Method and device for adjusting camera in parking system

Abstract

An embodiment of the present application provides a method and apparatus for adjusting a camera in a parking system, the method comprising: obtaining a first vehicle image captured by a camera, the first vehicle image comprising images of multiple vehicles in a target parking area; obtaining a recognition image after identifying the multiple vehicles based on the first vehicle image and a vehicle area recognition model, the recognition image identifying the recognition area of each of the multiple vehicles, and the recognition image comprising an identifier of the recognition area of each vehicle, the identifier being used to indicate the degree of overlap between the recognition areas of the multiple vehicles; and sending the recognition image, wherein the degree of overlap between the recognition areas of the multiple vehicles is used to adjust the parameters of the camera. The method and apparatus for adjusting a camera in a parking system according to an embodiment of the present application can accurately and effectively install cameras in a parking system.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence, and more specifically, to a method and apparatus for adjusting a camera in a parking system. Background Art

[0002] With the increasing number of cars, the demand for urban parking spaces is also growing. However, the pace of parking lot construction lags far behind the growth of the car population, resulting in a severe shortage of parking spaces. To compensate for this shortage, many cities have set up parking spaces along low-traffic feeder roads. These parking spaces are typically charged manually through timed billing. This method is not only labor-intensive, but also, due to the long length of temporary roadside parking, toll collectors cannot manage all parking spaces, resulting in the problem of delayed parking fee collection.

[0003] Some new roadside parking lots currently use electronic devices to monitor parking behavior, such as cameras, to manage vehicle parking. In this solution, camera placement is crucial. If the camera is not installed accurately, some vehicles in the parking space may not be recognized, resulting in inaccurate charging for these vehicles.

[0004] Therefore, how to accurately and effectively install cameras in parking systems has become an urgent problem to be solved. Summary of the Invention

[0005] The present application provides a method and device for adjusting a camera in a parking system, which can accurately and effectively install the camera in the parking system.

[0006] In a first aspect, a method for adjusting a camera in a parking system is provided, the method comprising: obtaining a first vehicle image captured by a camera, the first vehicle image comprising images of a plurality of vehicles in a target parking area; obtaining an identification image after identifying the plurality of vehicles based on the first vehicle image and a vehicle area recognition model, the identification image identifying an identification area of each of the plurality of vehicles, and the identification image comprising an identifier of the identification area of each vehicle, the identifier being used to indicate a degree of overlap between the identification areas of the plurality of vehicles; and sending the identification image, wherein the degree of overlap between the identification areas of the plurality of vehicles is used to adjust parameters of the camera.

[0007] In an embodiment of the present application, a recognition image is generated based on a vehicle image captured using the camera's initial parameters and a vehicle area recognition model, identifying each vehicle's recognition area. This recognition image includes an identifier indicating the degree of overlap between the vehicle's recognition areas, and the recognition image is then transmitted. Thus, upon receiving the recognition image, hardware engineers can adjust the camera parameters in real time and purposefully based on the degree of overlap between each vehicle's recognition areas. This not only significantly reduces the time required to adjust the camera, but also allows for accurate and efficient camera installation, thereby improving the accuracy of identifying vehicle information.

[0008] Furthermore, since the recognition area of a vehicle is much simpler than the recognition of specific license plate information, in an embodiment of the present application, the camera is adjusted using the overlap of the vehicle's recognition area, which does not require complex calculations, thereby increasing processing speed and being applicable to more parking systems.

[0009] In some possible implementations, the identification includes first indication information and / or second indication information, wherein the first indication information is used to indicate an identification area where the overlap between the identification areas of the multiple vehicles is higher than or equal to a threshold, and the second indication information is used to indicate an identification area where the overlap between the identification areas of the multiple vehicles is lower than the threshold.

[0010] The above technical solution sets different identifications for recognition areas with an overlap higher than or equal to a threshold and for recognition areas with an overlap lower than a threshold, so that after receiving the recognition picture, the hardware engineer can clearly see the recognition areas with higher overlap and the recognition areas with lower overlap. This can avoid the problem that the hardware engineer mistakenly identifies the recognition areas with higher overlap as having lower overlap, or mistakenly identifies the recognition areas with lower overlap as having higher overlap when adjusting the camera, thereby improving the efficiency of adjusting the camera.

[0011] In some possible implementations, the color indicated by the first indication information is different from the color indicated by the second indication information.

[0012] This implementation sets the color indicated by the first indication information and the color indicated by the second indication information to be different, which can reflect the difference between the recognition areas with a high degree of overlap and the recognition areas with a low degree of overlap in a more intuitive way.

[0013] In some possible implementations, the recognition image further identifies an overlap value between at least two recognition areas of the multiple vehicles whose overlap between the recognition areas is greater than or equal to a threshold.

[0014] The above technical solution identifies the overlap value between at least two recognition areas in the recognition image with an overlap greater than or equal to a threshold, allowing hardware engineers to more clearly and quickly understand the degree of overlap between the recognition areas in the recognition image, thereby enabling them to adjust the camera parameters in a purposeful and targeted manner.

