A camera and a corresponding lane number detection method and device

Abstract

The embodiment of the application discloses a camera and a corresponding lane number detection method and device, the method comprising: acquiring multiple cameras on the same road for monitoring different lanes to form an interactive group; calculating the overlapping area of each two cameras in the interactive group; and when the shooting range of any two cameras is calculated to have an overlapping area, calculating the relative position between the two cameras; sorting the multiple cameras according to the relative positions of the multiple cameras in the interactive group, and determining the lane numbers corresponding to the multiple cameras according to the sorting. Through the embodiment, the efficiency of the server in entering the lane numbers of the camera installation of the road monitoring system is improved, the entry error is reduced, and the entry cost is reduced.

Description

Technical Field

[0001] This application relates to road monitoring technology, and more particularly to a camera and its corresponding lane number detection method and device. Background Technology

[0002] With the increasing number of motor vehicles on the road, road monitoring systems have become an important component of the public security command system. When setting up a road monitoring system, road video surveillance cameras are installed at various checkpoints, and a communication network is configured to enable centralized control of the cameras at each checkpoint via a server cluster.

[0003] The standard lane width for Chinese standard highways is 2 x 7.5 meters for a two-way four-lane highway and 2 x 11.25 meters for a two-way six-lane highway. Different cameras are installed on different lanes, for example... Figure 1 As shown, taking a two-lane road as an example, the lanes are numbered 1 and 2 respectively. Camera a is installed in lane 1, and camera b is installed in lane 2.

[0004] Existing methods for matching cameras with lane numbers include:

[0005] 1. The specific lane where each camera is installed is manually recorded and then entered into the management server system. Since the number of cameras in a road monitoring system can reach hundreds or even thousands, manually recording and entering the data into the server system is extremely time-consuming and labor-intensive.

[0006] 2. The device uses its built-in GPS (Global Positioning System) to report its location to the management server system, which then calculates the camera's lane number. However, the GPS positioning accuracy of the camera is poor, resulting in a large positional error, typically around 10 meters. This makes it unsuitable for scenarios requiring precise location and lane number information for each camera at a checkpoint.

[0007] 3. Send a location request message to a third-party high-precision positioning system for a fee. The third-party high-precision positioning system returns high-precision location coordinates, and the device then reports its location and lane number to the management server system. This solution requires payment and is too costly. Summary of the Invention

[0008] This application provides a camera and its corresponding lane number detection method and apparatus, which can improve the efficiency of server input of lane numbers installed in road monitoring system cameras, reduce input errors, and lower input costs.

[0009] This application provides a method for detecting lane numbers corresponding to cameras, which may include:

[0010] Acquire multiple cameras on the same road used to monitor different lanes and form an interactive group;

[0011] The overlapping area is calculated for each pair of cameras in the interactive group; and when it is found that the shooting ranges of any two cameras have an overlapping area, the relative position between the two cameras is calculated.

[0012] The multiple cameras are sorted according to their relative positions within the interactive group, and the lane numbers corresponding to each of the multiple cameras are determined based on the sorting.

[0013] In an exemplary embodiment of this application, acquiring an interactive group of multiple cameras on the same road used for monitoring different lanes may include: performing the following process for each camera:

[0014] Using the camera's built-in positioning system, it broadcasts its own location information via a local area network; and receives location information broadcast by other cameras within the local area network besides itself.

[0015] Based on the received location information, determine one or more other cameras that are within a preset distance range from the camera itself, and form the interaction group with the one or more other cameras.

[0016] In an exemplary embodiment of this application, calculating the overlap region for each pair of cameras within the interaction group may include:

[0017] 31. Establish the set of comparison objects and the set of objects being compared;

[0018] 32. Select any camera in the interaction group as a comparison object and put it into the comparison object set, and put all cameras in the interaction group other than the comparison object into the comparison object set as comparison objects;

[0019] 33. Calculate the overlapping area between the comparison object and each comparison object in the set of comparison objects; wherein, when the calculation result shows that the shooting range of the comparison object and the comparison object overlaps, the comparison object and the comparison object are treated as any two cameras, and the relative position between the two cameras is calculated; when the calculation result shows that the shooting range of the comparison object and the comparison object does not overlap, the comparison object is deleted from the set of comparison objects, converted into a comparison object, and placed into the object set, and the overlapping area of ​​the comparison object is calculated with the next comparison object;

[0020] 34. After the overlapping area calculation of the comparison object with each of the comparison objects in the set of comparison objects is completed, the next comparison object is obtained and the process returns to step 33 until all comparison objects in the set of comparison objects have been compared.

[0021] In an exemplary embodiment of this application, the step of calculating the overlapping region between the comparison object and each of the comparison objects in the set of comparison objects may include: for the currently compared comparison object and any one of the comparison objects, performing the following process:

[0022] The comparison object initiates a comparison request to the comparison object, the comparison request including: the time period and time interval for capturing panoramic images;

[0023] Acquire at least one first panoramic image of the comparison object captured according to the time interval within the time period; and acquire at least one second panoramic image of the comparison object captured according to the time interval within the time period; wherein the first panoramic image and the second panoramic image are captured at the same time within each time period;

[0024] Detect whether there is an overlapping region between the first panoramic image and the second panoramic image;

[0025] When there is an overlapping area between the first panoramic image and the second panoramic image, it is determined that the shooting range of the comparison object and the compared object overlaps.

[0026] When the first panoramic image and the second panoramic image do not have an overlapping area, it is determined that the shooting range of the comparison object and the object being compared do not overlap.

[0027] In an exemplary embodiment of this application, detecting whether there is an overlapping region between the first panoramic image and the second panoramic image may include:

[0028] Multiple first feature points are obtained from the first panoramic image, and feature point information of the multiple first feature points is obtained;

[0029] The pixels in the second panoramic image are traversed to detect whether there is a second feature point in the second panoramic image that matches the feature point information of the first feature point.

[0030] When a second feature point matching the feature point information of the first feature point is detected in the second panoramic image, it is determined that there is an overlapping area between the first panoramic image and the second panoramic image.

[0031] When it is detected that there is no second feature point in the second panoramic image that matches the feature point information of the first feature point, it is determined that there is no overlapping area between the first panoramic image and the second panoramic image.

