A method, device, electronic equipment, and storage medium for capturing images.

Abstract

This application discloses a method, device, electronic device, and storage medium for capturing images, relating to the field of computer technology. The method includes: when an abnormal monitoring point is detected in an area to be inspected, calculating the shooting parameters of a camera component based on the point cloud data of the abnormal monitoring point acquired by a radar component; and controlling the camera component to take a picture of the abnormal monitoring point based on the shooting parameters, thereby obtaining an image of the abnormal monitoring point. The technical solution provided by this application can quickly and accurately capture abnormal monitoring points in slopes exhibiting foundation deformation, improving the efficiency of slope monitoring.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a method, device, electronic device and storage medium for capturing images. Background Technology

[0002] Artificial or natural high slopes can disrupt the original stable structure of mountains. Under the influence of factors such as heavy rainfall, earthquakes, and construction excavation, they can easily trigger geological disasters such as landslides, collapses, or mudslides, seriously threatening the lives and property of the people.

[0003] Currently, slope monitoring typically employs a combination of ground deformation monitoring radar and external (or internal) cameras. This means that radar collects data, and if ground deformation is detected, the data is uploaded to a cloud platform. Management personnel then use the external (or internal) cameras to capture images on-site. Figure 1 As shown, the left image is a schematic diagram of a combination scheme of ground deformation monitoring radar and an external camera, while the right image is a schematic diagram of a combination scheme of ground deformation monitoring radar and an internal camera. However, because the monitoring area of ​​radar ground deformation is wide and image capture requires manual management, this method cannot quickly and accurately capture corresponding landslide locations, resulting in low efficiency in slope monitoring. Therefore, how to improve the efficiency and accuracy of slope monitoring has become an urgent problem to be solved. Summary of the Invention

[0004] This application provides a method, device, electronic equipment, and storage medium for capturing images, which can quickly and accurately capture abnormal monitoring points in slopes where foundation deformation exists, thereby improving the efficiency of slope monitoring.

[0005] In a first aspect, this application provides a method for capturing images, the method being applied to an image capture device, the image capture device including a radar component and a camera component, the method comprising:

[0006] When an abnormal monitoring point is detected in the area to be inspected, the shooting parameters of the camera component are calculated based on the point cloud data of the abnormal monitoring point acquired by the radar component.

[0007] Based on the shooting parameters, the camera component is controlled to take pictures of the abnormal monitoring point to obtain an image of the abnormal monitoring point.

[0008] Furthermore, the area to be inspected includes multiple sub-regions divided based on the field of view of the capture device, and each sub-region contains several monitoring points; the detection of abnormal monitoring points from the area to be inspected includes: for the current sub-region, acquiring point cloud data of the monitoring points contained in the current sub-region; determining whether the current sub-region contains the abnormal monitoring point based on the point cloud data of the monitoring points; traversing the multiple sub-regions to obtain the sub-regions in the area to be inspected where the abnormal monitoring point exists, thereby completing the abnormal monitoring point detection task.

[0009] Furthermore, determining whether the abnormal monitoring point exists in the current sub-region based on the point cloud data of the monitoring point includes: determining the displacement of the monitoring point within the current monitoring period based on the point cloud data of the monitoring point; determining the target monitoring point with the largest displacement among the monitoring points, and using the largest displacement as the displacement of the current sub-region; and determining that the abnormal monitoring point exists in the current sub-region when the displacement of the current sub-region exceeds a preset threshold.

[0010] Furthermore, the field of view of the capture device includes the field of view of the radar component and the field of view of the camera component; based on the field of view of the capture device, the area to be inspected is divided into multiple sub-regions in the following manner: a first multiple value is calculated between the horizontal field of view of the radar component and the horizontal field of view of the camera component, and a second multiple value is calculated between the vertical field of view of the radar component and the vertical field of view of the camera component; data processing is performed on the horizontal field of view of the radar component and the first multiple value to obtain the horizontal field of view corresponding to a sub-region, and data processing is performed on the vertical field of view of the radar component and the second multiple value to obtain the vertical field of view corresponding to a sub-region; based on the horizontal and vertical field of view corresponding to the sub-region, the area to be inspected is divided into the multiple sub-regions.

