Tunnel monitoring method, system, computer device and storage medium

Abstract

The application relates to a tunnel monitoring method, a system, computer equipment and a storage medium. The method comprises the following steps: acquiring a vehicle side image cutout result and a vehicle type recognition result of a target vehicle driving into a tunnel; matching a corresponding vehicle white model according to the vehicle type recognition result; superimposing the vehicle side image cutout result on the vehicle white model to obtain a vehicle model of the target vehicle; and outputting the vehicle model to a display terminal, so that the display terminal displays the vehicle model in real time in a pre-established one-side tunnel map according to a real-time position of the target vehicle; wherein the vehicle model and the one-side tunnel map are one-side three-dimensional models which only present a three-dimensional form under a monitoring angle. The method can improve the authenticity of tunnel monitoring.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a tunnel monitoring method, system, computer device, and storage medium. Background Technology

[0002] Tunnels are special structures characterized by their long, narrow spaces, enclosed structures, and poor lighting. The combined effects of lighting conditions, cross-sectional shape, and road surface friction coefficients impair a driver's environmental perception and reaction time, leading to a higher accident rate than on ordinary roads. Accidents in tunnels often cause traffic congestion and structural damage, with serious consequences. Therefore, real-time monitoring of conditions within tunnels is crucial.

[0003] Traditional tunnel monitoring methods typically employ abstract two-dimensional tunnel maps and two-dimensional vehicle images, resulting in rather abstract monitoring images that fail to accurately depict the actual conditions inside the tunnel. Summary of the Invention

[0004] Therefore, it is necessary to provide a tunnel monitoring method, system, device, computer equipment, computer-readable storage medium, and computer program product that can improve the authenticity of monitoring images in order to address the above-mentioned technical problems.

[0005] Firstly, this application provides a tunnel monitoring method. The method includes:

[0006] Obtain the vehicle side image matting results and vehicle type recognition results of the target vehicle entering the tunnel;

[0007] Match the corresponding vehicle white model based on the vehicle model recognition results;

[0008] The vehicle side image cutout result is superimposed on the vehicle white model to obtain the vehicle model of the target vehicle;

[0009] The vehicle model is output to the display terminal so that the display terminal can display the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the target vehicle.

[0010] The vehicle model and the single-sided tunnel map are single-sided three-dimensional models that only present a three-dimensional form from the monitoring angle.

[0011] Secondly, this application provides a tunnel monitoring system. The system includes a first device, a backend server, and a display terminal, wherein:

[0012] The first device is used to determine the vehicle side image matting result and vehicle type recognition result of the target vehicle entering the tunnel;

[0013] The backend server is used to match the corresponding vehicle white model according to the vehicle model recognition result; to overlay the vehicle side image cutout result on the vehicle white model to obtain the vehicle model of the target vehicle; and to output the vehicle model to the display terminal.

[0014] The display terminal is used to display the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the target vehicle.

[0015] The vehicle model and the single-sided tunnel map are single-sided three-dimensional models that only present a three-dimensional form from the monitoring angle.

[0016] In one embodiment, the backend server is further configured to pre-build a one-sided three-dimensional model of the tunnel based on a two-dimensional map of the tunnel and on-site data; and to apply textures to the one-sided three-dimensional model based on images of objects in the tunnel to obtain the pre-built one-sided tunnel map.

[0017] In one embodiment, the backend server is further configured to apply textures to the single-sided 3D model based on images of objects in the tunnel; draw lane lines on the textured single-sided 3D model based on the real-world collected data to obtain the pre-established single-sided tunnel map; and output the vehicle model to a display terminal.

[0018] The display terminal is also used to display the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time position of the target vehicle, so that the vehicle model moves in the single-sided tunnel map according to the lane lines.

[0019] In one embodiment, the first device is further configured to capture a side image of the target vehicle entering the tunnel, perform image matting processing on the side image to obtain a side image matting result, and perform vehicle model recognition on the side image to obtain a vehicle model recognition result.

[0020] The backend server is also used to obtain the vehicle side image matting result and vehicle type recognition result of the target vehicle driving into the tunnel from the first device installed at the entrance of the tunnel.

[0021] In one embodiment, the system further includes a second device, wherein:

[0022] The second device is used to determine the license plate recognition result of the target vehicle entering the tunnel;

[0023] The backend server is also used to determine the real-time location of the vehicle matching the license plate based on the license plate recognition result, and output the vehicle model to the display terminal.

[0024] The display terminal is also used to display the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the matching vehicle.

[0025] In one embodiment, the second device is further used to capture images of the front or rear of a target vehicle entering the tunnel, and to perform license plate recognition based on the front or rear images to obtain a license plate recognition result.

[0026] The backend server is also used to obtain the license plate recognition results of the target vehicles entering the tunnel from the second device installed at the entrance of the tunnel.

[0027] In one embodiment, if no vehicle matching the license plate is determined based on the license plate recognition result, the backend server is further configured to output the vehicle model to the display terminal; the display terminal is further configured to display the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the vehicle whose entry time into the tunnel is closest to that of the target vehicle.

[0028] In one embodiment, if there is an unmatched vehicle in the tunnel whose license plate recognition result is not matched, the background server is further configured to determine the target vehicle model of the vehicle whose entry time in the tunnel is closest to that of the unmatched vehicle, and output the target vehicle model to the display terminal; the display terminal is further configured to display the target vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the unmatched vehicle.

[0029] Thirdly, this application also provides a tunnel monitoring device. The device includes:

[0030] The acquisition module is used to acquire the vehicle side image matting results and vehicle type recognition results of the target vehicle entering the tunnel;

[0031] The white model matching module is used to match the corresponding vehicle white model based on the vehicle model recognition result.

[0032] The vehicle model generation module is used to overlay the vehicle side image cutout result onto the vehicle white model to obtain the vehicle model of the target vehicle;

[0033] The output module is used to output the vehicle model to the display terminal so that the display terminal can display the vehicle model in real time in a pre-established single-sided tunnel map according to the real-time position of the target vehicle.

