CN115035714A - Vehicle parking behavior determination method, electronic device, and storage medium - Google Patents
Vehicle parking behavior determination method, electronic device, and storage medium Download PDFInfo
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
Abstract
The application discloses a vehicle parking behavior determination method, electronic equipment and a computer-readable storage medium. The method comprises the following steps: judging whether a reference vehicle in a static state exists in the target parking area or not in a delay time period after the target vehicle is judged to enter the target parking area; and if the target parking area has the reference vehicles, judging whether the reference vehicles have the target vehicles or not so as to determine whether the target vehicles have parking behaviors or not. By the aid of the method, accuracy of the parking behavior determination result of the target vehicle can be improved.
Description
Technical Field
The present disclosure relates to the field of video monitoring, and in particular, to a method for determining a parking behavior of a vehicle, an electronic device, and a computer-readable storage medium.
Background
In the field of traffic monitoring, there are many application scenarios where a determination of a parking behavior of a vehicle is required, for example, in a calculation process of a number of parking spaces, a determination of whether a vehicle is in a parking space is required, and therefore a determination of whether a parking behavior of a parking space exists is required. For another example, in the calculation of the parking fee, it is necessary to determine when the vehicle starts to park in the parking space, and thus it is necessary to determine whether there is a parking behavior of the parking space. For another example, in the process of identifying an illegal parking behavior, it is necessary to determine whether the vehicle has a parking behavior in a parking prohibition area.
However, the accuracy of the determination result of the parking behavior obtained by the current vehicle parking behavior determination method is not high.
Disclosure of Invention
The application provides a vehicle parking behavior determination method, an electronic device and a computer readable storage medium, which can solve the problem that the accuracy of a determination result of a parking behavior obtained by the existing vehicle parking behavior determination method is not high.
In order to solve the technical problem, the application adopts a technical scheme that: a vehicle parking behavior determination method is provided. The method comprises the following steps: judging whether a reference vehicle in a static state exists in the target parking area or not in a delay time period after the target vehicle is judged to drive into the target parking area; and if the reference vehicles exist, judging whether the target vehicle exists in the reference vehicles or not so as to determine whether the target vehicle has parking behavior or not.
In order to solve the above technical problem, another technical solution adopted by the present application is: an electronic device is provided, which comprises a processor and a memory connected with the processor, wherein the memory stores program instructions; the processor is configured to execute the program instructions stored by the memory to implement the above-described method.
In order to solve the above technical problem, the present application adopts another technical solution: there is provided a computer readable storage medium storing program instructions that when executed are capable of implementing the above method.
By the method, whether the reference vehicle in the static state exists in the target parking area or not (whether the possibility that the target vehicle is stably parked exists or not is judged) is judged in the delay time period after the target vehicle enters the target parking area; if there are reference vehicles (there is a possibility that the target vehicle is stationary), it is determined whether there is a target vehicle in each of the reference vehicles (it is determined whether the target vehicle is actually stationary) to determine whether there is a parking behavior of the target vehicle. Therefore, according to the parking behavior determining method and device, the parking behavior of the target vehicle is not directly determined when the target vehicle enters the target parking area, the target vehicle is considered to possibly have the parking behavior, whether the target vehicle is parked stably is further determined on the basis, and whether the target vehicle has the parking behavior is determined on the basis of whether the target vehicle is parked stably, so that the possibility that the parking behavior of the target vehicle is misjudged can be reduced, and the accuracy of the parking behavior determining result of the target vehicle is improved.