[0011] Furthermore, the shooting parameters include camera parameters and motion parameters of the gimbal used to drive the camera assembly; the calculation of the shooting parameters of the camera assembly based on the point cloud data of the anomaly monitoring points acquired by the radar assembly includes: calculating the distance between the anomaly monitoring point and the camera assembly based on the point cloud data of the anomaly monitoring point, and calculating the pose information of the camera assembly based on the point cloud data of the anomaly monitoring point, the pose information including the target shooting position and target shooting angle for shooting the anomaly monitoring point; determining the camera parameters of the camera assembly based on the distance; and calculating the motion parameters of the camera assembly moving to the target shooting position and at the target shooting angle based on the pose information.

[0012] Furthermore, the step of controlling the camera component to take pictures of the abnormal monitoring point based on the shooting parameters to obtain an image of the abnormal monitoring point includes: determining the target sub-region where the abnormal monitoring point is located; controlling the camera component to move to the target shooting position and be at the target shooting angle based on the motion parameters; and controlling the camera component to take pictures of the target sub-region based on the camera parameters to obtain an image containing the image corresponding to the abnormal monitoring point.

[0013] Furthermore, before determining the camera parameters of the imaging component based on the distance, the method further includes: determining the horizontal and vertical field of view of one sub-region among the plurality of sub-regions; determining the number of pixels corresponding to the one sub-region captured at a preset quality standard; correspondingly, determining the camera parameters of the imaging component based on the distance includes: determining the camera parameters of the imaging component based on the horizontal and vertical field of view of the one sub-region, the number of pixels, and the distance.

[0014] Secondly, this application provides a snapshot device, which is integrated into a snapshot device, the snapshot device including a radar component and a camera component, the device comprising:

[0015] The shooting parameter determination module is used to calculate the shooting parameters of the camera component based on the point cloud data of the abnormal monitoring points acquired by the radar component when an abnormal monitoring point is detected from multiple monitoring points in the area to be inspected.

[0016] An image capturing module is used to control the camera component to take pictures of the abnormal monitoring point based on the capturing parameters, thereby obtaining an image of the abnormal monitoring point.

[0017] Thirdly, this application provides an electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the snapshot method described in any embodiment of this application.

[0018] Fourthly, this application provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the snapshot method described in any embodiment of this application.

[0019] To address the shortcomings of existing technologies, this application provides a snapshot method that offers the following advantages: The snapshot device incorporates both a radar component and a camera component. The radar component acquires point cloud data of abnormal monitoring points, and the camera component calculates its shooting parameters based on the point cloud data. This allows the camera component to capture images of the abnormal monitoring points. Furthermore, by fusing data from the radar and camera components, the application enables automated snapshot capture by the camera component, eliminating the need for manual operation. This method allows for rapid and accurate capture of abnormal monitoring points on slopes exhibiting foundation deformation, addressing the current limitations of camera-based snapshot capture and improving the efficiency of slope monitoring.

[0020] It should be noted that the aforementioned computer instructions may be stored, in whole or in part, on a computer-readable storage medium. This computer-readable storage medium may be packaged together with the processor of the image capture device, or it may be packaged separately from the processor of the image capture device; this application does not impose any limitations on this.

[0021] The descriptions of the second, third, and fourth aspects in this application can be referenced to the detailed description of the first aspect; and the beneficial effects described in the second, third, and fourth aspects can be referenced to the analysis of the beneficial effects of the first aspect, which will not be repeated here.

[0022] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description.

[0023] It is understood that before using the technical solutions disclosed in the various embodiments of this application, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this application in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a schematic diagram of the structure of a current-technical image capture device;

[0026] Figure 2 This is a first flowchart illustrating a snapshot method provided in an embodiment of this application;

[0027] Figure 3This is a schematic diagram of the second process of a snapshot method provided in an embodiment of this application;

[0028] Figure 4 This is a schematic diagram of the structure of a snapshot device provided in an embodiment of this application;

[0029] Figure 5 This is a block diagram of an electronic device used to implement a snapshot method according to an embodiment of this application. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this application.