[0032] or,

[0033] Multiple second feature points are obtained from the second panoramic image, and feature point information of the multiple second feature points is obtained;

[0034] The pixels in the first panoramic image are traversed to detect whether there is a first feature point in the first panoramic image that matches the feature point information of the second feature point.

[0035] When a first feature point matching the feature point information of the second feature point is detected in the first panoramic image, it is determined that there is an overlapping area between the first panoramic image and the second panoramic image.

[0036] When it is detected that there is no first feature point in the first panoramic image that matches the feature point information of the second feature point, it is determined that there is no overlapping area between the first panoramic image and the second panoramic image.

[0037] In an exemplary embodiment of this application, obtaining a plurality of first feature points from the first panoramic image may include:

[0038] Calculate the gradient of each pixel in the first panoramic image;

[0039] The first panoramic image is divided into multiple first sub-region units, and the gradient histogram of each first sub-region unit is calculated to form the descriptor of the first sub-region unit. A first region block is formed by a preset number of first sub-region units, and the descriptors of the preset number of first sub-region units are concatenated to form the descriptor of the corresponding first region block. The descriptors of all the first region blocks are concatenated to form the descriptor of the first panoramic image.

[0040] The center pixels of the first region blocks with the highest gradient values ​​when sorted from largest to smallest are obtained as the first feature points of the first panoramic image; and the feature point information of the multiple first feature points is recorded; the feature point information of the multiple first feature points includes: the gradient magnitude of the multiple first feature points and the relative position between the multiple first feature points; the relative position between the multiple first feature points includes the direction vector between the multiple first feature points;

[0041] as well as,

[0042] The step of obtaining multiple second feature points from the second panoramic image may include:

[0043] Calculate the gradient of each pixel in the second panoramic image;

[0044] The second panoramic image is divided into multiple second sub-region units, and the gradient histogram of each second sub-region unit is calculated to form the descriptor of the second sub-region unit. A second region block is formed by a preset number of second sub-region units, and the descriptors of the preset number of second sub-region units are concatenated to form the descriptor of the corresponding second region block. The descriptors of all the second region blocks are concatenated to form the descriptor of the second panoramic image.

[0045] The center pixels of the second region blocks with the highest gradient values ​​when sorted from largest to smallest are obtained as the second feature points of the second panoramic image; and the feature point information of the multiple second feature points is recorded; the feature point information of the multiple second feature points includes: the gradient magnitude of the multiple second feature points and the relative position between the multiple second feature points; the relative position between the multiple second feature points includes the direction vector between the multiple second feature points.

[0046] In an exemplary embodiment of this application, detecting whether there is a second feature point in the second panoramic image that matches the feature point information of the first feature point may include:

[0047] The feature point information of the plurality of first feature points is compared with the feature point information of any plurality of second feature points traversed from the second panoramic image.

[0048] When the gradient magnitudes of the plurality of first feature points are the same as the gradient magnitudes of the plurality of second feature points, and the relative positions between the plurality of first feature points are consistent with the relative positions between the plurality of second feature points, it is determined that the plurality of first feature points and the plurality of second feature points match; and it is determined that there is a second feature point in the second panoramic image that matches the feature point information of the first feature point;

[0049] When the gradient magnitudes of the plurality of first feature points are not the same as the gradient magnitudes of the plurality of second feature points, and / or the relative positions between the plurality of first feature points are inconsistent with the relative positions between the plurality of second feature points, it is determined that the plurality of first feature points and the plurality of second feature points do not match; when the plurality of first feature points do not match any plurality of second feature points in the second panoramic image, it is determined that there are no second feature points in the second panoramic image that match the feature point information of the first feature points.

[0050] as well as,

[0051] The step of detecting whether there is a first feature point in the first panoramic image that matches the feature point information of the second feature point includes:

[0052] The feature point information of the plurality of second feature points is compared with the feature point information of any plurality of first feature points traversed from the first panoramic image.

[0053] When the gradient magnitudes of the plurality of second feature points are the same as the gradient magnitudes of the plurality of first feature points, and the relative positions between the plurality of second feature points are consistent with the relative positions between the plurality of first feature points, it is determined that the plurality of second feature points and the plurality of first feature points match; and it is determined that there is a first feature point in the first panoramic image that matches the feature point information of the second feature points;

[0054] When the gradient magnitudes of the plurality of second feature points are not the same as the gradient magnitudes of the plurality of first feature points, and / or the relative positions between the plurality of second feature points are inconsistent with the relative positions between the plurality of first feature points, it is determined that the plurality of second feature points and the plurality of first feature points do not match; when the plurality of second feature points do not match any plurality of first feature points in the first panoramic image, it is determined that there is no first feature point in the first panoramic image that matches the feature point information of the second feature points.

[0055] In an exemplary embodiment of this application, the arbitrary two cameras include a first camera and a second camera; calculating the relative position between the arbitrary two cameras may include:

[0056] The positions of the overlapping regions in the first panoramic image captured by the first camera and the second panoramic image captured by the second camera are detected, respectively.

[0057] When the overlapping region is located on the first side of the first panoramic image and the overlapping region is located on the second side of the second panoramic image, it is determined that the first camera and the second camera are adjacent to each other on the second side.

[0058] When the overlapping area is located on the second side of the first panoramic image and the overlapping area is located on the first side of the second panoramic image, it is determined that the second camera is adjacent to the second side of the first camera.

[0059] In an exemplary embodiment of this application, detecting the positions of the overlapping region in the first panoramic image captured by the first camera and the second panoramic image captured by the second camera may include:

[0060] Calculate the first average coordinates of multiple first feature points that match multiple second feature points; detect the relative position of the first average coordinates with the center point coordinates or the central axis of the first panoramic image; when the first average coordinates are located on a first side of the center point coordinates of the first panoramic image, determine that the overlapping region is located on a first side of the first panoramic image; when the first average coordinates are located on a second side of the center point coordinates of the first panoramic image, determine that the overlapping region is located on a second side of the first panoramic image; and,

[0061] Calculate the second average coordinates of multiple second feature points that match multiple first feature points; detect the relative position of the second average coordinates with the center point coordinates or the central axis of the second panoramic image; when the second average coordinates are located on the first side of the center point coordinates of the second panoramic image, determine that the overlapping area is located on the first side of the second panoramic image; when the second average coordinates are located on the second side of the center point coordinates of the second panoramic image, determine that the overlapping area is located on the second side of the second panoramic image.