Drawings
FIG. 1 is a schematic flow chart diagram illustrating an embodiment of a vehicle parking behavior determination method of the present application;
FIG. 2 is a schematic flow chart diagram illustrating another embodiment of a vehicle parking behavior determination method of the present application;
FIG. 3 is a schematic diagram of the detailed process of S21 in FIG. 2;
FIG. 4 is a schematic flow chart diagram illustrating a method for determining vehicle parking behavior according to another embodiment of the present application;
FIG. 5 is a schematic flow chart diagram illustrating a further embodiment of a vehicle parking behavior determination method according to the present application;
FIG. 6 is a schematic view of the detailed process of S43 in FIG. 5;
FIG. 7 is a schematic diagram of the relationship between the reference point and the target parking area at each time under the image coordinate system XOY;
FIG. 8 is a schematic structural diagram of an embodiment of the behavior determination device of the present application;
FIG. 9 is a schematic structural diagram of an embodiment of an electronic device of the present application;
FIG. 10 is a schematic structural diagram of an embodiment of a computer-readable storage medium of the present application;
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first", "second" and "third" in this application are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any indication of the number of technical features indicated. Thus, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of the feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless explicitly specified otherwise.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those skilled in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments without conflict.
The following describes in detail application scenarios of the method of the present application in the form of several examples:
application scenario 1: and calculating the parking fee. Judging whether the vehicle has parking behaviors in a parking area or not; if the parking behavior of the parking area is judged to exist, recording the driving information (the time of driving into the parking area, the license plate number of the vehicle and the ID of the parking area) of the vehicle; and recording the exit information (time of exiting the parking area, license plate number of the vehicle, ID of the parking area) of the vehicle when subsequently judging that the vehicle exits the parking area; determining an entrance time and an exit time of the vehicle based on the license plate number of the vehicle; calculating a time for the vehicle to occupy the parking area based on the entrance time and the exit time of the vehicle; the parking fee of the vehicle is calculated based on the time taken to occupy the parking area and the charging criteria.
Application scenario 2: and calculating the remaining parking spaces. Judging whether the vehicle has parking behaviors in a parking area or not; if the parking behavior of the parking area is judged to exist, recording the driving information of the vehicle (the time of driving into the parking area, the license plate number of the vehicle and the change of the parking area); the number of parking spaces in the parking area is reduced by one.
Application scenario 3: and (5) judging illegal parking behaviors. Judging whether the vehicle has parking behaviors in a parking forbidding area or not; and if the parking behaviors of the parking forbidding areas exist, recording the license plate number of the vehicle and reporting the illegal parking event.
The following describes a method for determining a parking behavior of a vehicle in the related art and the drawbacks thereof:
in the related art, a target vehicle is tracked to obtain track information of the target vehicle, and whether the relation between the position of the target vehicle at the latest moment in the track information of the target vehicle and a target parking area meets the requirement or not is judged; if the requirement is met, judging that the target vehicle enters a parking area; and if the target vehicle is judged to enter the parking area, judging that the parking behavior of the target vehicle exists.
The inventor of the application finds that the vehicle parking behavior judgment result is wrong due to the fact that the position of the target vehicle may be inaccurate. The reasons for the inaccuracy of the position of the target vehicle include at least the following two:
reason 1: the target vehicle is a passing vehicle, namely the target vehicle passes through the target parking area only and does not stay in the target parking area, but passes through the target parking area, so that the relation between the position of the target vehicle and the target parking area meets the requirement, the target vehicle is judged to enter the parking area, and then the target vehicle is judged to have the parking behavior of the target parking area. In this case, the target vehicle does not actually have a parking behavior, but is determined to have a parking behavior.
Reason 2: the target vehicle is shielded to cause the phenomenon of the target vehicle string ID, namely, the shielded vehicle ID of the target vehicle is mistaken for the ID of the target vehicle, so that the shielded vehicle enters the target parking area, the target vehicle is judged to enter the target parking area, and then the parking behavior of the target vehicle in the target parking area is judged. In this case, the target vehicle does not actually have a parking behavior, but is determined to have a parking behavior.
Based on this, the vehicle parking behavior determination method provided by the present application may be divided into two parts, one part is to determine whether the target vehicle enters the target parking area, and the other part is to determine whether there is a parking behavior for the target vehicle for a delay period after determining that the target vehicle enters the target parking area. Specifically, the following may be mentioned:
fig. 1 is a schematic flowchart of an embodiment of a vehicle parking behavior determination method according to the present application. It should be noted that, if the result is substantially the same, the flow sequence shown in fig. 1 is not limited in this embodiment. As shown in fig. 1, the present embodiment may include:
s11: first video data of a target area is acquired.