[0015] In some possible implementations, the recognition image further includes identification information of each of the multiple vehicles and third indication information, where the third indication information includes identification information of at least two vehicles whose recognition regions have an overlap greater than or equal to the threshold, and the overlap value of the at least two vehicles. This can reduce algorithm complexity.

[0016] In some possible implementations, the parameters of the camera include at least one of the following parameters: the height of the camera, the side angle between the main line of sight of the camera and the horizontal line, and the depression angle between the main line of sight of the camera and the vertical line.

[0017] In some possible implementations, the method further includes: identifying license plate information of a vehicle in a second vehicle image captured by the camera using the adjusted parameters.

[0018] In a second aspect, a device for adjusting a camera in a parking system is provided, characterized in that it includes units for executing the method in the above-mentioned first aspect or its various implementations.

[0019] In a third aspect, a device for adjusting a camera in a parking system is provided, comprising: a memory for storing a program; a processor for executing the program stored in the memory, wherein when the program stored in the memory is executed, the processor is used to execute the method in the above-mentioned first aspect or its various implementations.

[0020] In a fourth aspect, the present application further provides a computer-readable storage medium storing program code for execution by a device, wherein the program code includes instructions for executing the steps in the method of the above-mentioned first aspect or its various implementations.

[0021] In a fifth aspect, the present application also provides a computer program product, which includes a computer program stored on a computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the method in the above-mentioned first aspect or its various implementation methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a schematic diagram of a parking system according to an embodiment of the present application.

[0023] Figure 2It is a schematic flowchart of a method for adjusting a camera in a parking system in an embodiment of the present application.

[0024] Figure 3 This is a schematic diagram of an image recognition embodiment of the present application.

[0025] Figure 4 This is a schematic diagram of another identification image implemented in this application.

[0026] Figure 5 It is a schematic diagram of another parking system according to an embodiment of the present application.

[0027] Figure 6 It is a schematic block diagram of an apparatus for adjusting a camera in a parking system according to an embodiment of the present application.

[0028] Figure 7 It is a schematic block diagram of a device for adjusting a camera in a parking system according to another embodiment of the present application.

[0029] Figure 8 It is a structural diagram of a device for adjusting a camera in a parking system in an embodiment of the present application.

[0030] List of reference numerals:

[0031] 110, camera;

[0032] 120, parking management module;

[0033] 121, transmission device;

[0034] 122, identification device;

[0035] 123, fee management device;

[0036] 210, obtaining a first vehicle image captured by a camera, the first vehicle image including images of multiple vehicles in a target parking area;

[0037] 220. Obtaining, based on the first vehicle image and the vehicle region recognition model, a recognition image after identifying the plurality of vehicles, wherein the recognition image identifies a recognition region of each of the plurality of vehicles, and the recognition image includes an identifier of the recognition region of each vehicle, the identifier being used to indicate a degree of overlap between the recognition regions of the plurality of vehicles;

[0038] 230, sending the recognition image, wherein the overlap between the recognition areas of multiple vehicles is used to adjust the parameters of the camera;

[0039] 124, a device for adjusting a camera in a parking system;

[0040] 1241, send identification picture;

[0041] 130, hardware engineer;

[0042] 1301, adjusting camera parameters based on the overlap between recognition areas of multiple vehicles in the recognition image;

[0043] 600, a device for adjusting a camera in a parking system;

[0044] 610, acquisition unit;

[0045] 620, processing unit;

[0046] 630, communication unit;

[0047] 640, identification unit;

[0048] 800, a device for adjusting cameras in a parking system;

[0049] 801, memory;

[0050] 802, processor;

[0051] 803, communication interface;

[0052] 804, bus. DETAILED DESCRIPTION

[0053] The technical solutions in the embodiments of the present application are described below in conjunction with the accompanying drawings. It should be understood that the specific examples in this specification are only intended to help those skilled in the art better understand the embodiments of the present application, and are not intended to limit the scope of the embodiments of the present application.

[0054] It should be understood that in the various embodiments of the present application, the size of the serial number of each process does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0055] It should also be understood that the various implementation methods described in this specification can be implemented individually or in combination, and the embodiments of the present application are not limited to this.

[0056] Unless otherwise specified, all technical and scientific terms used in the embodiments of the present application have the same meaning as those commonly understood by those skilled in the art in the art of the present application. The terms used in this application are only for the purpose of describing specific embodiments and are not intended to limit the scope of this application.

[0057] Temporary roadside parking spaces are located along the roadside, without fixed entrances or exits. These spaces are typically charged and managed manually. However, this parking management method is not only labor-intensive and inefficient, but also, due to the long length of the roadside parking area, toll collectors are unable to manage all spaces, resulting in the inability to collect parking fees in a timely manner.