[0062] This application embodiment also provides a camera-corresponding lane number detection device, which may include a processor and a computer-readable storage medium. The computer-readable storage medium stores instructions, and when the instructions are executed by the processor, the camera-corresponding lane number detection method is implemented.

[0063] This application also provides a camera, which may include a lane number detection device corresponding to the camera.

[0064] Compared with related technologies, the embodiments of this application may include: acquiring multiple cameras on the same road used for monitoring different lanes, forming an interactive group; calculating the overlapping area for each pair of cameras within the interactive group; and when it is calculated that the shooting ranges of any two cameras have an overlapping area, calculating the relative position between the two cameras; sorting the multiple cameras according to their relative positions within the interactive group, and determining the lane number corresponding to each of the multiple cameras based on the sorting. This embodiment improves the efficiency of server inputting the lane numbers of cameras installed in the road monitoring system, reduces input errors, and lowers input costs.

[0065] Other features and advantages of this application will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the application. Other advantages of this application can be realized and obtained by means of the solutions described in the description and the accompanying drawings. Attached Figure Description

[0066] The accompanying drawings are used to provide an understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0067] Figure 1 This is a flowchart of the lane number detection method corresponding to the camera in an embodiment of this application;

[0068] Figure 2 This is a schematic diagram of the overlapping area of ​​two images in an embodiment of this application;

[0069] Figure 3 This is another schematic diagram of the overlapping area of ​​two images in an embodiment of this application;

[0070] Figure 4 This is a schematic diagram of a camera at a checkpoint location according to an embodiment of this application;

[0071] Figure 5 This is a schematic diagram of camera broadcast information within a local area network according to an embodiment of this application;

[0072] Figure 6 This is a flowchart illustrating a method for calculating the overlapping area of ​​each pair of cameras within an interactive group, according to an embodiment of this application.

[0073] Figure 7 This is a flowchart illustrating a method for calculating the overlapping region between a comparison object and each comparison object in the set of comparison objects, according to an embodiment of this application.

[0074] Figure 8 This is a flowchart illustrating a method for calculating the relative position between any two cameras according to an embodiment of this application.

[0075] Figure 9 This is a block diagram of the lane number detection device corresponding to the camera in this application embodiment;

[0076] Figure 10 This is a block diagram of the camera components in an embodiment of this application. Detailed Implementation

[0077] This application describes several embodiments, but these descriptions are exemplary and not restrictive, and it will be apparent to those skilled in the art that many more embodiments and implementations are possible within the scope of the embodiments described herein. Although many possible combinations of features are shown in the drawings and discussed in the detailed description, many other combinations of the disclosed features are also possible. Unless specifically limited, any feature or element of any embodiment may be used in combination with, or may replace, any feature or element of any other embodiment.

[0078] This application includes and contemplates combinations of features and elements known to those skilled in the art. The embodiments, features, and elements disclosed in this application may also be combined with any conventional features or elements to form a unique inventive scheme as defined by the claims. Any feature or element of any embodiment may also be combined with features or elements from other inventive schemes to form another unique inventive scheme as defined by the claims. Therefore, it should be understood that any feature shown and / or discussed in this application may be implemented individually or in any suitable combination. Therefore, the embodiments are not limited except by the limitations imposed by the appended claims and their equivalents. Furthermore, various modifications and changes may be made within the scope of the appended claims.

[0079] Furthermore, in describing representative embodiments, the specification may have presented methods and / or processes as a specific sequence of steps. However, the method or process should not be limited to the specific order of steps described herein, to the extent that it does not depend on such a specific order. As will be understood by those skilled in the art, other sequences of steps are also possible. Therefore, the specific order of steps set forth in the specification should not be construed as a limitation of the claims. Moreover, the claims concerning the method and / or process should not be limited to the steps performed in the written order, and those skilled in the art will readily understand that these orders can be varied and still remain within the spirit and scope of the embodiments of this application.

[0080] This application provides a method for detecting the lane number corresponding to a camera, such as... Figure 1 As shown, it may include steps S101-S103:

[0081] S101. Acquire multiple cameras on the same road used for monitoring different lanes and form an interactive group;

[0082] S102. Calculate the overlapping area for each pair of cameras in the interactive group; and when it is found that the shooting ranges of any two cameras have an overlapping area, calculate the relative position between the two cameras.

[0083] S103. Sort the multiple cameras according to their relative positions within the interactive group, and determine the lane number corresponding to each of the multiple cameras based on the sorting.

[0084] In an exemplary embodiment of this application, by calculating the overlapping area of ​​panoramic images captured by every two cameras at the same checkpoint location, the relative position of the overlapping area of ​​the panoramic images captured by the two cameras (e.g., whether it is on the left or right side of the image) can be determined. This allows the determination of the relative position of the camera with respect to the camera being compared (e.g., left or right position). By sequentially confirming the relative order of all cameras at the same checkpoint location, the current camera installation location can be determined, i.e., which lane it is installed in, and the specific lane number can be calculated.

[0085] In exemplary embodiments of this application, as Figure 2 As shown, the overlapping area of ​​images 1 and 2 is on the right side of the entire scene in image 1, and the overlapping area of ​​images 1 and 2 is on the left side of the entire scene in image 2. Therefore, it can be determined that camera 1 is installed to the left of camera 2. Similarly, as... Figure 3 As shown, the same method can be used to determine that camera 1 is installed to the right of camera 2. By calculating the relative position of image 1 with all camera images at the same checkpoint location, the installation position of camera 1 can be determined.

[0086] In the exemplary embodiments of this application, the solutions of the embodiments of this application will be described in detail below.

[0087] In an exemplary embodiment of this application, acquiring an interactive group of multiple cameras on the same road used for monitoring different lanes may include: performing the following process for each camera:

[0088] Using the camera's built-in positioning system, it broadcasts its own location information via a local area network; and receives location information broadcast by other cameras within the local area network besides itself.

[0089] Based on the received location information, determine one or more other cameras that are within a preset distance range from the camera itself, and form the interaction group with the one or more other cameras.