The target area includes a target parking area and its surrounding area.
The target area is provided with a camera, and the visual field range of the camera is the target area. The target parking area may be a parking-permitted area such as a parking space of a parking lot, a parking space on the roadside, or the like, or a parking-prohibited area such as a road zebra crossing, an expressway, or the like. The first video data comprises a plurality of video frames, and each video frame corresponds to a moment.
S12: and tracking the vehicles based on the first video data to obtain track information of a plurality of vehicles in the first video data.
The track information of the vehicle may include relevant position information of the vehicle at several moments, the relevant position information of the vehicle at a single moment may include an ID of the vehicle, a position of the vehicle, a type of the vehicle, license plate information of the vehicle, a video frame number of the vehicle, and the like, and the license plate information of the vehicle may include a license plate number, a license plate position, a license plate color, a license plate appearance, and the like. The trajectory information of the vehicle may include a plurality of sub-trajectory information, such as license plate sub-trajectory information (hereinafter referred to as first license plate sub-trajectory information) composed of license plate information, vehicle sub-trajectory information composed of the position of the vehicle, and the like.
The vehicle tracking related to the application can comprise three parts of vehicle position detection, vehicle position correlation and vehicle license plate information acquisition. For each video frame in the first video data, carrying out vehicle position detection on the video frame to obtain the position of each vehicle to be associated in the video frame; matching the position of each vehicle to be associated with the track information of each existing vehicle; if the position of the vehicle to be associated is matched with the track information of the existing vehicle, updating the track information of the existing vehicle matched with the position of the vehicle to be associated by using the position of the vehicle to be associated; if not, establishing the track information of a new vehicle based on the position of the vehicle to be associated. The license plate detection can be carried out on the region corresponding to the position of the license plate in each video frame, and the license plate information of the vehicle is obtained.
S13: and taking at least one vehicle in the first video data as a target vehicle, and judging whether the target vehicle enters the target parking area or not based on the relationship between the position of the target vehicle at the latest moment in the track information of the target vehicle and the target parking area.
The contact ratio between the position of the target vehicle at the latest moment and the target parking area can be calculated, and whether the target vehicle enters the target parking area or not can be judged based on the contact ratio. Setting a coincidence degree threshold, and if the coincidence degree is greater than the coincidence degree threshold, judging that the target vehicle enters a target parking area; otherwise, the target vehicle is judged not to drive into the target parking area.
If the target vehicle enters the target parking area, the target vehicle is possibly parked; if the target vehicle does not enter the target parking area, it means that there is no parking behavior for the target vehicle.
Further, it may be determined whether there is a parking behavior of the target vehicle after it is determined that the target vehicle enters the target parking area, that is, on the basis of the determination that there is a possibility of a parking behavior of the target vehicle. Specifically, the following may be mentioned:
fig. 2 is a schematic flow chart of another embodiment of the vehicle parking behavior determination method according to the present application. It should be noted that, if the result is substantially the same, the flow sequence shown in fig. 2 is not limited in this embodiment. As shown in fig. 2, the present embodiment may include:
s21: and determining whether the reference vehicle in the stationary state exists in the target parking area or not in a delay time period after the target vehicle is determined to enter the target parking area.
The time period during which the target vehicle enters the target parking area is referred to as an original time period, and the continuous time period of a preset duration after the original time period is referred to as a delay time period. The time period during which the target vehicle enters the target parking area may include a time period before and during which the target vehicle enters the target parking area, that is, a time period starting from a time point at which the target vehicle enters the field of view of the camera (a time point corresponding to the first video frame included in the first video data) and ending with a time point at which a relationship between the position of the target vehicle and the target parking area satisfies a requirement.
The delay period after the determination in S21 that the target vehicle has entered the target parking area may be, but is not limited to, achieved by S11 to S13.
Referring collectively to fig. 3, in some embodiments, S21 may include the sub-steps of:
s211: second video data of the target area is acquired for a delay period after it is determined that the target vehicle enters the target parking area.
S212: and tracking the license plate based on the second video data to obtain a plurality of second license plate sub-track information in the second video data.
