A monitoring network construction information processing method, device, terminal and medium

Abstract

The present application discloses a monitoring network construction information processing method, device, terminal and medium. The solution provided by the present application first obtains video image information and basic device information of camera devices connected to a video platform, and then determines the GIS information and actual coverage range of the camera devices based on the obtained information. Then, based on the target monitoring area where the monitoring network needs to be planned, combined with the GIS information and the actual coverage range, the monitoring network planning auxiliary information is determined according to the maximum coverage site selection problem logic. Based on the obtained monitoring network planning auxiliary information, the monitoring network construction of the target monitoring area is completed, the regional monitoring network construction is realized intelligently, the monitoring video information is used, the dependence on additional non-monitoring structured information is reduced, the dependence on manual data processing is reduced, and the efficiency of monitoring network construction is improved.

Description

Technical Field

[0001] The present application relates to the field of video surveillance technology, and in particular to a monitoring network construction information processing method, device, terminal and medium. Background Art

[0002] Currently, building a video surveillance network often requires extensive manual effort to determine the specific locations where surveillance cameras are deployed. Building and preserving specialized regional surveillance networks for key areas, such as roads, schools, waterways, and forests, requires even more human effort to perform comparison and screening, and then address any blind spots.

[0003] Currently, when building a monitoring network for a certain area, simple GIS information cannot fully reflect the monitoring area information captured by the surveillance cameras. Therefore, it is necessary to rely on other data for support, such as footprint points, electronic activity records, etc. However, this information needs to be manually sorted and counted. Once certain situations occur and the monitoring network needs to be adjusted, it is difficult for the monitoring system to be updated in time, resulting in low construction efficiency. Summary of the Invention

[0004] The present application provides a monitoring network construction information processing method, device, terminal and medium, which are used to solve the technical problem of low efficiency in existing monitoring network construction.

[0005] To solve the above technical problems, the first aspect of the present application provides a monitoring network construction information processing method, comprising:

[0006] Based on a camera device that has been connected to the video platform, obtain video image information and basic device information of the camera device, wherein the basic device information includes: IP address, shooting setting parameters and camera direction;

[0007] Determine the GIS information of the camera device based on the video image information and / or device basic information;

[0008] Calculating the actual coverage of the video image information according to the video image information;

[0009] Obtain the target monitoring area, combine the GIS information and the actual coverage range, and determine the monitoring network planning auxiliary information according to the maximum coverage site selection problem logic.

[0010] Preferably, determining the GIS information of the camera device according to the video image information and / or device basic information includes:

[0011] Obtaining first GIS information through IP address resolution according to the IP address in the basic information of the device;

[0012] According to the video image information, a geographic identifier contained in the video image information is identified by a preset image recognition model, and according to the geographic identifier, a second GIS information corresponding to the geographic identifier is determined by calling a map API interface;

[0013] Based on the distance value between the first GIS information and the second GIS information, if the distance value is lower than a preset distance threshold, the GIS information of the camera device is determined; if the distance value is not lower than the preset distance threshold, the environmental tags contained in the video image information are matched with the environmental information surrounding the first GIS information and the second GIS information respectively, and the GIS information with the highest matching degree is determined as the GIS information of the camera device.

[0014] Preferably, determining the GIS information of the camera device according to the video image information and / or device basic information includes:

[0015] According to the IP address in the basic information of the device, the GIS information of the camera device is obtained through IP address resolution.

[0016] Preferably, determining the GIS information of the camera device according to the video image information and / or device basic information includes:

[0017] According to the video image information, the geographic identifier contained in the video image information is identified through a preset image recognition model, and according to the geographic identifier, the GIS information corresponding to the geographic identifier is determined by calling a map API interface.

[0018] Preferably, calculating the actual coverage of the video image information according to the video image information includes:

[0019] According to the video image information, the video image information is divided into a plurality of image regions by an image segmentation model according to different target objects in the video image information;

[0020] Performing affine transformation processing on the image area, and determining an actual coverage length of the camera device based on, in combination with structural standard parameters of a target object corresponding to the image area;

[0021] According to the actual coverage length, combined with the GIS information and camera orientation of the camera device, the actual coverage range of the video image information is determined.