[0034] The vehicle model and the single-sided tunnel map are single-sided three-dimensional models that only present a three-dimensional form from the monitoring angle.

[0035] In one embodiment, the device further includes:

[0036] The map building module is used to pre-build a one-sided three-dimensional model of the tunnel based on the two-dimensional map of the tunnel and the field data collected; and to apply textures to the one-sided three-dimensional model based on the images of objects in the tunnel to obtain the pre-built one-sided tunnel map.

[0037] In one embodiment, the map building module is further configured to apply textures to the single-sided 3D model based on images of objects in the tunnel; and draw lane lines on the textured single-sided 3D model based on the field-collected data to obtain the pre-built single-sided tunnel map.

[0038] The output module is also used to output the vehicle model to the display terminal, so that the display terminal displays the vehicle model in real time on the pre-established single-sided tunnel map according to the real-time position of the target vehicle, and the vehicle model moves in the single-sided tunnel map according to the lane lines.

[0039] In one embodiment, the acquisition module is further configured to acquire the side image matting result and vehicle type recognition result of the target vehicle driving into the tunnel from a first device installed at the entrance of the tunnel; the first device is configured to capture the side image of the target vehicle driving into the tunnel, perform matting processing on the side image to obtain the side image matting result, and perform vehicle type recognition on the side image to obtain the vehicle type recognition result.

[0040] In one embodiment, the acquisition module is further configured to acquire the license plate recognition result of the target vehicle entering the tunnel;

[0041] The output module is also used to determine the real-time location of the vehicle matching the license plate based on the license plate recognition result; and output the vehicle model to the display terminal so that the display terminal displays the vehicle model in real time on the pre-established single-sided tunnel map according to the real-time location of the matching vehicle.

[0042] In one embodiment, the acquisition module is further configured to acquire the license plate recognition result of the target vehicle driving into the tunnel from a second device installed at the entrance of the tunnel; the second device is configured to capture the front or rear image of the target vehicle driving into the tunnel, and perform license plate recognition based on the front or rear image to obtain the license plate recognition result.

[0043] In one embodiment, the output module is further configured to output the vehicle model to the display terminal if no vehicle matching the license plate is determined based on the license plate recognition result, so that the display terminal can display the vehicle model in a pre-established single-sided tunnel map in real time according to the real-time location of the vehicle whose entry time in the tunnel is closest to that of the target vehicle.

[0044] In one embodiment, the output module is further configured to, if there is an unmatched vehicle in the tunnel with no matching license plate recognition result, determine the target vehicle model of the vehicle whose entry time is closest to that of the unmatched vehicle, and output the target vehicle model to the display terminal, so that the display terminal displays the target vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the unmatched vehicle.

[0045] Fourthly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the tunnel monitoring method described in the embodiments of this application.

[0046] Fifthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, causes the processor to perform the steps of the tunnel monitoring method described in the embodiments of this application.

[0047] Sixthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, causes the processor to perform the steps of the tunnel monitoring method described in the embodiments of this application.

[0048] The aforementioned tunnel monitoring methods, systems, devices, computer equipment, storage media, and computer program products pre-establish a single-sided tunnel map that presents a three-dimensional form only from the monitoring angle. Based on the vehicle type recognition results, a corresponding white model of the vehicle is matched. The vehicle side image cutout result is superimposed on the white model of the vehicle to obtain the vehicle model of the target vehicle. The vehicle model is also a single-sided three-dimensional model. The display terminal displays the vehicle model in real time on the pre-established single-sided tunnel map according to the real-time position of the target vehicle. Since both the single-sided tunnel map and the vehicle model are single-sided three-dimensional models that present a three-dimensional form only from the monitoring angle, they are more realistic than two-dimensional monitoring images, thus improving the realism of the monitoring images for tunnel monitoring. Attached Figure Description

[0049] Figure 1 This is a diagram illustrating the application environment of the tunnel monitoring method in one embodiment;

[0050] Figure 2 This is a diagram illustrating the application environment of the tunnel monitoring method in another embodiment;

[0051] Figure 3 This is a flowchart illustrating a tunnel monitoring method in one embodiment;

[0052] Figure 4This is a schematic diagram of the process for obtaining a vehicle model in one embodiment;

[0053] Figure 5 This is a schematic diagram of an interface displaying a vehicle model in a single-sided tunnel map, as shown in one embodiment.

[0054] Figure 6 This is an architecture diagram of a tunnel monitoring system in one embodiment;

[0055] Figure 7 This is an architecture diagram of the tunnel monitoring system in another embodiment;

[0056] Figure 8 This is a structural block diagram of a tunnel monitoring device in one embodiment;

[0057] Figure 9 This is a structural block diagram of the tunnel monitoring device in another embodiment;

[0058] Figure 10 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0060] In one embodiment, the tunnel monitoring method provided in this application can be applied to, for example... Figure 1In the application environment shown, the first device 102 communicates with the backend server 104 via a network, and the backend server 104 communicates with the display terminal 106 via a network. The first device 102 can determine the vehicle side image matting result and vehicle type recognition result of the target vehicle entering the tunnel. The backend server 104 can obtain the vehicle side image matting result and vehicle type recognition result of the target vehicle entering the tunnel from the first device 102. The backend server 104 can match the corresponding vehicle white model according to the vehicle type recognition result, overlay the vehicle side image matting result on the vehicle white model to obtain the vehicle model of the target vehicle, and output the vehicle model to the display terminal 106. The display terminal 106 can display the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the target vehicle. The first device 102 can be a camera or other device with matting and vehicle type recognition functions. The backend server 104 can be implemented using a separate server or a server cluster composed of multiple servers. Display terminal 106 can be, but is not limited to, various displays, projection devices, personal computers, laptops, smartphones, tablets, and portable wearable devices, such as smartwatches, smart bracelets, and head-mounted devices. The first device 102 can be located at the tunnel entrance. The backend server 104 can be located at a remote location away from the tunnel. Display terminal 106 can be located at the position where the monitoring screen is viewed.