The composition and the obtaining manner of the second license plate track information and the first license plate track information are similar, and are not described herein again.
S213: and determining whether reference vehicles exist in the target parking area or not based on the relation between the license plate positions at different moments in the second license plate track information.
For each second license plate track information, whether the vehicle to which the second license plate track information belongs is a reference vehicle can be determined based on the relation between license plate positions at different moments; and determining that the reference vehicle exists in each vehicle under the condition that the vehicle to which the at least one second license plate track information belongs is the reference vehicle. If the license plate positions at different moments in the second license plate trajectory information do not change or the change range is not large, the vehicle to which the second license plate trajectory information belongs is judged to be in a static state and is taken as a reference vehicle. The license plate positions at different moments are not changed, which means that the displacement between the license plate positions at different moments is 0; the variation range between the license plate positions at different moments is small, which means that the displacement between the license plate positions at different moments is smaller than a displacement threshold value. The displacement between the license plate positions at different moments can be calculated by any reference point of the license plate positions, such as a central point and a vertex.
If the reference vehicle exists in the target parking area, executing S22; otherwise, S23 is executed.
S22: and judging whether the target vehicle exists in the reference vehicles or not to determine whether the target vehicle has parking behavior or not.
In some embodiments, it may be determined whether a target vehicle is present in the reference vehicles based on the second license plate sub-trajectory information. S22 may include the following sub-steps: the second license plate sub-track information comprises a license plate number, and whether second license plate sub-track information meeting the requirement exists or not can be judged based on the license plate number, and the license plate number included in the second license plate sub-track information meeting the requirement is consistent with the target license plate number of the target vehicle; if the target vehicle exists, the target vehicle exists in the reference vehicles, namely the reference vehicle to which the second license plate track information meeting the requirements belongs is determined to be the target vehicle; if not, it is determined that the target vehicle does not exist in the reference vehicles.
The license plate number of the target vehicle can be determined from the first license plate track information of the target vehicle. It is understood that the license plate information of at least one time in the first license plate trajectory information of the target vehicle includes a license plate number. Due to the fact that the license plate of the target vehicle in some video frames is possibly shielded, the license plate information of the target vehicle at the corresponding moment is empty. Therefore, the license plate number of the target license plate can be the license plate number in the license plate information at any time.
For example, if a reference vehicle PP exists in the target parking area in a delay time period after the target vehicle is determined to enter the target parking area, that is, the number of PPs is not 0, the license plate numbers of each PP and the target vehicle P are compared, and if the license plate number of the PP is consistent with the license plate number of P, it is determined that P exists in PP; otherwise, judging that no P exists in the PP.
Further, whether or not there is a parking behavior of the target vehicle may be determined based on the determination result of whether or not there is the target vehicle in the respective reference vehicles.
It is understood that if the target vehicle has a behavior of the target parking area, the target vehicle may be stationary or approach stationary in the target parking area. The reference vehicles are in a stationary state for a delay period, and the presence of the target vehicle in each of the reference vehicles means that the target vehicle is stationary or approaching stationary in the target parking area. Therefore, if the judgment result shows that the target vehicle exists in the reference vehicles, the target vehicle is determined to have parking behavior; and if the judgment result is that the target vehicle does not exist in the reference vehicles, determining that the target vehicle does not have the parking behavior.
S23: and determining whether the target vehicle has no parking behavior or not based on the license plate track information of the target vehicle.
It is understood that, during the delay period, the target parking area does not have the reference vehicle in a stationary state, meaning that the target vehicle is not parked stably in the target parking area, so that it can be directly determined that there is no parking behavior of the target vehicle.
Further, in the case where the target parking area is not present in the reference vehicle, if it is directly determined that the target vehicle is not present in the parking behavior, there may be a case where a misjudgment is made. Therefore, whether the target vehicle has parking behavior or not can be further determined according to the license plate track information of the target vehicle. The license plate track information of the target vehicle comprises license plate positions of the target vehicle at multiple moments in an original time period and a delayed time period, wherein the original time period is a time period before and during the process that the target vehicle drives into the target parking area.