[0022] Preferably, calculating the actual coverage of the video image information according to the video image information includes:

[0023] Determining a target reference object from the video image information using an image target recognition model according to the video image information;

[0024] Determining the actual coverage length of the camera device according to the height information of the target reference object and the shooting setting parameters of the camera device in accordance with a preset spatial geometry conversion formula;

[0025] According to the actual coverage length, combined with the GIS information and camera orientation of the camera device, the actual coverage range of the video image information is determined.

[0026] Preferably, the spatial geometry conversion formula is specifically:

[0027]

[0028]

[0029] Wherein, L is the actual coverage length, D is the distance from the camera device to the target reference object, h is the height of the target reference object, F is the focal length of the camera, P is the pixel height, and H is the camera height.

[0030] At the same time, the second aspect of the present application provides a monitoring network construction information processing device, including:

[0031] An information acquisition unit is configured to acquire video image information and basic device information of a camera device connected to the video platform, wherein the basic device information includes: an IP address, shooting setting parameters, and camera orientation;

[0032] a GIS information determining unit, configured to determine the GIS information of the camera device based on the video image information and / or basic device information;

[0033] an image coverage range determining unit, configured to calculate an actual coverage range of the video image information based on the video image information;

[0034] The monitoring planning auxiliary information determination unit is used to obtain the target monitoring area, combine the GIS information and the actual coverage range, and determine the monitoring network planning auxiliary information according to the maximum coverage site selection problem logic.

[0035] A third aspect of the present application provides a monitoring network construction information processing terminal, comprising: a memory and a processor;

[0036] The memory is used to store program code, and the program code is used to implement a monitoring network construction information processing method provided in the first aspect of the present application;

[0037] The processor is configured to read and execute the program code.

[0038] The fourth aspect of the present application provides a computer-readable storage medium, in which program code is stored. The program code is used to be read and executed by a processor to implement a monitoring network construction information processing method as provided in the first aspect of the present application.

[0039] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0040] The solution provided in this application first obtains the video image information and basic device information of the camera devices that have been connected to the video platform, and then determines the GIS information and actual coverage range of the camera devices based on the obtained information. Then, based on the target monitoring area where the monitoring network needs to be planned, combined with the GIS information and the actual coverage range, the monitoring network planning auxiliary information is determined according to the maximum coverage site selection problem logic. Based on the obtained monitoring network planning auxiliary information, the monitoring network construction of the target monitoring area is completed, the regional monitoring network construction is realized intelligently, the monitoring video information is used, the dependence on additional non-monitoring structured information is reduced, the dependence on manual data processing is reduced, and the efficiency of monitoring network construction is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0042] Figure 1 A flowchart of an embodiment of a monitoring network construction information processing method provided in this application.

[0043] Figure 2 Schematic diagram of monitoring scene image.

[0044] Figure 3 A schematic diagram of the structure of an embodiment of a monitoring network construction information processing device provided in this application.

[0045] Figure 4 This is a structural diagram of an embodiment of a monitoring network construction information processing terminal provided by this application. DETAILED DESCRIPTION

[0046] The embodiments of the present application provide a monitoring network construction information processing method, device, terminal and medium for solving the technical problem of low efficiency in existing monitoring network construction.

[0047] In order to make the purpose, features, and advantages of the invention of this application more obvious and easy to understand, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the embodiments described below are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0048] First, a detailed description of an embodiment of a monitoring network construction information processing method provided by this application is as follows:

[0049] See also Figure 1 This embodiment provides a monitoring network construction information processing method, including:

[0050] Step 101: Based on the camera device connected to the video platform, obtain video image information and basic device information of the camera device.

[0051] It should be noted that the first step is to connect and aggregate the surveillance cameras through the video platform to obtain the camera's video image information and related basic information. The basic device information includes: IP address, shooting settings parameters, and camera orientation. Shooting settings parameters include but are not limited to: focal length, resolution, etc.

[0052] Step 102: Determine the GIS information of the camera device based on the video image information and / or basic device information.

[0053] Step 103: Calculate the actual coverage of the video image information based on the video image information.