[0090] In an exemplary embodiment of this application, the positioning system may include, but is not limited to, a GPS system, and the location information may include, but is not limited to, GPS information.

[0091] In an exemplary embodiment of this application, when cameras are installed at different checkpoint locations, each camera can connect to the network in parallel after power-on, and only cameras within the same local area network can communicate normally. For example... Figure 4 As shown.

[0092] In an exemplary embodiment of this application, based on the local area network (LAN), the GPS (Global Positioning System) system built into the cameras can be used to determine a set of cameras at the same checkpoint location and form an interactive group. Specifically, multiple cameras are typically deployed in the same checkpoint area, and these cameras are interconnected within the same LAN. Cameras within the LAN can broadcast their own device information, such as, but not limited to, GPS coordinates, device IP address (Internet Protocol address), model, and device serial number. Figure 5 As shown by the black dots, after any camera A in the local area network receives device information from other cameras, it can determine whether it and the other camera belong to the same checkpoint location according to the following calculation formula. If they do not belong to the same checkpoint location, the information is discarded without processing; if they belong to the same checkpoint location, they join the interaction group, completing the interaction group establishment.

[0093] S = F(GPS1, GPS2)

[0094] S < R;

[0095] In this context, GPS1 represents the coordinates of any camera A, GPS2 represents the coordinates of other cameras, and R represents a preset distance range. The value of R can be derived from practice, and R is generally around 15m.

[0096] In exemplary embodiments of this application, as Figure 6 As shown, the calculation of the overlapping area for each pair of cameras within the interactive group may include steps S201-S204:

[0097] S201. Establish the set of comparison objects and the set of objects to be compared.

[0098] In an exemplary embodiment of this application, in order to calculate the overlapping area for every two cameras, a set of comparison objects and a set of objects to be compared are employed. The set of comparison objects, denoted as set 1, can be pre-established, and the set of objects to be compared, denoted as set 2, can be pre-established.

[0099] S202. Obtain any one camera in the interaction group as a comparison object and put it into the comparison object set, and put all cameras in the interaction group other than the comparison object into the comparison object set as comparison objects.

[0100] In an exemplary embodiment of this application, set 1 initially contains only one comparison object, namely any camera A; the remaining cameras in the interaction group, excluding camera A, belong to set 2. The overlapping areas of the cameras in set 1 are calculated with those of the cameras in set 2, thereby determining the relative positions of each camera.

[0101] S203. Calculate the overlapping area between the comparison object and each comparison object in the set of comparison objects; wherein, when the calculation result shows that the shooting range of the comparison object and the comparison object overlaps, the comparison object and the comparison object are treated as any two cameras, and the relative position between the two cameras is calculated; when the calculation result shows that the shooting range of the comparison object and the comparison object does not overlap, the comparison object is deleted from the set of comparison objects, converted into a comparison object, and placed into the object set, and the overlapping area of ​​the comparison object is calculated with the next comparison object.

[0102] In exemplary embodiments of this application, as Figure 7 As shown, the step of calculating the overlapping region between the comparison object and each of the comparison objects in the set of comparison objects may include: for the currently compared comparison object and any one of the comparison objects, executing the following processes S301-S304:

[0103] S301, The comparison object initiates a comparison request to the comparison object, the comparison request including: the time period and time interval for capturing panoramic images.

[0104] In an exemplary embodiment of this application, cameras in set 1 send requests to cameras in set 2. Considering that under extreme conditions, adjacent lanes may appear visually similar, potentially leading to misjudgment of overlapping areas, the request content sent by the comparison objects in set 1 can be required to include the time period for capturing panoramic images (e.g., timespan = (2021-11-09 17:41~2021-11-09 17:51)) and the time interval for continuously capturing panoramic images (e.g., interval = 1).

[0105] S302. Obtain at least one first panoramic image of the comparison object captured according to the time interval within the time period; and obtain at least one second panoramic image of the comparison object captured according to the time interval within the time period; wherein the first panoramic image and the second panoramic image are captured at the same time within each time period.

[0106] In an exemplary embodiment of this application, the requested party (the comparison object) can take panoramic images at specified time intervals within a specified time period to obtain a second panoramic image and transmit the second panoramic image to the requesting party (the comparison object). At the same time, the requesting party will also take panoramic images at specified time intervals within a specified time period to obtain a first panoramic image.

[0107] S303. Detect whether there is an overlapping area between the first panoramic image and the second panoramic image.

[0108] In an exemplary embodiment of this application, after any camera A in set 1 receives a panoramic image from any camera B in set 2, it sequentially determines whether there is an overlapping area between the first panoramic image and the second panoramic image according to a preset method for determining the relative position of overlapping areas.

[0109] In an exemplary embodiment of this application, detecting whether there is an overlapping region between the first panoramic image and the second panoramic image may include:

[0110] Multiple first feature points are obtained from the first panoramic image, and feature point information of the multiple first feature points is obtained;

[0111] The pixels in the second panoramic image are traversed to detect whether there is a second feature point in the second panoramic image that matches the feature point information of the first feature point.

[0112] When a second feature point matching the feature point information of the first feature point is detected in the second panoramic image, it is determined that there is an overlapping area between the first panoramic image and the second panoramic image.

[0113] When it is detected that there is no second feature point in the second panoramic image that matches the feature point information of the first feature point, it is determined that there is no overlapping area between the first panoramic image and the second panoramic image.

[0114] Alternatively, detecting whether there is an overlapping region between the first panoramic image and the second panoramic image may include:

[0115] Multiple second feature points are obtained from the second panoramic image, and feature point information of the multiple second feature points is obtained;

[0116] The pixels in the first panoramic image are traversed to detect whether there is a first feature point in the first panoramic image that matches the feature point information of the second feature point.

[0117] When a first feature point matching the feature point information of the second feature point is detected in the first panoramic image, it is determined that there is an overlapping area between the first panoramic image and the second panoramic image.

[0118] When it is detected that there is no first feature point in the first panoramic image that matches the feature point information of the second feature point, it is determined that there is no overlapping area between the first panoramic image and the second panoramic image.