[0031] It should be noted that the terms "first," "second," "target," and "original," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in sequences other than those illustrated or described herein. Furthermore, the terms "comprising," "having," and any variations thereof are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] Figure 2 This is a schematic diagram of the first process of a snapshot method provided in this application embodiment. This embodiment is applicable to slope monitoring, where abnormal monitoring points are detected by a radar component and captured by a camera component. The snapshot method provided in this embodiment can be executed by the snapshot device provided in this application embodiment. This device can be implemented by software and / or hardware and integrated into the electronic device executing the method. Preferably, the electronic device in this application embodiment can be a snapshot device, which includes a radar component and a camera component. The radar component and camera component can be coaxially mounted and deployed on the same motion mechanism; alternatively, the radar component and camera component can be mounted on different axes and deployed on different motion mechanisms.

[0033] See Figure 2 The method in this embodiment includes, but is not limited to, the following steps:

[0034] S110. When an abnormal monitoring point is detected in the area to be inspected, the shooting parameters of the camera component are calculated based on the point cloud data of the abnormal monitoring point obtained by the radar component.

[0035] The area to be monitored refers to the area that needs to be monitored in slope monitoring. This area includes multiple monitoring points, with abnormal monitoring points being those exhibiting ground deformation (such as landslides, collapses, or debris flows). This implementation does not limit the specific forms of the radar and camera components; the radar component can be a radar sensor, and the camera component can be a camera. The shooting parameters include camera parameters and the motion parameters of the pan-tilt unit used to drive the camera component. Point cloud data can include the three-dimensional coordinates of the abnormal monitoring points in space, and may also include color, normal vectors, and intensity values.

[0036] In one optional embodiment, during the detection of the area to be inspected, the radar component can divide the area into multiple small grids based on its azimuth and range resolution, with each small grid being a minimum resolution unit. A single point within each small grid (referred to as a monitoring point) can replace the entire small grid; that is, the area to be inspected is divided into multiple monitoring points. The radar component performs slope monitoring on these monitoring points and identifies anomalous monitoring points exhibiting foundation deformation from among the multiple monitoring points. The specific process for determining these anomalous monitoring points will be detailed later. Figure 3 The corresponding embodiments are explained in detail.

[0037] Specifically, the shooting parameters can include camera parameters and motion parameters. The shooting parameters of the camera component are calculated based on the point cloud data of the anomaly detection points acquired by the radar component. This includes: acquiring the point cloud data of the anomaly detection points through the radar component; calculating the first distance between the anomaly detection point and the radar component using a spatial distance formula based on the three-dimensional coordinate information in the point cloud data; and determining the camera parameters of the camera component based on this distance. It is also necessary to calculate the pose information of the camera component based on the point cloud data of the anomaly detection points. Based on the pose information, the motion parameters of the camera component's motion mechanism (such as a gimbal) are calculated using a preset spatial motion formula, so that the motion mechanism can move the camera component from its current position to the target shooting position and at the target shooting angle.

[0038] The camera parameters of the camera component are determined based on the distance between the anomaly detection point and the camera component. The calculation process can be as follows: the camera parameters may include focal length values. A first association table is formed, showing the focal length value corresponding to a target distance that the camera component can clearly capture, based on a pre-set parameter. This first association table is stored in the storage unit of the capture device or a storage unit configured within the camera component. After determining the distance between the anomaly detection point and the camera component, the first association table is retrieved from the storage unit, and the focal length value corresponding to that distance is found. Based on this distance, the focal length value that can be clearly captured at the anomaly detection point is calculated. This configuration improves the response speed of the camera component's capture.

[0039] The process of calculating the pose information of the camera component based on the point cloud data of the anomaly monitoring point can be as follows: First, calculate the first azimuth and first elevation angles of the radar component observing the anomaly monitoring point based on the three-dimensional coordinate information in the point cloud data. Second, based on the azimuth and distance relationship between the radar component and the camera component deployed in the capture device, convert the first azimuth and first elevation angles into the second azimuth and second elevation angles of the camera component observing the anomaly monitoring point, and then calculate the pose information of the camera component capturing the anomaly monitoring point. The pose information includes the target shooting position and target shooting angle used to capture the anomaly monitoring point.