[0061] In another embodiment, such as Figure 2 As shown, in addition to the first device 102, the backend server 104, and the display terminal 106, a second device 108 may also be included. The second device 108 communicates with the backend server 104 via a network. The second device 108 can determine the license plate recognition result of the target vehicle entering the tunnel, and the backend server 104 can obtain the license plate recognition result of the target vehicle entering the tunnel from the second device 108. The backend server 104 can determine the real-time location of the vehicle matching the license plate based on the license plate recognition result and output the vehicle model to the display terminal 106. The display terminal 106 can display the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the matching vehicle. The second device 108 can be a camera or similar device with license plate recognition capabilities. The second device 108 can be located at the tunnel entrance. In one embodiment, the first device 102 and the second device 108 can also be the same device.

[0062] In one embodiment, such as Figure 3 As shown, a tunnel monitoring method is provided, including the following steps:

[0063] Step 302: Obtain the side image matting result and vehicle type recognition result of the target vehicle entering the tunnel.

[0064] The vehicle side image matting result is the matting result obtained by performing matting processing on the vehicle side image; that is, the result of extracting the vehicle from the vehicle side image. A vehicle side image is an image obtained by taking a picture of the side of the vehicle. Taking a picture of the side of the vehicle can be done from above the side of the vehicle. Figure 4 The image shown is a side view of the vehicle. The vehicle model recognition result is the result obtained by identifying the vehicle model of the target vehicle.

[0065] In one embodiment, the vehicle model identification result may include at least the type of the target vehicle. For example, the vehicle model identification result may be a truck, a car, or a bus. In another embodiment, the vehicle model identification result may include not only the type of the target vehicle but also its model. For example, the vehicle model identification result may be a hatchback, two-box, two-and-a-half-box, or three-box vehicle, or it may be a convertible or a fixed vehicle.

[0066] In one embodiment, if the vehicle model identification result indicates an abnormal vehicle, the backend server can output an abnormality warning message to the display terminal, which can then display the warning message. In another embodiment, the display terminal can show the warning message at the location of the abnormal vehicle. In yet another embodiment, the abnormal vehicle can be at least one of the following: a hazardous materials vehicle or a vehicle violating traffic regulations.

[0067] In one embodiment, the first device can capture a side image of the target vehicle and determine the side image matting result and vehicle type recognition result of the target vehicle based on the side image. The backend server can obtain the side image matting result and vehicle type recognition result of the target vehicle entering the tunnel from the first device.

[0068] Step 304: Match the corresponding vehicle white model based on the vehicle model recognition result.

[0069] Among them, the vehicle white model is a pre-built one-sided three-dimensional model that only has vehicle model features and no other features besides vehicle model features, and only presents a three-dimensional form from the monitoring angle.

[0070] In one embodiment, the backend server can match a vehicle white model that matches the vehicle characteristics of the vehicle model recognition result.

[0071] Step 306: Overlay the vehicle side image cutout result onto the vehicle white model to obtain the vehicle model of the target vehicle.

[0072] The vehicle model is a model that is displayed in a single-sided tunnel map, obtained by overlaying the vehicle side image cutout result onto the vehicle white model.

[0073] In one embodiment, the backend server can overlay the vehicle side image cutout result onto the vehicle white model to obtain the vehicle model of the target vehicle.

[0074] In one embodiment, the backend server can first adjust the size of the vehicle side image cutout result, and then overlay the adjusted vehicle side image cutout result onto the vehicle white model to obtain the vehicle model of the target vehicle. The adjusted vehicle side image cutout result matches the size of the vehicle white model.

[0075] like Figure 4 The flowchart for obtaining a vehicle model is shown. First, the first device captures a side image of the target vehicle. The side image is then cut out based on the side image. Finally, the cut-out side image is superimposed on the white vehicle model to obtain the vehicle model.

[0076] Step 308: Output the vehicle model to the display terminal so that the display terminal can display the vehicle model in real time on the pre-established single-sided tunnel map according to the real-time location of the target vehicle.

[0077] The vehicle model and the single-sided tunnel map are single-sided 3D models that only present a 3D appearance from the monitoring angle. The single-sided tunnel map is a single-sided 3D model of the tunnel. The real-time position of the target vehicle refers to the real-time location of the target vehicle within the tunnel.

[0078] In one embodiment, the backend server can output the vehicle model to the display terminal, which can then display the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the target vehicle.

[0079] In one embodiment, the backend server or display terminal can determine the corresponding position in the single-sided tunnel map based on the real-time position of the target vehicle, and the display terminal can display the vehicle model in real time in the pre-established single-sided tunnel map according to the position of the target vehicle in the single-sided tunnel map based on the real-time position of the target vehicle.

[0080] In one embodiment, the real-time location of the target vehicle can be determined based on its real-time positioning information. In another embodiment, the real-time location of the target vehicle can be determined based on the recognition results from cameras inside the tunnel.

[0081] Figure 5 This is a schematic diagram of the interface displaying a vehicle model on a single-sided tunnel map. For example... Figure 5 As shown, both the single-sided tunnel map and the vehicle model are single-sided 3D models that only present a 3D shape from the monitoring angle; that is, in... Figure 5 The image presented in the video is in three dimensions from different angles.

[0082] In one embodiment, such as Figure 5As shown, the display terminal can also display the license plate recognition result (i.e., license plate information) of each vehicle at the location of the vehicle model. It is understandable that this is done to protect privacy. Figure 5 The license plate information in the image has been obscured, only indicating that the license plate information can be displayed; the specific content of the license plate information is not important.

[0083] In one embodiment, the first device can also identify at least one of pedestrians and non-motorized vehicles in the tunnel. The backend server can match the corresponding one-sided 3D model based on the identification result of at least one of pedestrians and non-motorized vehicles and output it to the display terminal. The display terminal can display the one-sided 3D model corresponding to at least one of pedestrians and non-motorized vehicles in the one-sided tunnel map in real time.