[0119] In an exemplary embodiment of this application, obtaining a plurality of first feature points from the first panoramic image may include:

[0120] Calculate the gradient of each pixel in the first panoramic image;

[0121] The first panoramic image is divided into multiple first sub-region units, and the gradient histogram of each first sub-region unit is calculated to form the descriptor of the first sub-region unit. A first region block is formed by a preset number of first sub-region units, and the descriptors of the preset number of first sub-region units are concatenated to form the descriptor of the corresponding first region block. The descriptors of all the first region blocks are concatenated to form the descriptor of the first panoramic image.

[0122] The center pixels of the first region blocks with the highest gradient values ​​when sorted from largest to smallest are obtained as the first feature points of the first panoramic image; and the feature point information of the multiple first feature points is recorded; the feature point information of the multiple first feature points includes: the gradient magnitude of the multiple first feature points and the relative position between the multiple first feature points; the relative position between the multiple first feature points includes the direction vector between the multiple first feature points.

[0123] The step of obtaining multiple second feature points from the second panoramic image may include:

[0124] Calculate the gradient of each pixel in the second panoramic image;

[0125] The second panoramic image is divided into multiple second sub-region units, and the gradient histogram of each second sub-region unit is calculated to form the descriptor of the second sub-region unit. A second region block is formed by a preset number of second sub-region units, and the descriptors of the preset number of second sub-region units are concatenated to form the descriptor of the corresponding second region block. The descriptors of all the second region blocks are concatenated to form the descriptor of the second panoramic image.

[0126] The center pixels of the second region blocks with the highest gradient values ​​when sorted from largest to smallest are obtained as the second feature points of the second panoramic image; and the feature point information of the multiple second feature points is recorded; the feature point information of the multiple second feature points includes: the gradient magnitude of the multiple second feature points and the relative position between the multiple second feature points; the relative position between the multiple second feature points includes the direction vector between the multiple second feature points.

[0127] In an exemplary embodiment of this application, the gradient of each pixel in the image (first panoramic image and second panoramic image) is calculated (this may include calculating the gradient magnitude and gradient direction of each pixel) to capture image contour edge information and further weaken the interference of illumination. The image is divided into small regional units (such as the first and second sub-regional units mentioned above), for example, each small regional unit is 6*6 pixels in size (the size of this regional unit can be defined according to different application scenarios, and there is no limitation on the specific value). The gradient histogram of each regional unit (i.e., the number of different gradients) is counted to form the descriptor of each regional unit. Several regional units (i.e., a preset number, which can be defined according to different application scenarios, and there is no limitation on the specific value) are combined into a regional block (such as the first and second regional blocks mentioned above). For example, the size of each regional block can be 3*3 regional units. The feature descriptors of all regional units in a regional block are concatenated to obtain the feature descriptor of that regional block. The feature descriptors of all regional blocks in the image are concatenated to obtain the feature descriptor of the image.

[0128] In an exemplary embodiment of this application, three first feature points and three second feature points may be selected. The center pixel of the region block with a larger gradient value is preferred as the feature point, and the gradient magnitude of the selected feature points and the relative position information between the feature points (e.g., the direction vector formed between the feature points) are recorded.

[0129] In an exemplary embodiment of this application, detecting whether there is a second feature point in the second panoramic image that matches the feature point information of the first feature point may include:

[0130] The feature point information of the plurality of first feature points is compared with the feature point information of any plurality of second feature points traversed from the second panoramic image.

[0131] When the gradient magnitudes of the plurality of first feature points are the same as the gradient magnitudes of the plurality of second feature points, and the relative positions between the plurality of first feature points are consistent with the relative positions between the plurality of second feature points, it is determined that the plurality of first feature points and the plurality of second feature points match; and it is determined that there is a second feature point in the second panoramic image that matches the feature point information of the first feature point;

[0132] When the gradient magnitudes of the plurality of first feature points are not the same as the gradient magnitudes of the plurality of second feature points, and / or the relative positions between the plurality of first feature points are inconsistent with the relative positions between the plurality of second feature points, it is determined that the plurality of first feature points and the plurality of second feature points do not match; when the plurality of first feature points do not match any plurality of second feature points in the second panoramic image, it is determined that there is no second feature point in the second panoramic image that matches the feature point information of the first feature point.

[0133] In an exemplary embodiment of this application, matching feature information can be found in image b (second panoramic image) based on the feature information of image a (first panoramic image). The center points of regions with consistent similarity (i.e., matching) within a region block can be used as matching feature points. After finding three feature points in image b that match image a, the relative position (i.e., direction vector) information is used to determine whether the direction vectors between any two feature points in images a and b are consistent. If the size of the feature points and the direction vectors between feature points in the two images are completely matched, it indicates that there is an overlapping region between the two images; otherwise, there is no overlapping region.

[0134] The step of detecting whether there is a first feature point in the first panoramic image that matches the feature point information of the second feature point includes:

[0135] The feature point information of the plurality of second feature points is compared with the feature point information of any plurality of first feature points traversed from the first panoramic image.

[0136] When the gradient magnitudes of the plurality of second feature points are the same as the gradient magnitudes of the plurality of first feature points, and the relative positions between the plurality of second feature points are consistent with the relative positions between the plurality of first feature points, it is determined that the plurality of second feature points and the plurality of first feature points match; and it is determined that there is a first feature point in the first panoramic image that matches the feature point information of the second feature points;

[0137] When the gradient magnitudes of the plurality of second feature points are not the same as the gradient magnitudes of the plurality of first feature points, and / or the relative positions between the plurality of second feature points are inconsistent with the relative positions between the plurality of first feature points, it is determined that the plurality of second feature points and the plurality of first feature points do not match; when the plurality of second feature points do not match any plurality of first feature points in the first panoramic image, it is determined that there is no first feature point in the first panoramic image that matches the feature point information of the second feature points.

[0138] In an exemplary embodiment of this application, matching feature information can be found in image a (first panoramic image) based on the feature information of image b (second panoramic image). The center points of regions with consistent similarity (i.e., matching) within a region block can be used as matching feature points. After finding three feature points in image a that match image b, the relative position (i.e., direction vector) information is used to determine whether the direction vectors between any two feature points in images a and b are consistent. If the size of the feature points and the direction vectors between feature points are perfectly matched, it indicates that there is an overlapping region between the two images; otherwise, there is no overlapping region.

[0139] S304. When the first panoramic image and the second panoramic image have an overlapping area, it is determined that the shooting range of the comparison object and the compared object overlaps; when the first panoramic image and the second panoramic image do not have an overlapping area, it is determined that the shooting range of the comparison object and the compared object does not overlap.