[0058] To address this issue, some technologies have emerged that utilize electronic devices such as geomagnetic detectors, ultrasonic detectors, parking meter posts, or cameras to manage vehicle parking. These technologies no longer rely on manual parking fee collection, addressing the high costs, difficulty in supervision, low efficiency, and the tendency for missed charges associated with traditional parking management methods. These technologies are becoming a trend in future parking management. The embodiments of this application are applied to vehicle parking management using cameras.

[0059] Figure 1 A schematic diagram of a parking system using a camera for parking management is shown, wherein the parking system may include a camera 110 and a parking management module 120 , and the parking management module 120 may include a transmission device 121 , an identification device 122 and a fee management device 123 .

[0060] Optionally, the camera 110 may be mounted on a streetlight pole or a building on the roadside, wherein the field of view of one camera may include multiple parking spaces, such as Figure 1 As shown, the field of view of the camera 110 includes four parking spaces. If a vehicle is parked within the field of view of the camera 110, the camera 110 can capture a vehicle image of the vehicle.

[0061] Afterwards, the camera 110 may transmit the captured vehicle image to the transmission device 121 in the parking management module 120. For example, the camera 110 may transmit the vehicle image via a local area network to the transmission device 121. For example, the transmission device 121 may be a wired transmission device or a wireless transmission device.

[0062] The recognition device 122 is used to receive the vehicle image sent by the transmission device 121 and determine the vehicle information based on the received vehicle image. The vehicle information may include but is not limited to the license plate number, vehicle color, vehicle size, etc.

[0063] Next, the identification device 122 sends the determined vehicle information to the fee management device 123. Based on the vehicle information, the fee management device 123 determines the vehicle's parking time and generates billing data based on the parking time and billing rules. This allows users to pay by scanning the QR code displayed on the parking space upon leaving. Alternatively, the fee management device 123 can push the billing data to the user's mobile phone via a parking management app.

[0064] Furthermore, the recognition device 122 can also determine the occupancy status of the parking space within the coverage area of the camera 110 based on the received vehicle image, such as Figure 1 Of the four parking spaces, three are already occupied and one is vacant. Furthermore, the identification device 122 can inform the user of the occupancy and filling of the parking spaces at the location through a parking management application (APP) or other means, thereby achieving the purpose of regional parking guidance.

[0065] It should be understood that Figure 1 This is only a schematic diagram of a parking system provided in an embodiment of the present application. The positional relationship between the equipment, devices, modules, etc. shown in the diagram does not constitute any limitation.

[0066] The accuracy of parking management in a parking system depends on the camera's installation position. For example, if the angle between the camera and the parking space is too small, the images of two adjacent vehicles captured by the camera will often overlap significantly. This makes it impossible for the parking management module to identify the license plates of two adjacent vehicles based on the vehicle images, and thus, it is impossible to charge parking fees based on the license plates. If the angle between the camera and the parking space is too large, although the parking management module can more easily identify the license plates of adjacent vehicles, the excessive angle may cause additional difficulties in recognizing the license plates of vehicles closer to the camera.

[0067] Therefore, how to accurately and effectively install cameras in parking systems has become an urgent problem to be solved.

[0068] In view of this, an embodiment of the present application proposes a method for adjusting a camera in a parking system. After the camera is pre-installed, the vehicle image is processed according to the vehicle image captured by the pre-installed camera, so that the hardware engineer can adjust the pre-installed camera in real time based on the processed vehicle image, thereby achieving the purpose of accurately and effectively installing the camera in the parking system.

[0069] Figure 2 The schematic flow chart of the method 200 for adjusting a camera in a parking system according to an embodiment of the present application is shown. The method 200 may be performed by a device for adjusting a camera, which may include: Figure 1 In the parking management module 120. Figure 2 As shown, method 200 may include at least part of the following contents.

[0070] Optionally, the method 200 may be applied to the roadside parking system mentioned above.

[0071] Optionally, the method 200 may be applied to a parking system in a large parking lot, such as an underground parking lot.

[0072] 210 , obtaining a first vehicle image captured by a camera, where the first vehicle image includes images of multiple vehicles in a target parking area.

[0073] The first vehicle image is a vehicle image captured by the camera at the pre-installation position. Optionally, the camera parameters used in the pre-installation of the camera may be determined empirically, or may be the camera parameters used when the camera was last installed.

[0074] For example, the camera parameters used for camera pre-installation can be determined by a device for adjusting the camera in the parking system and sent to a hardware engineer. The hardware engineer then pre-installs the camera based on the received camera parameters. Alternatively, the camera parameters can be determined by the hardware engineer himself.

[0075] Camera parameters may include, but are not limited to, at least one of the following parameters: camera height, side angle, and pitch angle. The camera height is the distance between the camera and the ground; the camera side angle is the angle between the camera's main line of sight and the horizontal line; and the camera pitch angle is the angle between the camera's main line of sight and the vertical line.

[0076] Optionally, the target parking area may include a parking space within the camera's field of view. Considering that some drivers do not park according to regulations and may park their vehicles in areas outside parking spaces, the target parking area may also include areas outside parking spaces within the camera's field of view.