[0084] The aforementioned tunnel monitoring method pre-establishes a single-sided tunnel map that presents a 3D form only from the monitoring angle. Based on vehicle type recognition results, a corresponding white model of the vehicle is matched. The vehicle side image cutout result is superimposed on the vehicle white model to obtain the target vehicle model. This vehicle model is also a single-sided 3D model. The display terminal shows the vehicle model in real-time on the pre-established single-sided tunnel map according to the target vehicle's real-time position. Because both the single-sided tunnel map and the vehicle model are single-sided 3D models that present a 3D form only from the monitoring angle, they are more realistic than 2D monitoring images, improving the realism of the monitoring footage for tunnel monitoring and enabling real-time tracking of vehicle trajectories. Furthermore, the single-sided 3D model reduces resource consumption and manpower compared to a pure 3D model, thus lowering costs. The vehicle model obtained by superimposing the vehicle side image cutout result on the vehicle white model can intuitively display the vehicle's model characteristics, avoiding uniformity in vehicle models and facilitating the differentiation, identification, and tracking of vehicles in the tunnel.

[0085] In one embodiment, the method further includes: pre-establishing a one-sided three-dimensional model of the tunnel based on a two-dimensional map of the tunnel and field-collected data; and applying textures to the one-sided three-dimensional model based on images of objects in the tunnel to obtain a pre-established one-sided tunnel map.

[0086] In one embodiment, the two-dimensional map of the tunnel can be a high-precision planar map of the tunnel.

[0087] In one embodiment, the field data can be obtained by photographing, measuring, and sketching the tunnel.

[0088] In one embodiment, modelers can use a 2D map of the tunnel as a base map, combined with on-site data, to create a 3D model of one side of the tunnel. They can then apply textures to the 3D model based on images of objects in the tunnel. The backend server can generate a pre-built 3D map of the tunnel and output it to the display terminal.

[0089] In one embodiment, objects in the tunnel may include at least one of the following: walls, sidewalks, driveways, emergency lanes, emergency escape routes, and signs.

[0090] In one embodiment, the single-sided tunnel map can also be rendered with light, and the rendered single-sided tunnel map can be used as a pre-established single-sided tunnel map. In this embodiment, a single-sided tunnel map that more closely resembles the effect of realistic lighting can be obtained.

[0091] In one embodiment, after obtaining a one-sided tunnel map, the one-sided tunnel map can be overlaid with a satellite map to determine the correspondence between the coordinates in the one-sided tunnel map and the satellite positioning coordinates. The display terminal can then display the target vehicle in the one-sided tunnel map based on the target vehicle's satellite positioning coordinates.

[0092] In the above embodiments, a one-sided three-dimensional model of the tunnel is pre-established based on the two-dimensional map of the tunnel and the data collected on site. The one-sided three-dimensional model is then textured with images of objects in the tunnel to obtain a pre-established one-sided tunnel map. This results in a one-sided tunnel map that is closer to the actual situation in the tunnel, and can show the location of the tunnel's internal structure and facilities, thus improving the realism of the tunnel monitoring footage.

[0093] In one embodiment, applying textures to a single-sided 3D model based on images of objects in the tunnel to obtain a pre-established single-sided tunnel map includes: applying textures to the single-sided 3D model based on images of objects in the tunnel; and drawing lane lines on the textured single-sided 3D model based on field-collected data to obtain the pre-established single-sided tunnel map. Outputting the vehicle model to a display terminal so that the display terminal displays the vehicle model in real-time on the pre-established single-sided tunnel map according to the real-time position of the target vehicle includes: outputting the vehicle model to the display terminal so that the display terminal displays the vehicle model in real-time on the pre-established single-sided tunnel map according to the real-time position of the target vehicle, and moving the vehicle model within the single-sided tunnel map according to the lane lines.

[0094] Lane lines are lines on the road within a tunnel used to constrain vehicle movement. In one embodiment, lane lines may include lane lines for motor vehicles and lane lines for non-motor vehicles.

[0095] In one embodiment, modelers can use their terminals to draw lane lines on a textured, single-sided 3D model based on field-collected data, and the backend server can generate a pre-built single-sided tunnel map. In another embodiment, modelers can use their terminals to draw lane lines on a textured, single-sided 3D model based on tunnel alignment information from field-collected data, and the backend server can generate a pre-built single-sided tunnel map.

[0096] In one embodiment, the display terminal can display the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the target vehicle, so that the vehicle model moves in the single-sided tunnel map according to the direction constrained by the lane lines.

[0097] In one embodiment, the modeler can check the lane lines based on the movement of the vehicle model displayed on the terminal. If the check is correct, a single-sided tunnel map is obtained. If there are problems, the lane lines are adjusted.

[0098] In the above embodiments, lane lines are drawn in the single-sided tunnel map, and the vehicle model moves in the single-sided tunnel map according to the lane lines, making the content displayed on the tunnel monitoring screen more realistic.

[0099] In one embodiment, obtaining the side image matting result and vehicle type recognition result of the target vehicle entering the tunnel includes: obtaining the side image matting result and vehicle type recognition result of the target vehicle entering the tunnel from a first device installed at the entrance of the tunnel; the first device is used to capture the side image of the target vehicle entering the tunnel, perform matting processing on the side image to obtain the side image matting result, and perform vehicle type recognition on the side image to obtain the vehicle type recognition result.

[0100] The first device is installed at the entrance of the tunnel to capture images of the vehicle side and determine the results of the vehicle side image matting and vehicle type recognition.

[0101] In one embodiment, the first device may be mounted on a gantry at the tunnel entrance.

[0102] In one embodiment, the first device can capture a side image of the target vehicle entering the tunnel, perform image matting processing on the side image to obtain a side image matting result, and perform vehicle model recognition on the side image to obtain a vehicle model recognition result. The backend server can obtain the side image matting result and vehicle model recognition result of the target vehicle entering the tunnel from the first device.