[0140] In an exemplary embodiment of this application, if two images (a first panoramic image and a second panoramic image) have an overlapping area, the system further determines whether its installation position is to the left or right of the other party's camera by comparing the position of the overlapping area between its own panoramic image and the other party's panoramic image.

[0141] In an exemplary embodiment of this application, multiple comparisons can be performed on multiple first panoramic images and multiple second panoramic images, and multiple comparison results can be obtained. The result with the highest probability (overlapping or non-overlapping) can be selected as the final result based on the multiple comparison results.

[0142] S204. After the overlapping area calculation between the comparison object and each of the comparison objects in the set of comparison objects is completed, the next comparison object is obtained, and the process returns to step S203 until all comparison objects in the set of comparison objects have been compared.

[0143] In an exemplary embodiment of this application, if the comparison object and the compared object do not overlap, it indicates that the two cameras are installed far apart and do not intersect in their monitoring fields. In this case, camera B (the compared object) is added to set 1, and camera B is removed from set 2. The above operation steps S203 and S204 are repeated to sequentially determine the relative positions of all comparison objects in set 1 and all compared objects in set 2, and finally confirm the position of the camera currently being compared relative to other cameras in the interaction group.

[0144] In exemplary embodiments of this application, as Figure 8As shown, the arbitrary two cameras include a first camera and a second camera; the calculation of the relative position between the arbitrary two cameras may include steps S401-S403:

[0145] S401. Detect the positions of the overlapping regions in the first panoramic image captured by the first camera and the second panoramic image captured by the second camera.

[0146] In an exemplary embodiment of this application, detecting the positions of the overlapping region in the first panoramic image captured by the first camera and the second panoramic image captured by the second camera may include:

[0147] Calculate the first average coordinates of multiple first feature points that match multiple second feature points; detect the relative position of the first average coordinates with the center point coordinates or the central axis of the first panoramic image; when the first average coordinates are located on a first side of the center point coordinates of the first panoramic image, determine that the overlapping region is located on a first side of the first panoramic image; when the first average coordinates are located on a second side of the center point coordinates of the first panoramic image, determine that the overlapping region is located on a second side of the first panoramic image; and,

[0148] Calculate the second average coordinates of multiple second feature points that match multiple first feature points; detect the relative position of the second average coordinates with the center point coordinates or the central axis of the second panoramic image; when the second average coordinates are located on the first side of the center point coordinates of the second panoramic image, determine that the overlapping area is located on the first side of the second panoramic image; when the second average coordinates are located on the second side of the center point coordinates of the second panoramic image, determine that the overlapping area is located on the second side of the second panoramic image.

[0149] In an exemplary embodiment of this application, if the shooting ranges of the two cameras overlap, the position of the overlapping area relative to the central axis of the original images (first panoramic image and second panoramic image) can be calculated. The average coordinates of three feature points are calculated according to the following formula.

[0150] In an exemplary embodiment of this application, the three feature points can be denoted as (x1, y1), (x2, y2), and (x3, y3), and the average coordinates are calculated as follows:

[0151]

[0152] S402. When the overlapping area is located on the first side (e.g., the right side) of the first panoramic image and the overlapping area is located on the second side (e.g., the left side) of the second panoramic image, it is determined that the first camera and the second camera are adjacent to each other on the second side (e.g., the left side).

[0153] S403. When the overlapping area is located on the second side (e.g., the left side) of the first panoramic image and the overlapping area is located on the first side (e.g., the right side) of the second panoramic image, it is determined that the second camera is adjacent to the second side (e.g., the left side) of the first camera.

[0154] In an exemplary embodiment of this application, any two cameras are denoted as A and B, respectively. The panoramic image captured by camera A is denoted as image a (first panoramic image), and the panoramic image captured by camera B is denoted as image b (second panoramic image). Determining the relative position of cameras A and B is transformed into calculating the position of the overlapping area of ​​images a and b relative to the original images. That is, if the overlapping area is to the right of the central axis of the original image a and to the left of the central axis of the original image b, then camera A can be determined to be to the left of B. Conversely, if the overlapping area is to the left of the central axis of the original image a and to the right of the central axis of the original image b, then camera A can be determined to be to the right of B.

[0155] In an exemplary embodiment of this application, specifically, if the average coordinates of the three first feature points of image a (first panoramic image) are located to the right of the center point coordinates of image a, and the average coordinates of the three second feature points of image b (second panoramic image) are located to the left of the center point coordinates of image b, it can be determined that camera A is located to the left of camera B. If the average coordinates of the three first feature points of image a are located to the left of the center point coordinates of image a, and the average coordinates of the three second feature points of image b are located to the right of the center point coordinates of image b, it can be determined that camera A is located to the right of camera B.

[0156] In an exemplary embodiment of this application, the above steps are used to determine the relative positions of any two cameras. Based on the relative positions of multiple cameras within the interactive group, the order of the multiple cameras can be determined, and based on the order of the multiple cameras, the lane number associated with each camera can be finally determined.

[0157] In an exemplary embodiment of this application, the process of determining the lane number based on relative position is illustrated below.

[0158] In an exemplary embodiment of this application, it is assumed that four cameras are installed on a one-way four-lane road, numbered A1, A2, A3, and A4 respectively, provided that the images captured by adjacent cameras overlap. The detection steps according to the above process include 1-5:

[0159] 1. Steps to create set 1: {A1}, set 2: {A2, A3, A4}.

[0160] 2. Compare all cameras in set 1 with all cameras in set 2 to determine if there are any overlapping areas. The comparison results are shown in Table 1:

[0161] Table 1

[0162]

[0163]

[0164] A1 and A2 have an overlapping area, and A1 is to the left of A2. A1 has no overlapping area with A3 and A4.

[0165] 3. Add A3 to set 1, and remove A3 from set 2, resulting in the following new set:

[0166] Set 1: {A1, A3}; Set 2: {A2, A4};

[0167] 4. Repeat step 2, comparing each camera in set 1 with each camera in set 2 to determine if there are any overlapping areas. The comparison results are shown in Table 2:

[0168] Table 2

[0169]

[0170] 5. Continue until the relative position of camera A1 is confirmed. As can be seen from step 4, the relative position of A1 is as follows:

[0171] The cameras are arranged from left to right as A1A2A3A4, which means that A1 is on the far left and that camera A1 is attached to either the first or fourth lane.