[0077] Alternatively, the camera may directly send the first vehicle image to the device for adjusting the camera.

[0078] Alternatively, the camera may store the first vehicle image in the cloud, so that the device for adjusting the camera may obtain the first vehicle image from the cloud.

[0079] Alternatively, the first vehicle image captured by the camera mentioned above may be directly acquired. In this manner, the camera may transmit a vehicle image to the camera adjustment device only after a certain number of frames, which may easily result in discontinuous vehicle images.

[0080] Alternatively, obtaining the first vehicle image captured by the camera may include: obtaining a first video stream captured by the camera, and intercepting the first vehicle image from the first video stream.

[0081] The above technical solution first obtains a video stream and then captures a vehicle image from the video stream. Because the camera transmits each frame of the video stream to the device for adjusting the camera, the multiple vehicle images captured by the device for adjusting the camera from the video stream are continuous. In other words, the device for adjusting the camera can obtain each frame of the vehicle image, which facilitates subsequent operations.

[0082] Optionally, in this embodiment of the present application, the device for adjusting the camera may also utilize a tracking algorithm to track each vehicle in the continuous first video stream. For example, the tracking algorithm may be utilized to determine which vehicle in the current frame corresponds to which vehicle in the previous frame. This avoids the problem of misidentifying vehicles in different frames.

[0083] The tracking algorithm may be any one of the following algorithms: Kalman filter algorithm, optical flow method, particle filter algorithm or mean shift algorithm.

[0084] 220. Based on the first vehicle image and the vehicle area recognition model, an identification image is obtained after identifying multiple vehicles. The identification image identifies the identification area of each of the multiple vehicles, and includes an identification of the identification area of each vehicle, which is used to indicate the degree of overlap between the identification areas of the multiple vehicles.

[0085] The vehicle area recognition model can be obtained from a vehicle image and a recognition area of a sample vehicle. Accordingly, the vehicle area recognition model only needs to obtain the recognition area of the vehicle, without requiring a complex calculation model.

[0086] The vehicle recognition model may be, but is not limited to, logistic regression (LR), gradient boosting decision tree (GBDT), support vector machine (SVM), neural network, etc.

[0087] The neural network here can be a heavyweight neural network, such as a deep neural network (DNN), or a lightweight neural network, such as SqueezeNet, ShuffleNet, MobileNet, and Xception.

[0088] Because heavyweight neural networks have higher computing power than lightweight neural networks, given the same camera parameters, a heavyweight neural network might be able to identify a vehicle's license plate information in a captured image, while a lightweight neural network might not. Given the uncertainty of the actual product's computing power during production, a lightweight neural network is used during camera adjustment. This ensures that regardless of whether the actual product uses a heavyweight or lightweight neural network, the camera adjustment device can accurately identify the vehicle's identification area.

[0089] Furthermore, since lightweight neural networks have a faster processing speed, setting the vehicle area recognition model as a lightweight neural network model allows hardware engineers to adjust the camera to the optimal position in a shorter time.

[0090] Optionally, the first vehicle image and the recognition image can be used as sample data to input into the vehicle region recognition model to update the vehicle region recognition model. This increases the sample data used to train the vehicle region recognition model, and the trained vehicle region recognition model becomes more accurate, significantly reducing the number and time required to adjust the camera using the vehicle region recognition model.

[0091] It should be noted that both the first vehicle image and the identification image may include multiple images. For example, each frame may include a first vehicle image and an identification image.

[0092] Figure 3 is a schematic diagram of a frame of recognition picture, optionally, as Figure 3 As shown, the vehicle recognition area can be the area formed by the length and width of the vehicle, that is, the vehicle recognition area is a rectangle formed by the length and width of the vehicle. Alternatively, the vehicle recognition area can also be the outline of the vehicle, in which case the vehicle recognition area is an irregular geometric shape.

[0093] Alternatively, the overlap of recognition areas can be used to represent the degree of vehicle overlap. The overlap between the recognition areas of multiple vehicles can be expressed as the degree of overlap between two vehicles, that is, the degree of overlap between the two vehicles. For example, if the recognition area of vehicle 1 is R1 and the recognition area of vehicle 2 is R2, and the overlap between recognition areas R1 and R2 is C, then the overlap between vehicle 1 and vehicle 2 is also C.

[0094] The identification may include first indication information and / or second indication information, wherein the first indication information is used to indicate an identification area where the overlap between the identification areas of multiple vehicles is higher than or equal to a threshold, and the second indication information is used to indicate an identification area where the overlap between the identification areas of multiple vehicles is lower than a threshold.

[0095] As an example, the color indicated by the first indication information and the color indicated by the second indication information can be different. For example, assuming the vehicle recognition area is a rectangle, if two vehicles are very close together and have a high degree of overlap, the recognition areas of the two vehicles may be red rectangles. If the two vehicles are relatively far apart and the recognition areas of the two vehicles do not overlap, the recognition areas of the two vehicles may be green rectangles.