[0103] In other embodiments, the first device can capture a side image of the target vehicle entering the tunnel and send the side image to a backend server. The backend server can perform image matting processing on the side image to obtain the side image matting result, and perform vehicle model recognition on the side image to obtain the vehicle model recognition result.

[0104] In the above embodiments, the first device can capture a side image of the target vehicle entering the tunnel, perform image matting processing on the side image to obtain the side image matting result, and perform vehicle model recognition on the side image to obtain the vehicle model recognition result. The backend server can obtain the side image matting result and vehicle model recognition result of the target vehicle entering the tunnel from the first device, and can flexibly use remote and near devices to process together, so as to achieve tunnel monitoring efficiently and accurately.

[0105] In one embodiment, the method further includes: acquiring the license plate recognition result of the target vehicle entering the tunnel. Outputting the vehicle model to a display terminal so that the display terminal displays the vehicle model in real-time on a pre-established single-sided tunnel map according to the real-time location of the target vehicle includes: determining the real-time location of the vehicle matching the license plate based on the license plate recognition result; and outputting the vehicle model to the display terminal so that the display terminal displays the vehicle model in real-time on a pre-established single-sided tunnel map according to the real-time location of the matching vehicle.

[0106] The license plate recognition result is the result obtained by recognizing the license plate of the target vehicle.

[0107] In one embodiment, the second device can capture images of the front or rear of the target vehicle, and determine the license plate recognition result of the target vehicle entering the tunnel based on the front or rear images. The backend server can obtain the license plate recognition result from the second device.

[0108] In one embodiment, the backend server can determine the real-time location of the vehicle whose license plate matches the license plate based on the real-time location information of each vehicle in the tunnel. The display terminal can then display the vehicle model in real-time on a pre-built single-sided tunnel map according to the real-time location of the matching vehicle.

[0109] In the above embodiments, the real-time location of the vehicle matching the license plate is determined based on the license plate recognition result, and the vehicle model is displayed in real time on the pre-established single-sided tunnel map according to the real-time location of the matching vehicle. This can realistically display the real-time situation inside the tunnel in the monitoring screen and reflect the position of the vehicle in the tunnel in real time, thereby improving the realism and real-time performance of tunnel monitoring.

[0110] In one embodiment, obtaining the license plate recognition result of a target vehicle entering a tunnel includes: obtaining the license plate recognition result of the target vehicle entering the tunnel from a second device installed at the entrance of the tunnel; the second device is used to capture a front or rear image of the target vehicle entering the tunnel, and perform license plate recognition based on the front or rear image to obtain the license plate recognition result.

[0111] The second device is installed at the tunnel entrance to capture images of the front or rear of a vehicle and to determine the license plate recognition result. The front image is an image obtained by photographing the front of the target vehicle. The rear image is an image obtained by photographing the rear of the target vehicle. The image content of both the front and rear images of the target vehicle includes the license plate of the target vehicle.

[0112] In one embodiment, the second device may be installed on a gantry at the entrance of the tunnel.

[0113] In one embodiment, the second device can capture images of the front or rear of the target vehicle entering the tunnel, and perform license plate recognition based on these images to obtain the license plate recognition result. The backend server can then obtain the license plate recognition result of the target vehicle from the second device.

[0114] In another embodiment, the second device can capture images of the front and rear of the target vehicle, and perform license plate recognition based on the front and rear images respectively to obtain a first license plate recognition result and a second license plate recognition result. The backend server can obtain the first and second license plate recognition results from the second device. The backend server can compare the first and second license plate recognition results. If they match, the matching result is taken as the license plate recognition result of the target vehicle. If they do not match, the backend server can output a license plate cloning warning to the display terminal, which can then display the warning. In one embodiment, the display terminal can display the license plate cloning warning at the location corresponding to the vehicle model of the target vehicle on a single-sided tunnel map. The license plate cloning warning is used to alert the target vehicle to the presence of a cloned license plate.

[0115] In one embodiment, there is one second device, which can capture images of the front and rear of the target vehicle. In another embodiment, there are two second devices, which can capture images of the front and rear of the target vehicle respectively, and perform license plate recognition based on the front and rear images to obtain a first license plate recognition result and a second license plate recognition result.

[0116] In the above embodiments, the second device can capture images of the front or rear of the target vehicle entering the tunnel, and perform license plate recognition based on the images to obtain the license plate recognition result. The backend server can obtain the license plate recognition result of the target vehicle from the second device, enabling flexible use of remote and near-end devices for collaborative processing, achieving efficient and accurate tunnel monitoring.

[0117] In one embodiment, outputting a vehicle model to a display terminal so that the display terminal displays the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the matching vehicle includes at least one of the following: if no vehicle matching the license plate is determined based on the license plate recognition result, the vehicle model is output to the display terminal so that the display terminal displays the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the vehicle whose entry time is closest to that of the target vehicle; if there is an unmatched vehicle in the tunnel for which no license plate recognition result is found, the target vehicle model of the vehicle whose entry time is closest to that of the unmatched vehicle is determined, and the target vehicle model is output to the display terminal so that the display terminal displays the target vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the unmatched vehicle.

[0118] Unmatched vehicles refer to vehicles in the tunnel for which no license plate recognition result was found. The target vehicle model is the vehicle model of the vehicle whose entry time in the tunnel is closest to that of the unmatched vehicle.

[0119] In one embodiment, if a vehicle matching the license plate is not identified based on the license plate recognition result, the backend server can output the vehicle model to the display terminal. The display terminal can then display the vehicle model in real time on a pre-established single-sided tunnel map based on the real-time location of the vehicle whose entry time into the tunnel is closest to that of the target vehicle.

[0120] In one embodiment, if a matching vehicle cannot be identified from the vehicles in the tunnel based on the license plate recognition results, the display terminal can display the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the vehicle in the tunnel whose entry time is closest to that of the target vehicle.

[0121] In one embodiment, if there is an unmatched vehicle in the tunnel whose license plate recognition result is not matched, the backend server can determine the target vehicle model of the vehicle whose entry time is closest to that of the unmatched vehicle and output the target vehicle model to the display terminal. The display terminal can display the target vehicle model in real time on the pre-established single-sided tunnel map according to the real-time location of the unmatched vehicle.