[0172] In an exemplary embodiment of this application, if it is known that the lane number corresponding to A1 is 1, and it is known that there are four lanes on the current road, the arrangement numbers of A1A2A3A4 can be determined to be 1, 2, 3, and 4 respectively based on the lane number 1 of A. The arrangement numbers of A2A3A4 increase sequentially relative to the arrangement number of A, and the lane numbers corresponding to A2A3A4 also increase sequentially to 2, 3, and 4 respectively.

[0173] In an exemplary embodiment of this application, similarly, if it is known that the lane number corresponding to A1 is 4, and it is known that there are four lanes on the current road, then the arrangement numbers of A1A2A3A4 can be determined to be 4, 3, 2, and 1 respectively based on the lane number 4 of A. The arrangement numbers of A2A3A4 decrease sequentially relative to the arrangement number of A, so the lane numbers corresponding to A2A3A4 also decrease sequentially to 3, 2, and 1 respectively.

[0174] In exemplary embodiments of this application, the solutions of this application embodiments include at least the following advantages:

[0175] 1. This solution addresses the problems of low efficiency, large errors, or high costs associated with existing methods for inputting lane numbers into road monitoring system cameras via server input.

[0176] 2. The method in this application embodiment requires no human intervention and does not require a third-party positioning system (such as a GPS positioning system), saving time and effort while maintaining high accuracy.

[0177] This application embodiment also provides a lane number detection device 1 corresponding to a camera, such as... Figure 9 As shown, it may include a processor 11 and a computer-readable storage medium 12, wherein the computer-readable storage medium 12 stores instructions that, when executed by the processor 11, implement the method for detecting the lane number corresponding to the camera.

[0178] In the exemplary embodiments of this application, any of the embodiments in the foregoing method embodiments can be applied to the device embodiments, and will not be described in detail here.

[0179] This application embodiment also provides a camera 2, such as Figure 10 As shown, it may include the lane number detection device 1 corresponding to the camera.

[0180] In the exemplary embodiments of this application, any of the embodiments in the foregoing method embodiments can be applied to the camera embodiment, and will not be described in detail here.

[0181] It will be understood by those skilled in the art that all or some of the steps, systems, or apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

Claims

1. A method for detecting lane numbers corresponding to cameras, characterized in that, The method includes: Acquire multiple cameras on the same road used to monitor different lanes and form an interactive group; For each pair of cameras in the interactive group, the overlapping area is calculated, and when it is found that the shooting ranges of any two cameras have an overlapping area, the relative position between the two cameras is calculated. The multiple cameras are sorted according to their relative positions within the interactive group, and the lane numbers corresponding to each of the multiple cameras are determined based on the sorting. The calculation of the overlap area for each pair of cameras within the interactive group includes:

31. Establish the set of comparison objects and the set of objects being compared; 32. Select any camera in the interaction group as a comparison object and put it into the comparison object set, and put all cameras in the interaction group other than the comparison object into the comparison object set as comparison objects; 33. Calculate the overlapping area between the comparison object and each comparison object in the set of comparison objects; wherein, when the calculation result shows that the shooting range of the comparison object and the comparison object overlaps, the comparison object and the comparison object are treated as any two cameras, and the relative position between the two cameras is calculated; when the calculation result shows that the shooting range of the comparison object and the comparison object does not overlap, the comparison object is deleted from the set of comparison objects, converted into a comparison object, and placed into the object set, and the overlapping area of ​​the comparison object is calculated with the next comparison object; 34. After the overlapping area calculation between the comparison object and each of the comparison objects in the set of comparison objects is completed, the next comparison object is obtained and the process returns to step 33 until all comparison objects in the set of comparison objects have been compared. The step of calculating the overlapping region between the comparison object and each comparison object in the set of comparison objects includes: for the currently being compared object and any comparison object, performing the following process: The comparison object initiates a comparison request to the comparison object, the comparison request including: the time period and time interval for capturing panoramic images; Acquire at least one first panoramic image of the comparison object captured according to the time interval within the time period; and acquire at least one second panoramic image of the comparison object captured according to the time interval within the time period; wherein the first panoramic image and the second panoramic image are captured at the same time within each time period; Detect whether there is an overlapping region between the first panoramic image and the second panoramic image; When there is an overlapping area between the first panoramic image and the second panoramic image, it is determined that the shooting range of the comparison object and the compared object overlaps. When the first panoramic image and the second panoramic image do not have an overlapping area, it is determined that the shooting range of the comparison object and the object being compared do not overlap.

2. The method for detecting lane numbers corresponding to cameras according to claim 1, characterized in that, The step of acquiring an interactive group composed of multiple cameras on the same road used for monitoring different lanes includes: performing the following process for each camera: Using the camera's built-in positioning system, it broadcasts its own location information via a local area network; and receives location information broadcast by other cameras within the local area network besides itself. Based on the received location information, determine one or more other cameras that are within a preset distance range from the camera itself, and form the interaction group with the one or more other cameras.

3. The method for detecting lane numbers corresponding to cameras according to claim 1, characterized in that, The step of detecting whether there is an overlapping region between the first panoramic image and the second panoramic image includes: Multiple first feature points are obtained from the first panoramic image, and feature point information of the multiple first feature points is obtained; The pixels in the second panoramic image are traversed to detect whether there is a second feature point in the second panoramic image that matches the feature point information of the first feature point. When a second feature point matching the feature point information of the first feature point is detected in the second panoramic image, it is determined that there is an overlapping area between the first panoramic image and the second panoramic image. When it is detected that there is no second feature point in the second panoramic image that matches the feature point information of the first feature point, it is determined that there is no overlapping area between the first panoramic image and the second panoramic image. or, Multiple second feature points are obtained from the second panoramic image, and feature point information of the multiple second feature points is obtained; The pixels in the first panoramic image are traversed to detect whether there is a first feature point in the first panoramic image that matches the feature point information of the second feature point. When a first feature point matching the feature point information of the second feature point is detected in the first panoramic image, it is determined that there is an overlapping area between the first panoramic image and the second panoramic image. When it is detected that there is no first feature point in the first panoramic image that matches the feature point information of the second feature point, it is determined that there is no overlapping area between the first panoramic image and the second panoramic image.