[0040] Optionally, motion parameters for each monitoring point can be pre-determined, and a second association table can be obtained by associating the point cloud data of each monitoring point with the motion parameters corresponding to the clearly captured images of that monitoring point by the camera. After obtaining the point cloud data of an abnormal monitoring point, the second association table is then used to query the motion parameters corresponding to the motion mechanism of the camera component. This setup can also improve the response speed of the camera component's image capture.

[0041] S120: Based on the shooting parameters, control the camera component to take pictures of the abnormal monitoring points and obtain images of the abnormal monitoring points.

[0042] In this embodiment, the motion mechanism corresponding to the camera component is controlled to move based on motion parameters, so as to move the camera component from its current position to the target shooting position and to the target shooting angle; the camera focal length of the camera component is adjusted based on the determined focal length value, and then the camera component is controlled to take pictures of the abnormal monitoring point to obtain the image of the abnormal monitoring point.

[0043] Optionally, the radar and camera components can be coaxially mounted and share a motion mechanism, enabling the camera component to capture precise images.

[0044] The technical solution provided in this embodiment calculates the shooting parameters of the camera component based on the point cloud data of the abnormal monitoring point acquired by the radar component when an abnormal monitoring point is detected in the area to be inspected. Based on the shooting parameters, the camera component is controlled to take a picture of the abnormal monitoring point to obtain an image of the abnormal monitoring point. This application simultaneously configures a radar component and a camera component in the capture device. The radar component acquires the point cloud data of the abnormal monitoring point, calculates the shooting parameters of the camera component based on the point cloud data, and then controls the camera component to take a picture of the abnormal monitoring point to obtain an image. This application fuses the data of the radar component and the camera component, enabling automated capture by the camera component without manual operation. It can quickly and accurately capture abnormal monitoring points with foundation deformation in the slope, solving the current pain points of camera capture and improving the efficiency of slope monitoring.

[0045] The following further describes the image capture method provided in the embodiments of this application. In another optional embodiment of this application, the main challenge of the image capture method that integrates radar components and camera components is that when the number of monitoring points monitored by the radar is in the millions, it is impossible to ensure that the radar works normally while capturing images of different monitoring points. For example, if a radar has a scanning range of 0 to 180° and an azimuth resolution of 1°, and a monitoring distance of 2 km and a range resolution of 0.3 m, the estimated data volume is (180 / 1)*(2000 / 0.3) = 1,200,000. That is, at the maximum monitoring range and distance, there are a total of 1,200,000 monitoring points. For example, if there are 100 points on a slope, and assuming that capturing one point takes 10 seconds, then it would take 1,000 seconds to capture the image, and there is also the possibility of repeatedly capturing the same monitoring point, which is inefficient.

[0046] To address this challenge, the following method is adopted: First, the area to be inspected can be divided into multiple sub-regions based on the field of view of the capture device. Each sub-region contains several (or a preset number) monitoring points. In slope monitoring, the task of detecting abnormal monitoring points from the area to be inspected is accomplished by determining whether there are abnormal monitoring points in each sub-region. Using sub-regions to represent the monitoring points contained within each sub-region reduces the amount of data from monitoring points without missing any reports. The specific process for determining whether there are abnormal monitoring points in each sub-region will be discussed later. Figure 3The corresponding embodiments are explained below. Secondly, instead of capturing images of individual monitoring points, a method of capturing images of sub-regions is used, thus reducing the problem of duplicate captures. For example, assuming a sub-region has 100 monitoring points, if an abnormal monitoring point exists within that sub-region, regardless of whether there is one or more abnormal monitoring points, the camera component will only capture one image of the entire sub-region. Optionally, since the resolution of the camera component is based on angle, while the resolution of the radar component includes both angle and distance, the units are not uniform; this embodiment can use angular resolution to normalize the units of the entire system.