[0122] In one embodiment, if there are unmatched vehicles among the vehicles in the tunnel whose license plate recognition results are not matched, the backend server can determine the target vehicle model of the vehicle whose entry time in the tunnel is closest to that of the unmatched vehicle from the vehicle models of each vehicle, and output the target vehicle model to the display terminal. The display terminal can display the target vehicle model in real time on the pre-established single-sided tunnel map according to the real-time location of the unmatched vehicle.

[0123] In the above embodiments, the two abnormal situations—vehicles whose license plates are not matched based on the license plate recognition results and unmatched vehicles in the tunnel whose license plates are not matched—can also be addressed accordingly, ensuring the normal execution of tunnel monitoring and improving the authenticity and completeness of the monitoring images.

[0124] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0125] Based on the same inventive concept, this application also provides a tunnel monitoring system for implementing the tunnel monitoring method described above. The solution provided by this system is similar to the implementation scheme described in the above method; therefore, the specific limitations in one or more tunnel monitoring system embodiments provided below can be found in the limitations of the tunnel monitoring method described above, and will not be repeated here.

[0126] In one embodiment, such as Figure 6 As shown, a tunnel monitoring system 600 is provided, including a first device 602, a backend server 604, and a display terminal 606, wherein:

[0127] The first device 602 is used to determine the vehicle side image matting result and vehicle type recognition result of the target vehicle entering the tunnel.

[0128] The backend server 604 is used to match the corresponding vehicle white model based on the vehicle model recognition result; to overlay the vehicle side image cutout result onto the vehicle white model to obtain the vehicle model of the target vehicle; and to output the vehicle model to the display terminal.

[0129] Display terminal 606 is used to display the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the target vehicle.

[0130] Among them, the vehicle model and the single-sided tunnel map are single-sided 3D models that only present a 3D shape from the monitoring angle.

[0131] In one embodiment, the backend server 604 is also used to pre-build a one-sided three-dimensional model of the tunnel based on the two-dimensional map of the tunnel and the data collected on site; and to apply textures to the one-sided three-dimensional model based on the images of objects in the tunnel to obtain a pre-built one-sided tunnel map.

[0132] In one embodiment, the backend server 604 is further configured to apply textures to a single-sided 3D model based on images of objects in the tunnel; draw lane lines on the textured single-sided 3D model based on real-world data, thereby obtaining a pre-established single-sided tunnel map, and output the vehicle model to the display terminal 606. The display terminal 606 is further configured to display the vehicle model in real-time on the pre-established single-sided tunnel map according to the real-time position of the target vehicle, allowing the vehicle model to move within the single-sided tunnel map along the lane lines.

[0133] In one embodiment, the first device 602 is further configured to capture a side image of the target vehicle entering the tunnel, perform image matting processing on the side image to obtain a side image matting result, and perform vehicle model recognition on the side image to obtain a vehicle model recognition result. The backend server 604 is further configured to obtain the side image matting result and vehicle model recognition result of the target vehicle entering the tunnel from the first device installed at the tunnel entrance.

[0134] In one embodiment, such as Figure 7 As shown, system 600 also includes a second device 608, wherein the second device 608 is used to determine the license plate recognition result of the target vehicle entering the tunnel. The backend server 604 is also used to determine the real-time location of the vehicle matching the license plate based on the license plate recognition result, and output the vehicle model to the display terminal. The display terminal 606 is also used to display the vehicle model in real-time on a pre-established single-sided tunnel map according to the real-time location of the matching vehicle.

[0135] In one embodiment, the second device 608 is further configured to capture images of the front or rear of the target vehicle entering the tunnel, and perform license plate recognition based on the front or rear images to obtain a license plate recognition result. The backend server 604 is further configured to obtain the license plate recognition result of the target vehicle entering the tunnel from the second device installed at the tunnel entrance.

[0136] In one embodiment, if no vehicle matching the license plate is determined based on the license plate recognition result, the backend server 604 is further configured to output the vehicle model to the display terminal. The display terminal 606 is further configured to display the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the vehicle whose entry time into the tunnel is closest to that of the target vehicle.

[0137] In one embodiment, if there are unmatched vehicles in the tunnel whose license plate recognition results are not matched, the backend server 604 is further configured to determine the target vehicle model of the vehicle whose entry time in the tunnel is closest to that of the unmatched vehicle, and output the target vehicle model to the display terminal. The display terminal 606 is further configured to display the target vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the unmatched vehicle.

[0138] The aforementioned tunnel monitoring system pre-creates a single-sided tunnel map that presents a 3D form only from the monitoring angle. Based on vehicle type recognition results, a corresponding white model of the vehicle is matched. The vehicle side image cutout result is then overlaid onto the white model to obtain the target vehicle model. This vehicle model is also a single-sided 3D model. The display terminal shows the vehicle model in real-time on the pre-created single-sided tunnel map according to the target vehicle's real-time position. Because both the single-sided tunnel map and the vehicle model are single-sided 3D models that only present a 3D form from the monitoring angle, they are more realistic than 2D monitoring images, improving the realism of the monitoring footage for tunnels. Furthermore, the single-sided 3D model reduces resource consumption and saves manpower compared to a pure 3D model. The vehicle model obtained by overlaying the vehicle side image cutout result onto the white model can intuitively display the vehicle's model characteristics, avoiding uniformity in vehicle models and facilitating the differentiation, identification, and tracking of vehicles in the tunnel.

[0139] Based on the same inventive concept, this application also provides a tunnel monitoring device for implementing the tunnel monitoring method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more tunnel monitoring device embodiments provided below can be found in the limitations of the tunnel monitoring method described above, and will not be repeated here.