4. The method for detecting lane numbers corresponding to cameras according to claim 3, characterized in that, The step of obtaining multiple first feature points from the first panoramic image includes: Calculate the gradient of each pixel in the first panoramic image; The first panoramic image is divided into multiple first sub-region units, and the gradient histogram of each first sub-region unit is calculated to form the descriptor of the first sub-region unit. A first region block is formed by a preset number of first sub-region units, and the descriptors of the preset number of first sub-region units are concatenated to form the descriptor of the corresponding first region block. The descriptors of all the first region blocks are concatenated to form the descriptor of the first panoramic image. The center pixels of the first region blocks with the highest gradient values ​​when sorted from largest to smallest are obtained as the first feature points of the first panoramic image; and the feature point information of the multiple first feature points is recorded; the feature point information of the multiple first feature points includes: the gradient magnitude of the multiple first feature points and the relative position between the multiple first feature points; the relative position between the multiple first feature points includes the direction vector between the multiple first feature points; as well as, The step of obtaining multiple second feature points from the second panoramic image includes: Calculate the gradient of each pixel in the second panoramic image; The second panoramic image is divided into multiple second sub-region units, and the gradient histogram of each second sub-region unit is calculated to form the descriptor of the second sub-region unit. A second region block is formed by a preset number of second sub-region units, and the descriptors of the preset number of second sub-region units are concatenated to form the descriptor of the corresponding second region block. The descriptors of all the second region blocks are concatenated to form the descriptor of the second panoramic image. The center pixels of the second region blocks with the highest gradient values ​​when sorted from largest to smallest are obtained as the second feature points of the second panoramic image; and the feature point information of the multiple second feature points is recorded; the feature point information of the multiple second feature points includes: the gradient magnitude of the multiple second feature points and the relative position between the multiple second feature points; the relative position between the multiple second feature points includes the direction vector between the multiple second feature points.

5. The method for detecting lane numbers corresponding to cameras according to claim 4, characterized in that, The step of detecting whether there is a second feature point in the second panoramic image that matches the feature point information of the first feature point includes: The feature point information of the plurality of first feature points is compared with the feature point information of any plurality of second feature points traversed from the second panoramic image. When the gradient magnitudes of the plurality of first feature points are the same as the gradient magnitudes of the plurality of second feature points, and the relative positions between the plurality of first feature points are consistent with the relative positions between the plurality of second feature points, it is determined that the plurality of first feature points and the plurality of second feature points match; and it is determined that there is a second feature point in the second panoramic image that matches the feature point information of the first feature point; When the gradient magnitudes of the plurality of first feature points are not the same as the gradient magnitudes of the plurality of second feature points, and / or the relative positions between the plurality of first feature points are inconsistent with the relative positions between the plurality of second feature points, it is determined that the plurality of first feature points and the plurality of second feature points do not match; when the plurality of first feature points do not match any plurality of second feature points in the second panoramic image, it is determined that there are no second feature points in the second panoramic image that match the feature point information of the first feature points. as well as, The step of detecting whether there is a first feature point in the first panoramic image that matches the feature point information of the second feature point includes: The feature point information of the plurality of second feature points is compared with the feature point information of any plurality of first feature points traversed from the first panoramic image. When the gradient magnitudes of the plurality of second feature points are the same as the gradient magnitudes of the plurality of first feature points, and the relative positions between the plurality of second feature points are consistent with the relative positions between the plurality of first feature points, it is determined that the plurality of second feature points and the plurality of first feature points match; and it is determined that there is a first feature point in the first panoramic image that matches the feature point information of the second feature points; When the gradient magnitudes of the plurality of second feature points are not the same as the gradient magnitudes of the plurality of first feature points, and / or the relative positions between the plurality of second feature points are inconsistent with the relative positions between the plurality of first feature points, it is determined that the plurality of second feature points and the plurality of first feature points do not match; when the plurality of second feature points do not match any plurality of first feature points in the first panoramic image, it is determined that there is no first feature point in the first panoramic image that matches the feature point information of the second feature points.

6. The method for detecting lane numbers corresponding to cameras according to claim 5, characterized in that, The arbitrary two cameras include a first camera and a second camera; the calculation of the relative position between the arbitrary two cameras includes: The positions of the overlapping regions in the first panoramic image captured by the first camera and the second panoramic image captured by the second camera are detected, respectively. When the overlapping region is located on the first side of the first panoramic image and the overlapping region is located on the second side of the second panoramic image, it is determined that the first camera and the second camera are adjacent to each other on the second side. When the overlapping area is located on the second side of the first panoramic image and the overlapping area is located on the first side of the second panoramic image, it is determined that the second camera is adjacent to the second side of the first camera.

7. The method for detecting lane numbers corresponding to cameras according to claim 6, characterized in that, The detection of the position of the overlapping region in the first panoramic image captured by the first camera and the second panoramic image captured by the second camera includes: Calculate the first average coordinates of multiple first feature points that match multiple second feature points; detect the relative position of the first average coordinates with the center point coordinates or the central axis of the first panoramic image; when the first average coordinates are located on a first side of the center point coordinates of the first panoramic image, determine that the overlapping region is located on a first side of the first panoramic image; when the first average coordinates are located on a second side of the center point coordinates of the first panoramic image, determine that the overlapping region is located on a second side of the first panoramic image; and, Calculate the second average coordinates of multiple second feature points that match multiple first feature points; detect the relative position of the second average coordinates with the center point coordinates or the central axis of the second panoramic image; when the second average coordinates are located on the first side of the center point coordinates of the second panoramic image, determine that the overlapping area is located on the first side of the second panoramic image; when the second average coordinates are located on the second side of the center point coordinates of the second panoramic image, determine that the overlapping area is located on the second side of the second panoramic image.

8. A lane number detection device corresponding to a camera, characterized in that, The device includes a processor and a computer-readable storage medium storing instructions that, when executed by the processor, implement the camera-corresponding lane number detection method as described in any one of claims 1-7.

9. A camera, characterized in that, Includes the lane number detection device corresponding to the camera as described in claim 8.

Images