[0047] Specifically, the inspection area is divided into multiple sub-regions based on the field of view of the capture device. This can include the field of view of the capture device, encompassing both the radar component's and the camera component's fields of view. First, a first multiple is calculated between the horizontal field of view of the radar component and the horizontal field of view of the camera component. A second multiple is calculated between the vertical field of view of the radar component and the vertical field of view of the camera component. Then, data processing is performed on the horizontal field of view of the radar component and the first multiple to obtain the horizontal field of view corresponding to a sub-region. Similarly, data processing is performed on the vertical field of view of the radar component and the second multiple to obtain the vertical field of view corresponding to a sub-region. Finally, the inspection area is divided into multiple sub-regions based on the horizontal and vertical field of view of each sub-region.

[0048] For example, assume the horizontal and vertical field of view of the camera assembly are 5°*4°, and the horizontal and vertical field of view of the radar assembly are 180°*30°. The first multiplier is 180 / 5 = 36, so we take 37; the second multiplier is 30 / 4 = 7.5, so we take 8; the horizontal field of view corresponding to one sub-region is 180 / 37 = 4.865°; the vertical field of view corresponding to one sub-region is 30 / 8 = 3.75°; the horizontal and vertical field of view corresponding to one sub-region is 4.865°*3.75°; the total number of sub-regions is 37*8 = 296. Optionally, each sub-region has the same size, and each sub-region contains the same number of monitoring points.

[0049] Furthermore, before determining the camera parameters of the camera component based on the distance between the anomaly detection point and the camera component, the process includes: determining the horizontal and vertical field of view of one sub-region among multiple sub-regions; and determining the number of pixels corresponding to a sub-region to be captured at a preset quality standard, such as four pixels; wherein, the preset quality standard means that the captured image can clearly and accurately observe the detailed features of objects within the sub-region. Correspondingly, determining the camera parameters of the camera component based on the distance between the anomaly detection point and the camera component includes: determining the focal length value in the camera parameters of the camera component based on the horizontal and vertical field of view of a sub-region, the number of pixels, and the distance, and then capturing images of the sub-region containing the anomaly detection point at standard quality.

[0050] Furthermore, based on the shooting parameters, the camera component is controlled to take pictures of the abnormal monitoring points to obtain images of the abnormal monitoring points. This includes: determining the target sub-region where the abnormal monitoring point is located; controlling the motion mechanism corresponding to the camera component to move based on the motion parameters, so that the camera component is moved from its current position to the target shooting position and at the target shooting angle; adjusting the camera focal length of the camera component based on the determined focal length value, and then controlling the camera component to take pictures of the target sub-region to obtain an image containing the image corresponding to the abnormal monitoring point.

[0051] The image capture method provided in the embodiments of this application is further described below. Figure 3 This is a second flowchart illustrating a snapshot method provided in an embodiment of this application. This embodiment is an optimization based on the above embodiments, specifically an optimization that provides a detailed explanation of the detection process for abnormal monitoring points.

[0052] See Figure 3 The method in this embodiment includes, but is not limited to, the following steps:

[0053] S210. For the current sub-region, obtain the point cloud data of the monitoring points contained in the current sub-region.

[0054] The area to be inspected includes multiple sub-areas divided by the field of view of the capture device, and each sub-area contains several monitoring points.

[0055] In this embodiment of the application, during the slope monitoring of the area to be inspected, point cloud data of the monitoring points contained in each sub-area are acquired by the radar component in each monitoring cycle.

[0056] S220. Determine the displacement of the monitoring points within the current monitoring period based on the point cloud data of the monitoring points.

[0057] In this embodiment of the application, the displacement of each monitoring point is determined by comparing it with the point cloud data acquired in the previous monitoring cycle.

[0058] S230. Determine the target monitoring point with the largest displacement among the monitoring points, and use the largest displacement as the displacement of the current sub-region.

[0059] In this embodiment of the application, the displacement of each monitoring point contained in the current sub-region is sorted from high to low to determine the target monitoring point with the largest displacement. The target monitoring point with the most obvious displacement (maximum displacement) represents the current sub-region, and the displacement of the current sub-region is the determined maximum displacement.