[0054] It should be noted that the video image information and basic device information obtained in step 101 are used to determine the GIS information and actual coverage of each camera device in steps 102 and 103, respectively. It is understood that steps 102 and 103 of this embodiment can be performed sequentially, the order of execution can be reversed, and in some embodiments, they can be performed in parallel.

[0055] More specifically, the following methods are mentioned in step 102 of this embodiment for obtaining the GIS address information of the relevant surveillance camera:

[0056] (1) IP address resolution method: Through the IP address of the video accessed to the platform, the address is geo-resolved to obtain the geographic information of latitude and longitude. IP ; However, this method is limited by the IP address, and the public IP may be the address of the jump server.

[0057] (2) Image recognition method: Use pre-trained image recognition models to identify geographic identifiers contained in video image information. These geographic identifiers can be landmarks or road signs displayed in the image, or manually set geographic location watermarks. Call the relevant map API interface to obtain relevant GIS information. word .

[0058] (3) Hybrid identification method: According to the above methods (1) and (2), two sets of GIS geographic information Loc IP and Loc word Then, the two sets of address information are calibrated and the actual geographical distance between them is calculated. If the distance is small enough, the address information is assumed to be accurate. If the address distance between the two differs greatly, further verification is performed. The video image is input into the image label model (such as CLIP) for preliminary recognition to obtain the environmental tags included in the video image. These tags are used to match the environmental information around the two GIS information to select the GIS information with the highest matching degree as the final GIS information determined by the device. For example, if the image contains water areas, the API interface is called to obtain the Loc IP and Loc word If one camera contains water areas but the other does not, the one containing water areas is selected as the geographic information. If neither camera meets the conditions, the camera is removed from subsequent calculations.

[0059] The actual coverage of the video image information as mentioned in step 103 of this embodiment can be determined by referring to the following implementation methods:

[0060] First, use a pre-trained image recognition model to identify objects in the video image data. Specifically, a segmentation and labeling model (YoloV8+CLIP) is used to extract and output image information, obtaining the image capture labels and the image region location of each label. The following two methods are used to obtain the text information corresponding to each part of the image.

[0061] Among them, Yolo is used to segment and detect the data. Since Yolo is not very good at extracting background information in the image, the obtained text data is put into the fine-tuned CLIP, and the similarity between each part of the image and the corresponding label text is calculated. The label with the highest confidence is obtained as the label of the part.

[0062] You can further combine Yolo and clip structurally, use Yolo to segment and detect images, pass the mask information and segment features obtained by the middle layer of the Yolo model into clip for training, and obtain the label information of clip for each mask part.

[0063] Then, based on the image information obtained by model recognition, calculations can be performed using affine transformation and / or the camera's built-in parameters + reference objects, as follows:

[0064] Assume that Figure 2 Take the following scenario as an example:

[0065] (1) Convert the information on the image, for example: the image with labels and the coordinate positions corresponding to the labels. The area marked as road in the image has coordinate points [(X1, Y1), (X2, Y2), (X3, Y3), ...], and the five groups of coordinate points shown in the figure (sorted clockwise from the far upper corner) are [(X1, Y1), (X2, Y2), (X3, Y3), (X4, Y4), (X5, Y5)]. The lower left corner (X4, Y4) is a prominent corner and is not included in the following calculations.

[0066] Since the road itself is a rectangular area in reality, affine transformation is performed based on the quadrilateral formed by [(X1, Y1), (X2, Y2), (X3, Y3), (X5, Y5)]. The matrix of affine transformation is obtained ,The quadrilateral in the image can be converted into a rectangle through affine transformation.

[0067] (2) Assume that the size of the rectangular road in the image is (l, w), and according to GIS information, the road here is a national highway. According to relevant information, the standard width of a national highway is 3.5 meters, so the width of three lanes is 3.5*3=10.5m. Calculate the actual coverage length L of this camera based on matrix similarity. .

[0068] (3) Based on the camera location calculated in step (2), the camera address is Loc. As well as the current camera orientation (assuming it is northeast), the camera will now cover the road conditions within a range of L meters northeast of Loc on a certain road.