[0096] This implementation sets the color indicated by the first indication information and the color indicated by the second indication information to be different, which can reflect the difference between the recognition areas with a high degree of overlap and the recognition areas with a low degree of overlap in a more intuitive way.

[0097] As another example, the first indication information may be a dashed line, and the second indication information may be a solid line. Still assuming that the vehicle recognition area is a rectangle, if there is a high degree of overlap between two vehicles, the recognition areas of the two vehicles may be dashed boxes; if there is no overlap between the two vehicles, the recognition areas of the two vehicles may be solid boxes.

[0098] It should be understood that the specific examples in the embodiments of the present application are only intended to help those skilled in the art better understand the embodiments of the present application, rather than to limit the scope of the embodiments of the present application.

[0099] The above technical solution sets different identifications for recognition areas with an overlap higher than or equal to a threshold and for recognition areas with an overlap lower than a threshold, so that after receiving the recognition picture, the hardware engineer can clearly see the recognition areas with higher overlap and the recognition areas with lower overlap. This can avoid the problem that the hardware engineer mistakenly identifies the recognition areas with higher overlap as having lower overlap, or mistakenly identifies the recognition areas with lower overlap as having higher overlap when adjusting the camera, thereby improving the efficiency of adjusting the camera.

[0100] In order to enable hardware engineers to know more clearly and quickly the specific degree of overlap between the recognition areas in the recognition image with an overlap higher than or equal to a threshold, the recognition image can further identify the overlap value between at least two recognition areas with an overlap higher than or equal to the threshold.

[0101] In one implementation, the recognition image may include third indication information, which is used to indicate the overlap value between at least two recognition areas whose overlap is greater than or equal to a threshold. Optionally, the third indication information may be an intersection over union (IOU). IOU is a measure of the overlap between different objects, which can be expressed as the following formula:

[0102]

[0103] Among them, A and B are both vehicle identification areas. From the above formula, we can know that IOU is the ratio of the intersection area of A and B to the union area of A and B.

[0104] The larger the IOU, the higher the overlap between A and B. For example, Figure 4 As shown, Figure 4The lower right corner shows that the IOU between the recognition areas of vehicle 3 and vehicle 6 is 0.25, and the IOU between the recognition areas of vehicle 6 and vehicle 7 is 0.23. It can be seen that the overlap between vehicle 3 and vehicle 6 is higher than the overlap between vehicle 3 and vehicle 6.

[0105] The above technical solution identifies the overlap value between at least two recognition areas in the recognition image with an overlap greater than or equal to a threshold, allowing hardware engineers to more clearly and quickly understand the degree of overlap between the recognition areas in the recognition image, thereby enabling them to adjust the camera parameters in a purposeful and targeted manner.

[0106] Of course, in addition to identifying the overlap value between at least two recognition areas with an overlap greater than or equal to a threshold, the recognition image may also identify the overlap value between at least two recognition areas with an overlap less than a threshold.

[0107] Optionally, in the embodiment of the present application, the identification image may further include identification information of each of the multiple vehicles. As an example, the identification information may be an ID. Figure 3 and Figure 4 , Figure 3 and Figure 4 There are 7 vehicles, and the IDs of the 7 vehicles are 1, 2...7 respectively.

[0108] It should be noted that the ID can be a unique ID assigned to each vehicle by the camera adjustment device. For multiple frames of different recognition images, the same vehicle ID remains the same. For example, the recognition image in the nth frame includes vehicles A, B, C, and D, and the IDs of these four vehicles are 1, 2, 3, and 4, respectively. The recognition image in the (n+2)th frame includes vehicles B, C, and E. Vehicle B's ID remains 2, and Vehicle C's ID remains 3.

[0109] In this case, the third indication information may include identification information of at least two vehicles whose overlap between the recognition areas is greater than or equal to a threshold value and the overlap value of the at least two vehicles. In this way, the complexity of the algorithm can be reduced.

[0110] For example, Figure 4 As shown in the figure, the identification information of the two vehicles at the top are 6 and 7 respectively, and the overlap value of the recognition areas of these two vehicles is 0.23. Figure 4 As can be seen from the lower right corner, the third indication information includes identification information 6 and 7, and also includes the IOU value between the two vehicles with identification information 6 and 7, namely 6-7IOU: 0.23. Similarly, the overlap value of the recognition area of the vehicles with identification information 3 and 6 is 0.25. Figure 4It can be seen again in the lower right corner that the third indication information includes identification information 3 and 6, and also includes the IOU value between the two vehicles whose identification information is 3 and 6 respectively, that is, 3-6IOU: 0.25.

[0111] Alternatively, the identification image may include identification information for each vehicle's identification area. Similar to the vehicle's identification information, the identification information for the identification area may be an ID, and each vehicle's identification area ID is unique. In this case, the third indication information includes the identification information for at least two identification areas whose overlap is greater than or equal to a threshold, and the overlap value between the at least two identification areas.

