two-dimensional coordinates corresponding to the multiple targets. The mathematical expression of the internal parameter matrix K is: Among them, f x and f y is the focal length of the camera in the x-axis and y-axis directions, (c x , c y ) are the principal point coordinates of the camera; The distortion coefficient of the camera is determined using a least squares method.

4. The method according to claim 3, characterized in that The method of determining the distortion coefficient of the camera by using the least square method includes: Construct the radial distortion coefficient equation and the tangential distortion coefficient equation, where: The mathematical expression of the radial distortion coefficient equation is: The mathematical expression of the tangential distortion coefficient equation is: in, is the first two-dimensional coordinate of the wth target after distortion elimination, and r is The distance between the principal coordinates of the phase, The radial distortion coefficient equation and the tangential distortion coefficient equation are solved to obtain the radial distortion coefficient (k1, k2, k3) and the tangential distortion coefficient (p1, p2) of the camera.

5. The method according to claim 2, characterized in that: The determining the extrinsic parameters of the camera based on the first three-dimensional coordinates and the corrected first two-dimensional corrected coordinates includes: Based on the first three-dimensional coordinates and the corrected first two-dimensional correction coordinates, the external parameters of the camera are determined by using a PnP calibration method.

6. The method according to claim 1, characterized in that The overlap of the fields of view of the two cameras in the binocular camera is greater than 80 percent, and the number of the targets is not less than six.

7. A slope deformation monitoring device, characterized in that: include: A target actual coordinate acquisition unit, used for acquiring, at a first moment, first three-dimensional coordinates of a plurality of targets arranged on the slope to be monitored; A target image coordinate acquisition unit, used for acquiring a first two-dimensional image of the target using a binocular camera system to obtain a first two-dimensional coordinate of the target; A camera parameter acquisition unit, configured to calibrate a camera in a binocular camera system based on the first two-dimensional coordinates and the first three-dimensional coordinates of the target, and obtain intrinsic parameters and extrinsic parameters of the camera; a target actual coordinate conversion unit, used for collecting a second two-dimensional image of the target by using a binocular camera system at a second moment, and converting a second two-dimensional coordinate of the target on the second two-dimensional image into a second three-dimensional coordinate based on the intrinsic parameters and extrinsic parameters of the camera; A judgment unit is used to judge that the slope to be monitored is deformed if the second three-dimensional coordinate is different from the first three-dimensional coordinate.

8. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that A computer program is included which, when executed by a processor, implements the method according to any one of claims 1 to 6.

Images