[0140] In one embodiment, such as Figure 8 As shown, a tunnel monitoring device 800 is provided, including: an acquisition module 802, a white model matching module 804, a vehicle model generation module 806, and an output module 808, wherein:

[0141] The acquisition module 802 is used to acquire the vehicle side image matting result and vehicle type recognition result of the target vehicle driving into the tunnel.

[0142] The white model matching module 804 is used to match the corresponding vehicle white model based on the vehicle model recognition result.

[0143] The vehicle model generation module 806 is used to overlay the vehicle side image cutout result onto the vehicle white model to obtain the vehicle model of the target vehicle.

[0144] The output module 808 is used to output the vehicle model to the display terminal so that the display terminal can display the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the target vehicle.

[0145] Among them, the vehicle model and the single-sided tunnel map are single-sided 3D models that only present a 3D shape from the monitoring angle.

[0146] In one embodiment, such as Figure 9 As shown, the device 800 also includes:

[0147] The map creation module 810 is used to pre-create a single-sided three-dimensional model of the tunnel based on the two-dimensional map of the tunnel and the data collected on site; and to apply textures to the single-sided three-dimensional model based on the images of objects in the tunnel to obtain a pre-created single-sided tunnel map.

[0148] In one embodiment, the map creation module 810 is further configured to apply textures to a single-sided 3D model based on images of objects in the tunnel; and to draw lane lines on the textured single-sided 3D model based on real-world data, thereby obtaining a pre-built single-sided tunnel map. The output module 808 is further configured to output the vehicle model to a display terminal, so that the display terminal displays the vehicle model in real-time on the pre-built single-sided tunnel map according to the real-time position of the target vehicle, allowing the vehicle model to move within the single-sided tunnel map according to the lane lines.

[0149] In one embodiment, the acquisition module 802 is further configured to acquire the vehicle side image matting result and vehicle type recognition result of the target vehicle driving into the tunnel from the first device installed at the entrance of the tunnel; the first device is configured to capture the vehicle side image of the target vehicle driving into the tunnel, perform matting processing on the vehicle side image to obtain the vehicle side image matting result, and perform vehicle type recognition on the vehicle side image to obtain the vehicle type recognition result.

[0150] In one embodiment, the acquisition module 802 is further configured to acquire the license plate recognition result of the target vehicle entering the tunnel. The output module 808 is further configured to determine the real-time location of the vehicle matching the license plate based on the license plate recognition result; and output the vehicle model to the display terminal so that the display terminal displays the vehicle model in real time on the pre-established single-sided tunnel map according to the real-time location of the matching vehicle.

[0151] In one embodiment, the acquisition module 802 is further configured to acquire the license plate recognition result of the target vehicle driving into the tunnel from the second device installed at the entrance of the tunnel; the second device is configured to capture the front or rear image of the target vehicle driving into the tunnel, and perform license plate recognition based on the front or rear image to obtain the license plate recognition result.

[0152] In one embodiment, the output module 808 is further configured to output the vehicle model to the display terminal if no vehicle matching the license plate is determined based on the license plate recognition result, so that the display terminal can display the vehicle model in real time on the pre-established single-sided tunnel map according to the real-time location of the vehicle whose entry time into the tunnel is closest to that of the target vehicle.

[0153] In one embodiment, the output module 808 is further configured to, if there is an unmatched vehicle in the tunnel that has not been matched with a license plate recognition result, determine the target vehicle model of the vehicle whose entry time is closest to that of the unmatched vehicle, and output the target vehicle model to the display terminal, so that the display terminal displays the target vehicle model in real time on the pre-established single-sided tunnel map according to the real-time location of the unmatched vehicle.

[0154] The aforementioned tunnel monitoring device pre-creates a single-sided tunnel map that presents a 3D form only from the monitoring angle. Based on vehicle type recognition results, it matches a corresponding white model of the vehicle. The vehicle side image cutout result is then superimposed onto the white model to obtain the target vehicle model. This vehicle model is also a single-sided 3D model. The display terminal shows the vehicle model in real-time on the pre-created single-sided tunnel map according to the target vehicle's real-time position. Because both the single-sided tunnel map and the vehicle model are single-sided 3D models that only present a 3D form from the monitoring angle, they are more realistic than 2D monitoring images, improving the realism of the monitoring footage for tunnel monitoring. Furthermore, the single-sided 3D model reduces resource consumption and saves manpower compared to a pure 3D model. The vehicle model obtained by superimposing the vehicle side image cutout result onto the white model can intuitively display the vehicle's model characteristics, avoiding uniformity in vehicle models and facilitating the differentiation, identification, and tracking of vehicles in the tunnel.

[0155] Each module in the aforementioned tunnel monitoring device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0156] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 10As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores data. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a tunnel monitoring method.

[0157] Those skilled in the art will understand that Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0158] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0159] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0160] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0161] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0162] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0163] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0164] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A tunnel monitoring method, characterized in that, The method includes: Obtain the side image matting result and vehicle model recognition result of the target vehicle entering the tunnel; the vehicle model recognition result includes at least the type and style of the target vehicle, and the style of the target vehicle includes a single car, a two-box car, a two-and-a-half-box car or a three-box car, or includes a convertible or a non-convertible car. Obtain a vehicle white model that matches the vehicle features of the vehicle identification result; the vehicle white model is a pre-built one-sided three-dimensional model that only has vehicle features and no other features besides vehicle features, and only presents a three-dimensional shape from the monitoring angle; The size of the vehicle side image cutout result is adjusted, and the resized vehicle side image cutout result is superimposed on the vehicle white model to obtain the vehicle model of the target vehicle; the vehicle model is the model obtained for display in the single-sided tunnel map; the single-sided tunnel map is a single-sided 3D model of the tunnel, and the single-sided tunnel map is constructed based on the 2D map of the tunnel and is a single-sided tunnel map after lighting rendering, so that the single-sided tunnel map after lighting rendering is closer to the real lighting effect; wherein, the 2D map of the tunnel is a high-precision planar map of the tunnel; The vehicle model is output to a display terminal so that the display terminal can display the vehicle model in real time on a pre-established one-sided tunnel map according to the real-time position of the target vehicle. This includes: if no vehicle matching the license plate is determined based on the license plate recognition result of the target vehicle entering the tunnel, the vehicle model is output to the display terminal so that the display terminal can display the vehicle model in real time on the pre-established one-sided tunnel map according to the real-time position of the vehicle whose entry time is closest to that of the target vehicle. The vehicle model and the one-sided tunnel map are one-sided 3D models that only present a 3D form from the monitoring angle. The display terminal displays the vehicle model of the target vehicle in the one-sided tunnel map based on the correspondence between the satellite positioning coordinates of the target vehicle, the coordinates in the one-sided tunnel map, and the satellite positioning coordinates. This allows the vehicle model to move in the one-sided tunnel map according to the direction constrained by the lane lines, making the content displayed on the tunnel monitoring screen more realistic. The correspondence between the coordinates in the one-sided tunnel map and the satellite positioning coordinates is determined by overlaying the one-sided tunnel map and the satellite map.