[0112] 230 , sending the recognition image, wherein the overlap between the recognition areas of multiple vehicles is used to adjust the parameters of the camera.

[0113] Specifically, if Figure 5 As shown, 1241, the device 124 for adjusting the camera can send a recognition picture to the hardware engineer; 1301, the hardware engineer 130 receives the recognition picture and adjusts the parameters of the camera based on the overlap between the recognition areas of multiple vehicles in the recognition picture.

[0114] Optionally, sending the identification picture may specifically include: packaging multiple identification pictures into a second video stream, and sending the second video stream.

[0115] Furthermore, after 230, the camera may capture a second vehicle image using the adjusted parameters, and the device for adjusting the camera may obtain the second vehicle image and identify vehicle information of the vehicle in the second vehicle image. The vehicle information may include a license plate, vehicle color, and vehicle size.

[0116] If the camera adjustment device can identify all vehicle information of the vehicle in the second vehicle image, the camera has been adjusted to the optimal position, which is the final installation position of the camera. In addition, the camera adjustment device can determine the parking time of the vehicle based on the identified vehicle information and charge parking fees for the vehicle in the second vehicle image.

[0117] Alternatively, if the vehicle information of the vehicle in the second vehicle image still cannot be recognized, the camera adjustment device continues to generate a recognition image based on the second vehicle image and the vehicle area recognition model. The recognition image includes the recognition area of each of the multiple vehicles in the second vehicle image. The recognition image is then sent to the hardware engineer to adjust the camera parameters again based on the recognition area of each vehicle.

[0118] The camera, the device for adjusting the camera, and the hardware engineer repeat the above operations in sequence until the device for adjusting the camera can accurately identify the vehicle information of all vehicles in the vehicle image.

[0119] It should be understood that in the embodiments of the present application, "first" and "second" are only used to distinguish different objects, but do not limit the scope of the embodiments of the present application.

[0120] In an embodiment of the present application, a recognition image is generated based on a vehicle image captured using the camera's initial parameters and a vehicle area recognition model, identifying each vehicle's recognition area. This recognition image includes an identifier indicating the degree of overlap between the vehicle's recognition areas, and the recognition image is then transmitted. Thus, upon receiving the recognition image, hardware engineers can adjust the camera parameters in real time and purposefully based on the degree of overlap between each vehicle's recognition areas. This not only significantly reduces the time required to adjust the camera, but also allows for accurate and efficient camera installation, thereby improving the accuracy of identifying vehicle information.

[0121] Furthermore, since the recognition area of a vehicle is much simpler than the recognition of specific license plate information, in an embodiment of the present application, the camera is adjusted using the overlap of the vehicle's recognition area, which does not require complex calculations, thereby increasing processing speed and being applicable to more parking systems.

[0122] The above describes in detail the method embodiments of the embodiments of the present application. The following describes the device embodiments of the embodiments of the present application. The device embodiments and the method embodiments correspond to each other. Therefore, for the parts that are not described in detail, please refer to the previous method embodiments. The device can implement any possible implementation method of the above methods.

[0123] Figure 6 FIG2 shows a schematic block diagram of an apparatus 600 for adjusting a camera in a parking system according to an embodiment of the present application. The apparatus 600 can execute the method for adjusting a camera in a parking system according to the embodiment of the present application. For example, the apparatus 600 can be the apparatus for adjusting a camera in the aforementioned method 200, such as Figure 5 124 of them.

[0124] like Figure 6 As shown, the apparatus 600 may include:

[0125] An acquiring unit 610 is configured to acquire a first vehicle image captured by a camera, wherein the first vehicle image includes images of multiple vehicles in a target parking area;

[0126] a processing unit 620 configured to obtain, based on the first vehicle image and the vehicle region recognition model, a recognition image for identifying the multiple vehicles, wherein the recognition image identifies a recognition region for each of the multiple vehicles and includes an identifier for the recognition region of each vehicle, the identifier being used to indicate a degree of overlap between the recognition regions of the multiple vehicles;

[0127] The communication unit 630 is configured to send the recognition image, wherein the overlap between the recognition areas of the multiple vehicles is used to adjust the parameters of the camera.

[0128] Optionally, in one embodiment of the present application, the identification includes first indication information and / or second indication information, the first indication information is used to indicate the identification area where the overlap between the identification areas of the multiple vehicles is higher than or equal to a threshold, and the second indication information is used to indicate the identification area where the overlap between the identification areas of the multiple vehicles is lower than the threshold.

[0129] Optionally, in one embodiment of the present application, the color indicated by the first indication information is different from the color indicated by the second indication information.

[0130] Optionally, in one embodiment of the present application, the recognition image further identifies an overlap value between at least two vehicles whose recognition areas of the multiple vehicles have an overlap value greater than or equal to a threshold.

[0131] Optionally, in one embodiment of the present application, the recognition image also includes identification information of each of the multiple vehicles and third indication information, and the third indication information includes identification information of at least two vehicles whose overlap between recognition areas is higher than or equal to the threshold and the overlap value of the at least two vehicles.