[0060] S240. When the displacement of the current sub-region exceeds the preset threshold, it is determined that there is an abnormal monitoring point in the current sub-region.

[0061] In this embodiment of the application, it is determined whether the displacement of the current sub-region exceeds a preset threshold. If it does not exceed the preset threshold, it is determined that there is no abnormal monitoring point in the current sub-region and no snapshot is required. If it exceeds the preset threshold, it is determined that there is an abnormal monitoring point in the current sub-region and snapshot is required.

[0062] S250. Traverse multiple sub-regions to obtain the sub-regions in the area to be inspected that contain abnormal monitoring points, thereby completing the task of detecting abnormal monitoring points.

[0063] In this embodiment of the application, based on the above steps, each sub-region in multiple sub-regions is traversed to obtain the sub-region in the region to be inspected that contains abnormal monitoring points, thereby completing the detection task of abnormal monitoring points.

[0064] The technical solution provided in this embodiment acquires point cloud data of the monitoring points contained in the current sub-region; determines the displacement of the monitoring points within the current monitoring period based on the point cloud data; identifies the target monitoring point with the largest displacement and uses the largest displacement as the displacement of the current sub-region; when the displacement of the current sub-region exceeds a preset threshold, it is determined that there is an abnormal monitoring point in the current sub-region; and iterates through multiple sub-regions to obtain the sub-regions in the area to be inspected that contain abnormal monitoring points, thereby completing the task of detecting abnormal monitoring points. This application divides the area to be inspected into multiple sub-regions, using each sub-region to represent the monitoring points contained in that sub-region. By determining whether there are abnormal monitoring points in each sub-region, the task of detecting abnormal monitoring points in the area to be inspected is completed. This embodiment can simplify the massive amount of data in radar monitoring, reduce the difficulty of capturing images, and improve the efficiency of slope monitoring.

[0065] Figure 4 This is a schematic diagram of the structure of a snapshot device provided in an embodiment of this application, as shown below. Figure 4 As shown, the device is integrated into a capture device, which includes a radar component and a camera component. The device 400 may include:

[0066] The shooting parameter determination module 410 is used to calculate the shooting parameters of the camera component based on the point cloud data of the abnormal monitoring points acquired by the radar component when an abnormal monitoring point is detected from multiple monitoring points in the area to be inspected.

[0067] The image capturing module 420 is used to control the camera component to take pictures of the abnormal monitoring point based on the capturing parameters, so as to obtain an image of the abnormal monitoring point.

[0068] Optionally, the area to be inspected includes multiple sub-areas divided based on the field of view of the capture device, and each sub-area contains several monitoring points;

[0069] Furthermore, the aforementioned capture device may also include: an abnormal monitoring point determination module;

[0070] The abnormal monitoring point determination module is used to acquire point cloud data of monitoring points contained in the current sub-region for the current sub-region; determine whether the abnormal monitoring point exists in the current sub-region based on the point cloud data of the monitoring points; traverse the multiple sub-regions to obtain the sub-regions in the region to be inspected that contain abnormal monitoring points, thereby completing the abnormal monitoring point detection task.

[0071] Furthermore, the aforementioned abnormal monitoring point determination module can also be specifically used to: determine the point displacement of the monitoring point within the current monitoring period based on the point cloud data of the monitoring point; determine the target monitoring point with the maximum point displacement among the monitoring points, and use the maximum point displacement as the displacement of the current sub-region; when the displacement of the current sub-region exceeds a preset threshold, determine that the abnormal monitoring point exists in the current sub-region.

[0072] Optionally, the field of view of the capture device includes the field of view of the radar component and the field of view of the camera component;

[0073] Furthermore, the aforementioned image capture device may also include: a module for dividing the area to be inspected;

[0074] The inspection area division module is used to calculate a first multiple between the horizontal field of view of the radar component and the horizontal field of view of the camera component, and to calculate a second multiple between the vertical field of view of the radar component and the vertical field of view of the camera component; to process the horizontal field of view of the radar component and the first multiple to obtain the horizontal field of view of a sub-region, and to process the vertical field of view of the radar component and the second multiple to obtain the vertical field of view of a sub-region; and to divide the inspection area into multiple sub-regions based on the horizontal and vertical field of view of the sub-region.