[0069] (4) Repeat steps (1) to (3) to obtain the area covered by all surveillance cameras on the road section. The above content is explained using roads as an example. Other similar areas, such as buildings, can be calculated using similar methods.

[0070] In addition, if there is no direct way to estimate the required area, you can use the built-in parameters of the camera + reference objects to calculate:

[0071] Select the target frame where the person is detected at the farthest end as the reference object. Assume that the height of the reference object is h = 1.7m, the pixel height is P, and the focal length of the camera is F. Calculate the distance from the camera to the target object according to the formula , at this time the camera height is H, and the actual coverage length can be calculated according to the Pythagorean theorem .

[0072] Step 104: Obtain the target monitoring area, combine the GIS information and the actual coverage, and determine the monitoring network planning auxiliary information according to the maximum coverage site selection problem logic.

[0073] Finally, based on the GIS information and actual coverage of each surveillance camera obtained in steps 102 and 103, it is possible to determine whether the target surveillance area has an existing surveillance network and the monitoring status of the existing surveillance network. The Maximum Covering Location Problem (MCLP) is then used to calculate auxiliary information for determining surveillance network planning. When delineating a target surveillance area for a surveillance network to be constructed, the system can automatically calculate the minimum number and location of missing monitoring points in the event of missing monitoring points. This auxiliary surveillance network planning information can also be used to determine whether the angle, direction, or focal length of existing surveillance cameras can be adjusted based on existing surveillance, thereby reducing system construction costs. This solution, which uses only surveillance video information, enables automated adjustment and construction of the delineated area based on the existing surveillance network, reducing reliance on additional non-structured surveillance information and the workload of manual screening and adjustment of surveillance videos.

[0074] The above is a detailed description of an embodiment of a monitoring network construction information processing method provided by the present application. The following is a detailed description of an embodiment of a monitoring network construction information processing device provided by the present application.

[0075] See also Figure 3 This embodiment provides a monitoring network construction information processing device, including:

[0076] The information acquisition unit 201 is used to acquire video image information and basic device information of the camera device based on the camera device that has been connected to the video platform, wherein the basic device information includes: IP address, shooting setting parameters and camera direction;

[0077] GIS information determination unit 202, configured to determine GIS information of the camera device based on the video image information and / or basic device information;

[0078] The image coverage determination unit 203 is configured to calculate the actual coverage of the video image information based on the video image information;

[0079] The monitoring planning auxiliary information determination unit 204 is used to obtain the target monitoring area, combine the GIS information and the actual coverage range, and determine the monitoring network planning auxiliary information according to the maximum coverage site selection problem logic.

[0080] In addition, if Figure 4 As shown, the present application provides an embodiment of a monitoring network construction information processing terminal, wherein the implementation types of the terminal include but are not limited to: personal computers, industrial computers, servers and embedded intelligent devices, and the main components of the terminal include: a memory 33 and a processor 31, and the memory 33 and the processor 31 can be connected via a communication bus 34;

[0081] The memory 33 is used to store program codes, and the program codes are used to implement a monitoring network construction information processing method provided in the above embodiment;

[0082] The processor 31 is used to read and execute program codes.

[0083] The present application also provides a computer-readable storage medium, in which program code is stored. The program code is used to be read and executed by a processor to implement a monitoring network construction information processing method provided in the above embodiment.

[0084] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the terminals, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0085] In the several embodiments provided in this application, it should be understood that the disclosed terminals, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0086] The terms "first," "second," "third," "fourth," and the like (if any) in the specification of the present application and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of the present application described herein, for example, can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising 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 process, method, product, or apparatus.