[0132] Optionally, in one embodiment of the present application, the parameters of the camera include at least one of the following parameters: the height of the camera, the side angle between the main line of sight of the camera and the horizontal line, and the depression angle between the main line of sight of the camera and the vertical line.

[0133] Optionally, in one embodiment of the present application, the acquiring unit 610 may further be configured to: acquire a second vehicle image captured by the camera using the adjusted parameters;

[0134] like Figure 7 As shown, the apparatus 600 may further include: an identification unit 640, configured to identify vehicle information of the vehicle in the second vehicle picture.

[0135] Figure 8 Schematic diagram of the hardware structure of the device for adjusting the camera in the parking system of an embodiment of the present application. Figure 8The device 800 for adjusting a camera in a parking system shown includes a memory 801 , a processor 802 , a communication interface 803 , and a bus 804 . The memory 801 , the processor 802 , and the communication interface 803 are connected to each other via the bus 804 .

[0136] Memory 801 can be a read-only memory (ROM), a static storage device, or a random access memory (RAM). Memory 801 can store programs. When the program stored in memory 801 is executed by processor 802, processor 802 and communication interface 803 are used to perform the various steps of the method for adjusting a camera in a parking system according to an embodiment of the present application.

[0137] The processor 802 can be a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), a graphics processing unit (GPU) or one or more integrated circuits, and is used to execute relevant programs to implement the functions required to be performed by the units in the device for adjusting the camera in the parking system of the embodiment of the present application, or to execute the method for adjusting the camera in the parking system of the embodiment of the present application.

[0138] The processor 802 may also be an integrated circuit chip having signal processing capabilities. In implementation, each step of the method for adjusting a camera in a parking system according to an embodiment of the present application may be accomplished by hardware integrated logic circuits in the processor 802 or by software instructions.

[0139] The processor 802 may also be a general-purpose processor, a digital signal processor (DSP), an ASIC, a field programmable gate array (FPGA), or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component. It may implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of this application. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application may be directly implemented and executed by a hardware processor, or by a combination of hardware and software modules within the processor. The software module may be located in a storage medium well-established in the art, such as a random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or register. The storage medium is located in the memory 801. The processor 802 reads the information in the memory 801 and, in conjunction with its hardware, performs the functions required to be performed by the units included in the device for adjusting a camera in the parking system of the embodiments of this application, or performs the method for adjusting a camera in the parking system of the embodiments of this application.

[0140] The communication interface 803 uses a transceiver device such as, but not limited to, a transceiver to implement communication between the device 800 and other devices or a communication network. For example, the first vehicle image captured by the camera can be obtained through the communication interface 803.

[0141] The bus 804 may include a path for transmitting information between various components of the device 800 (eg, the memory 801 , the processor 802 , and the communication interface 803 ).

[0142] It should be noted that although the above-mentioned device 800 only shows a memory, a processor, and a communication interface, in the specific implementation process, those skilled in the art should understand that the device 800 may also include other devices necessary for normal operation. At the same time, according to specific needs, those skilled in the art should understand that the device 800 may also include hardware devices that implement other additional functions. In addition, those skilled in the art should understand that the device 800 may also include only the devices necessary to implement the embodiments of the present application, and does not necessarily include Figure 8 All devices shown in .

[0143] An embodiment of the present application further provides a computer-readable storage medium storing program code for execution by a device, wherein the program code includes instructions for executing the steps in the method for adjusting a camera in the above-mentioned parking system.

[0144] An embodiment of the present application further provides a computer program product, which includes a computer program stored on a computer-readable storage medium, wherein the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the method for adjusting a camera in the above-mentioned parking system.

[0145] The aforementioned computer-readable storage medium may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0146] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0147] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. 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 through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0148] The terms used in this application are only used to describe the embodiments and are not used to limit the claims. As used in the description of the embodiments and claims, unless the context clearly indicates, the singular forms "a" and "the" are intended to also include plural forms. Similarly, the terms "and / or" as used in this application refer to any and all possible combinations of one or more associated listings. In addition, when used in this application, the term "comprising" refers to the existence of stated features, wholes, steps, operations, elements, and / or components, but does not exclude the existence or addition of one or more other features, wholes, steps, operations, elements, components and / or these groups.

[0149] The various aspects, implementations, implementations, or features of the described embodiments can be used individually or in any combination. The various aspects of the described embodiments can be implemented by software, hardware, or a combination of software and hardware. The described embodiments can also be embodied by a computer-readable medium storing computer-readable code, the computer-readable code comprising instructions executable by at least one computing device. The computer-readable medium can be associated with any data storage device capable of storing data that can be read by a computer system. Exemplary computer-readable media can include read-only memory, random access memory, compact disc read-only memory (CD-ROM), hard disk drive (HDD), digital video disc (DVD), magnetic tape, and optical data storage devices. The computer-readable medium can also be distributed among computer systems connected via a network so that the computer-readable code can be stored and executed in a distributed manner.