[0075] Optionally, the shooting parameters include camera parameters and motion parameters of the gimbal used to drive the camera assembly;

[0076] Furthermore, the aforementioned shooting parameter determination module 410 can be specifically used to: calculate the distance between the anomaly monitoring point and the camera component based on the point cloud data of the anomaly monitoring point, and calculate the pose information of the camera component based on the point cloud data of the anomaly monitoring point, wherein the pose information includes the target shooting position and target shooting angle for shooting the anomaly monitoring point; determine the camera parameters of the camera component based on the distance; and calculate the motion parameters of the camera component moving to the target shooting position and at the target shooting angle based on the pose information.

[0077] Furthermore, the image capturing module 420 described above can be specifically used to: determine the target sub-region where the abnormal monitoring point is located; control the camera component to move to the target shooting position and be at the target shooting angle based on the motion parameters; control the camera component to take pictures of the target sub-region based on the camera parameters, and obtain an image containing the image corresponding to the abnormal monitoring point.

[0078] Furthermore, the aforementioned image capture device may also include: a parameter determination module;

[0079] The parameter determination module is used to determine the horizontal and vertical field of view of one sub-region among the plurality of sub-regions before determining the camera parameters of the imaging component based on the distance; and to determine the number of pixels corresponding to the one sub-region captured with a preset quality standard.

[0080] Correspondingly, the shooting parameter determination module 410 can also be specifically used to: determine the camera parameters of the camera component based on the horizontal and vertical field of view of the sub-region, the number of pixels, and the distance.

[0081] The image capture device provided in this embodiment can be applied to any of the image capture methods provided in the above embodiments, and has the corresponding functions and beneficial effects.

[0082] Figure 5 This is a block diagram of an electronic device used to implement a snapshot method according to an embodiment of this application. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present application described and / or claimed herein.

[0083] like Figure 5As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0084] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0085] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the snapshot method.

[0086] In some embodiments, the snapshot method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the snapshot method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the snapshot method by any other suitable means (e.g., by means of firmware).

[0087] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0088] Computer programs used to implement the methods of this application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0089] In the context of this application, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0090] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0091] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0092] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0093] Note that the above are merely preferred embodiments and technical principles applied in this application. Those skilled in the art will understand that this application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of this application. For example, those skilled in the art can use the various forms of processes shown above to reorder, add, or delete steps; the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solution of this application can be achieved, and no limitations are imposed herein.

[0094] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method of snapshotting, characterized by, The method is applied to a snapshot device including a radar component and a camera component, and the method comprises: When an abnormal monitoring point is detected in a to-be-inspected area, a shooting parameter of the camera component is calculated based on point cloud data of the abnormal monitoring point acquired by the radar component; The camera component is controlled to take a photo of the abnormal monitoring point based on the shooting parameter, and an image of the abnormal monitoring point is obtained; The to-be-inspected area includes a plurality of sub-areas divided based on a field of view angle of the snapshot device, and each sub-area contains a plurality of monitoring points; the detection of the abnormal monitoring point in the to-be-inspected area comprises: For a current sub-area, point cloud data of the monitoring points contained in the current sub-area is acquired; A point position displacement of the monitoring points in a current monitoring period is determined based on the point cloud data of the monitoring points; A target monitoring point with a maximum point position displacement is determined from the monitoring points, and the maximum point position displacement is taken as a displacement of the current sub-area; When the displacement of the current sub-area exceeds a preset threshold, it is determined that the current sub-area has the abnormal monitoring point; The plurality of sub-areas in the to-be-inspected area having the abnormal monitoring point are obtained by traversing the plurality of sub-areas, so as to complete the detection of the abnormal monitoring point.