2. The method according to claim 1, characterized in that, The method further includes: A one-sided three-dimensional model of the tunnel is pre-built based on a two-dimensional map of the tunnel and on-site data. The single-sided 3D model is textured using images of objects in the tunnel to obtain the pre-built single-sided tunnel map.

3. The method according to claim 2, characterized in that, The step of applying textures to the single-sided 3D model based on images of objects in the tunnel to obtain the pre-built single-sided tunnel map includes: Texture mapping is performed on the single-sided 3D model based on images of objects in the tunnel; Based on the data collected on-site, lane lines are drawn on the textured single-sided 3D model to obtain the pre-established single-sided tunnel map; The step of outputting the vehicle model to a display terminal, so that the display terminal can display the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the target vehicle, includes: The vehicle model is output to the display terminal so that the display terminal displays the vehicle model in real time on the pre-established single-sided tunnel map according to the real-time position of the target vehicle, and the vehicle model moves in the single-sided tunnel map according to the lane lines.

4. The method according to claim 1, characterized in that, The results of obtaining the side image matting and vehicle type recognition of the target vehicle entering the tunnel include: The first device installed at the entrance of the tunnel acquires the side image matting result and vehicle type recognition result of the target vehicle driving into the tunnel; the first device is used to capture the side image of the target vehicle driving into the tunnel, perform matting processing on the side image to obtain the side image matting result, and perform vehicle type recognition on the side image to obtain the vehicle type recognition result.

5. The method according to any one of claims 1 to 4, characterized in that, The method further includes: Obtain the license plate recognition results of the target vehicle entering the tunnel; The step of outputting the vehicle model to a display terminal, so that the display terminal can display the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the target vehicle, includes: The real-time location of the vehicle matching the license plate is determined based on the license plate recognition results; The vehicle model is output to a display terminal so that the display terminal displays the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the matching vehicle.

6. The method according to claim 5, characterized in that, The license plate recognition results of the target vehicle entering the tunnel include: The license plate recognition result of the target vehicle entering the tunnel is obtained from a second device installed at the entrance of the tunnel; the second device is used to capture the front or rear image of the target vehicle entering the tunnel, and to perform license plate recognition based on the front or rear image to obtain the license plate recognition result.

7. The method according to claim 5, characterized in that, The step of outputting the vehicle model to a display terminal, so that the display terminal displays the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time position of the matching vehicle, includes: If there is an unmatched vehicle in the tunnel whose license plate recognition result is not matched, then the target vehicle model of the vehicle whose entry time is closest to that of the unmatched vehicle is determined, and the target vehicle model is output to the display terminal so that the display terminal displays the target vehicle model in real time on the pre-established single-sided tunnel map according to the real-time location of the unmatched vehicle.

8. A tunnel monitoring system, characterized in that, The system includes a first device, a backend server, and a display terminal, wherein: The first device is used to determine the side image matting result and vehicle model recognition result of the target vehicle entering the tunnel; the vehicle model recognition result includes at least the type and style of the target vehicle, and the style of the target vehicle includes a single-box car, a two-box car, a two-and-a-half-box car or a three-box car, or includes a convertible car or a non-convertible car. The backend server is used to acquire a vehicle white model that matches the vehicle model features of the vehicle model recognition result. The vehicle white model is a pre-built one-sided 3D model that only has vehicle model features and no other features, and only presents a 3D shape from the monitoring angle. The size of the vehicle side image cutout result is adjusted, and the adjusted vehicle side image cutout result is superimposed on the vehicle white model to obtain the vehicle model of the target vehicle. The vehicle model is the model obtained for display in the one-sided tunnel map. The one-sided tunnel map is a one-sided 3D model of the tunnel. The one-sided tunnel map is a one-sided tunnel map constructed based on the two-dimensional map of the tunnel and a light-rendered one-sided tunnel map to make the light-rendered one-sided tunnel map closer to the real light effect. The two-dimensional map of the tunnel is a high-precision planar map of the tunnel. The vehicle model is output to the display terminal. The display terminal is used to display the vehicle model in real time on a pre-established single-sided tunnel map according to the real-time location of the target vehicle, including: if no vehicle matching the license plate is determined according to the license plate recognition result of the target vehicle entering the tunnel, the vehicle model is output to the display terminal so that the display terminal displays the vehicle model in real time on the pre-established single-sided tunnel map according to the real-time location of the vehicle closest to the time of the target vehicle entering the tunnel. The vehicle model and the single-sided tunnel map are single-sided 3D models that only present a 3D form from the monitoring angle. The display terminal displays the vehicle model of the target vehicle in the single-sided tunnel map based on the correspondence between the satellite positioning coordinates of the target vehicle, the coordinates in the single-sided tunnel map, and the satellite positioning coordinates. This allows the vehicle model to move in the single-sided tunnel map according to the direction constrained by the lane lines, making the content displayed on the tunnel monitoring screen more realistic. The correspondence between the coordinates in the single-sided tunnel map and the satellite positioning coordinates is determined by overlaying the single-sided tunnel map and the satellite map.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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