[0150] The above technical description may refer to the accompanying drawings, which form a part of this application and illustrate implementation methods in accordance with the described embodiments in the drawings. Although these embodiments are described in sufficient detail to enable those skilled in the art to implement these embodiments, these embodiments are non-limiting; other embodiments can be used and changes can be made without departing from the scope of the described embodiments. For example, the order of operations described in the flowchart is non-limiting, so the order of two or more operations illustrated in the flowchart and described according to the flowchart can be changed according to several embodiments. As another example, in several embodiments, one or more operations illustrated in the flowchart and described according to the flowchart are optional or deletable. In addition, certain steps or functions can be added to the disclosed embodiments, or the order of two or more steps can be replaced. All these changes are considered to be included in the disclosed embodiments and the claims.

[0151] In addition, terms are used in the above technical description to provide a thorough understanding of the described embodiments. However, overly detailed details are not required to implement the described embodiments. Therefore, the above description of the embodiments is presented for the purpose of illustration and description. The embodiments presented in the above description and the examples disclosed based on these embodiments are provided separately to add context and help understand the described embodiments. The above description is not intended to be exhaustive or to limit the described embodiments to the precise form of the present application. Based on the above teachings, several modifications, selective applications and variations are feasible. In some cases, well-known processing steps are not described in detail to avoid unnecessarily affecting the described embodiments.

[0152] The above description is merely a specific implementation of the embodiments of the present application, but the scope of protection of the embodiments of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the embodiments of the present application should be included in the scope of protection of the embodiments of the present application. Therefore, the scope of protection of the embodiments of the present application should be based on the scope of protection of the claims.

Claims

1. A method for adjusting a camera in a parking system, characterized in that: include: 210, obtaining a first vehicle image captured by a camera, wherein the first vehicle image includes images of multiple vehicles in a target parking area; 220. Obtaining, based on the first vehicle image and the vehicle region recognition model, a recognition image after identifying the multiple vehicles, wherein the recognition image identifies a recognition region of each of the multiple vehicles and includes an identifier of the recognition region of each vehicle, wherein the identifier indicates a degree of overlap between the recognition regions of the multiple vehicles; 230, sending the recognition picture, wherein the overlap between the recognition areas of the multiple vehicles is used to adjust the parameters of the camera; The identification includes first indication information and / or second indication information, the first indication information is used to indicate the identification area where the overlap between the identification areas of the multiple vehicles is higher than or equal to a threshold, and the second indication information is used to indicate the identification area where the overlap between the identification areas of the multiple vehicles is lower than the threshold.

2. The method according to claim 1, characterized in that The color indicated by the first indication information is different from the color indicated by the second indication information.

3. The method according to claim 1 or 2, characterized in that The recognition image further identifies an overlap value between at least two recognition areas of the multiple vehicles whose overlap between the recognition areas is greater than or equal to a threshold.

4. The method according to claim 3, characterized in that The recognition image also includes identification information of each of the multiple vehicles and third indication information, and the third indication information includes identification information of at least two vehicles whose overlap between recognition areas is higher than or equal to the threshold and the overlap value of the at least two vehicles.

5. The method according to claim 1, wherein The parameters of the camera include at least one of the following parameters: the height of the camera, the side angle between the main line of sight of the camera and the horizontal line, and the depression angle between the main line of sight of the camera and the vertical line.

6. The method according to claim 1, characterized in that The method further comprises: Obtaining a second vehicle image captured by the camera using the adjusted parameters; Identify vehicle information of the vehicle in the second vehicle image.

7. A device for adjusting a camera in a parking system, characterized in that: include: An acquisition unit (610) is configured to acquire a first vehicle image captured by a camera, wherein the first vehicle image includes images of a plurality of vehicles in a target parking area; a processing unit (620) configured to obtain, based on the first vehicle image and the vehicle region recognition model, a recognition image after identifying the plurality of vehicles, wherein the recognition image identifies the recognition region of each of the plurality of vehicles, and the recognition image includes an identifier of the recognition region of each vehicle, wherein the identifier is used to indicate a degree of overlap between the recognition regions of the plurality of vehicles; a communication unit (630) for transmitting the recognition image, wherein the overlap between the recognition areas of the plurality of vehicles is used to adjust the parameters of the camera; The identification includes first indication information and / or second indication information, the first indication information is used to indicate the identification areas where the overlap between the identification areas of the multiple vehicles is higher than or equal to a threshold, and the second indication information is used to indicate the identification areas where the overlap between the identification areas of the multiple vehicles is lower than the threshold.

8. A device for adjusting a camera in a parking system, characterized in that: include: Memory, used to store programs; A processor is configured to execute a program stored in the memory. When the program stored in the memory is executed, the processor is configured to execute the method for adjusting a camera in a parking system according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable medium stores a program code for execution by a device, wherein the program code includes instructions for executing the steps of the method for adjusting a camera in a parking system according to any one of claims 1 to 6.

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