[0087] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0088] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0089] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0090] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0091] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A monitoring network construction information processing method, characterized in that: include: Based on a camera device that has been connected to the video platform, obtain video image information and basic device information of the camera device, wherein the basic device information includes: IP address, shooting setting parameters and camera direction; Determine the GIS information of the camera device based on the video image information and / or device basic information; Calculating the actual coverage of the video image information according to the video image information; Obtain the target monitoring area, combine the GIS information and the actual coverage range, and determine the monitoring network planning auxiliary information according to the maximum coverage site selection problem logic; The determining of the GIS information of the camera device according to the video image information and / or basic device information includes: Obtaining first GIS information through IP address resolution according to the IP address in the basic information of the device; According to the video image information, a geographic identifier contained in the video image information is identified by a preset image recognition model, and according to the geographic identifier, a second GIS information corresponding to the geographic identifier is determined by calling a map API interface; Based on the distance value between the first GIS information and the second GIS information, if the distance value is lower than a preset distance threshold, the GIS information of the camera device is determined; if the distance value is not lower than the preset distance threshold, the environmental tags contained in the video image information are matched with the environmental information surrounding the first GIS information and the second GIS information respectively, and the GIS information with the highest matching degree is determined as the GIS information of the camera device.

2. A monitoring network construction information processing method according to claim 1, characterized in that: Determining the GIS information of the camera device according to the video image information and / or device basic information includes: According to the IP address in the basic information of the device, the GIS information of the camera device is obtained through IP address resolution.

3. A monitoring network construction information processing method according to claim 1, characterized in that: Determining the GIS information of the camera device according to the video image information and / or device basic information includes: According to the video image information, the geographic identifier contained in the video image information is identified through a preset image recognition model, and according to the geographic identifier, the GIS information corresponding to the geographic identifier is determined by calling a map API interface.

4. A monitoring network construction information processing method according to claim 1, characterized in that: Calculating, based on the video image information, an actual coverage range of the video image information includes: According to the video image information, the video image information is divided into a plurality of image regions by an image segmentation model according to different target objects in the video image information; Performing affine transformation processing on the image area, and determining an actual coverage length of the camera device based on, in combination with structural standard parameters of a target object corresponding to the image area; According to the actual coverage length, combined with the GIS information and camera orientation of the camera device, the actual coverage range of the video image information is determined.

5. A monitoring network construction information processing method according to claim 1, characterized in that: Calculating, based on the video image information, an actual coverage range of the video image information includes: Determining a target reference object from the video image information using an image target recognition model according to the video image information; Determining the actual coverage length of the camera device according to the height information of the target reference object and the shooting setting parameters of the camera device in accordance with a preset spatial geometry conversion formula; According to the actual coverage length, combined with the GIS information and camera orientation of the camera device, the actual coverage range of the video image information is determined.

6. A monitoring network construction information processing method according to claim 5, characterized in that: The spatial geometry conversion formula is specifically: ； ； Wherein, L is the actual coverage length, D is the distance from the camera device to the target reference object, h is the height of the target reference object, F is the focal length of the camera, P is the pixel height, and H is the camera height.

7. A monitoring network construction information processing device, characterized in that: include: An information acquisition unit is configured to acquire video image information and basic device information of a camera device connected to the video platform, wherein the basic device information includes: an IP address, shooting setting parameters, and camera orientation; a GIS information determining unit, configured to determine the GIS information of the camera device based on the video image information and / or basic device information; an image coverage range determining unit, configured to calculate an actual coverage range of the video image information based on the video image information; A monitoring planning auxiliary information determination unit is used to obtain a target monitoring area, combine the GIS information and the actual coverage range, and determine the monitoring network planning auxiliary information according to the maximum coverage site selection problem logic; The GIS information determination unit is specifically used to: Obtaining first GIS information through IP address resolution according to the IP address in the basic information of the device; According to the video image information, a geographic identifier contained in the video image information is identified by a preset image recognition model, and according to the geographic identifier, a second GIS information corresponding to the geographic identifier is determined by calling a map API interface; Based on the distance value between the first GIS information and the second GIS information, if the distance value is lower than a preset distance threshold, the GIS information of the camera device is determined; if the distance value is not lower than the preset distance threshold, the environmental tags contained in the video image information are matched with the environmental information surrounding the first GIS information and the second GIS information respectively, and the GIS information with the highest matching degree is determined as the GIS information of the camera device.

8. A monitoring network construction information processing terminal, characterized in that: include: memory and processor; The memory is used to store program code, and the program code is used to implement a monitoring network construction information processing method according to any one of claims 1 to 6; The processor is configured to read and execute the program code.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores program code, and the program code is used to be read and executed by a processor to implement a monitoring network construction information processing method according to any one of claims 1 to 6.

Images