2. The snapshot method of claim 1, wherein, The field of view angle of the snapshot device includes a field of view angle of the radar component and a field of view angle of the camera component; the to-be-inspected area is divided into a plurality of sub-areas based on the field of view angle of the snapshot device by the following method: A first multiple value between a horizontal field of view angle of the radar component and a horizontal field of view angle of the camera component is calculated, and a second multiple value between a vertical field of view angle of the radar component and a vertical field of view angle of the camera component is calculated; A horizontal field of view angle corresponding to a sub-area is obtained by data processing on the horizontal field of view angle of the radar component and the first multiple value, and a vertical field of view angle corresponding to a sub-area is obtained by data processing on the vertical field of view angle of the radar component and the second multiple value; The to-be-inspected area is divided into the plurality of sub-areas based on the horizontal field of view angle and the vertical field of view angle corresponding to the sub-area.

3. The snapshot method of claim 1, wherein, The shooting parameter includes a camera parameter and a motion parameter for driving a holder of the camera component; the shooting parameter of the camera component is calculated based on the point cloud data of the abnormal monitoring point acquired by the radar component, comprising: The distance between the abnormal monitoring point and the camera component is calculated based on the point cloud data of the abnormal monitoring point, and the pose information of the camera component is calculated according to the point cloud data of the abnormal monitoring point, the pose information including a target shooting position and a target shooting angle for shooting the abnormal monitoring point; The camera parameter of the camera component is determined according to the distance; The motion parameter of the camera component moving to the target shooting position and being at the target shooting angle is calculated based on the pose information.

4. The snapshot method of claim 3, wherein, The camera component is controlled to take a photo of the abnormal monitoring point based on the shooting parameter, and an image of the abnormal monitoring point is obtained, comprising: A target sub-area where the abnormal monitoring point is located is determined; control the camera assembly to move to the target shooting position and be at the target shooting angle based on the motion parameters; control the camera assembly to take a photo of the target sub-region based on the camera parameters, to obtain an image containing a corresponding image of the abnormal monitoring point.

5. The snapshot method of claim 3, wherein, Before the camera parameters of the camera assembly are determined according to the distance, the method further includes: determining a horizontal field of view angle and a vertical field of view angle of a sub-region in the plurality of sub-regions; determining a number of pixel points corresponding to the sub-region that are shot at a preset quality standard; Accordingly, the determination of the camera parameters of the camera assembly according to the distance includes: determining the camera parameters of the camera assembly based on the horizontal field of view angle and the vertical field of view angle of the sub-region, the number of pixel points, and the distance.

6. A snapshot device, characterized by The device is integrated into a snapshot device, the snapshot device includes a radar assembly and a camera assembly, and the device includes: a shooting parameter determination module configured to, when an abnormal monitoring point is detected from a plurality of monitoring points in a to-be-inspected region, calculate shooting parameters of the camera assembly based on point cloud data of the abnormal monitoring point acquired by the radar assembly; an image shooting module configured to control the camera assembly to take a photo of the abnormal monitoring point based on the shooting parameters, to obtain an image of the abnormal monitoring point; The to-be-inspected region includes a plurality of sub-regions divided based on a field of view angle of the snapshot device, and each sub-region contains a plurality of monitoring points; the device further includes an abnormal monitoring point determination module configured to: for a current sub-region, acquire point cloud data of monitoring points contained in the current sub-region; determine a point position displacement amount of the monitoring points in a current monitoring period based on the point cloud data of the monitoring points; determine a target monitoring point with a maximum point position displacement amount in the monitoring points, and take the maximum point position displacement amount as a displacement amount of the current sub-region; when the displacement amount of the current sub-region exceeds a preset threshold, determine that the current sub-region has the abnormal monitoring point; traverse the plurality of sub-regions to obtain sub-regions in the to-be-inspected region that have abnormal monitoring points, to complete a detection task of the abnormal monitoring points.

7. An electronic device, comprising: The electronic device includes: at least one processor; and a memory connected in communication with the at least one processor; The memory stores a computer program executed by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the snapshot method in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for enabling a processor to execute the snapshot method in any one of claims 1 to 5 when executed.

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