By implementing the embodiment, the method and the device for determining the parking area of the vehicle determine whether the reference vehicle in the static state exists in the target parking area (determine whether the possibility that the target vehicle is parked stably exists) in the delay time period after the target vehicle enters the target parking area; if there are reference vehicles (there is a possibility that the target vehicle is stationary), it is determined whether there is a target vehicle in each of the reference vehicles (it is determined whether the target vehicle is actually stationary) to determine whether there is a parking behavior of the target vehicle. Therefore, according to the parking behavior determining method and device, the parking behavior of the target vehicle is not directly determined when the target vehicle enters the target parking area, the target vehicle is considered to possibly have the parking behavior, whether the target vehicle is parked stably is further determined on the basis, and whether the target vehicle has the parking behavior is determined on the basis of whether the target vehicle is parked stably, so that the possibility that the parking behavior of the target vehicle is misjudged can be reduced, and the accuracy of the parking behavior determining result of the target vehicle is improved.
Fig. 4 is a flowchart illustrating a vehicle parking behavior determination method according to another embodiment of the present application. It should be noted that, if the result is substantially the same, the flow sequence shown in fig. 4 is not limited in this embodiment. As shown in fig. 4, the present embodiment may include:
s31: and acquiring second video data of the target area in a delay time period after the target vehicle is judged to enter the target parking area.
S32: and tracking the license plate based on the second video data to obtain second license plate sub-track information of the target vehicle.
And the license plate tracking can obtain a plurality of second license plate sub-track information in the second video data, and the second license plate sub-track information with the license plate number consistent with the target license plate number of the target vehicle is used as the second license plate sub-track information of the target vehicle.
S33: and combining the first license plate track information of the target vehicle and the second license plate track information of the target vehicle to obtain license plate track information of the target vehicle.
S31 to S33 and S211 to S213 may be in parallel, or S31 to S33 may be performed after S211 to S213, that is, in the case where it is determined through S211 to S213 that there is no reference vehicle, S31 to S33 are performed.
The parallel case of S31-S33 and S211-S213 is explained as follows as an example:
1) and acquiring second video data of the target area in a delay time period after the target vehicle is judged to enter the target parking area.
2) Tracking the license plate based on the second video data to obtain a plurality of second license plate sub-track information in the second video data; determining second license plate sub-track information of the target vehicle from the second license plate sub-track information; and combining the first license plate sub-track information of the target vehicle and the second license plate sub-track information of the target vehicle to obtain license plate track information of the target vehicle.
3) And determining whether reference vehicles exist in the target parking area or not based on the relation between the license plate positions at different moments in the second license plate trajectory information.
Further, in the step S23, when it is determined whether the parking behavior exists in the target vehicle based on the license plate trajectory information of the target vehicle, the misjudgment filtering coefficient of the parking behavior may be obtained based on reference points (center points, vertexes, and the like) of license plate positions at multiple times in the license plate trajectory information; judging whether the misjudgment filtering coefficient meets the coefficient condition or not; if the coefficient condition is met, judging that the target vehicle has a parking behavior; otherwise, judging that the target vehicle has no parking behavior.
The misjudgment filtering coefficient can be obtained at least in the following ways:
the first method is as follows: judging whether the reference points meet misjudgment filtering conditions or not, wherein the misjudgment filtering conditions comprise that the number of the reference points is larger than a number threshold value, and the reference points at specific moments in a plurality of moments are outside a target parking area, and the specific moments at least comprise starting moments and ending moments; if the misjudgment filtering condition is not met, determining the misjudgment filtering coefficient as a preset coefficient value, wherein the preset coefficient value meets the coefficient condition; and if the misjudgment filtering condition is met, determining the misjudgment filtering coefficient as other coefficient values, wherein the other coefficient values do not meet the coefficient condition. Accordingly, the coefficient condition is to misjudge the filter coefficient as a preset coefficient value.
The second method comprises the following steps: and acquiring a misjudgment filtering coefficient based on the distance between the reference points at different moments.
In some embodiments, a distance section, which is a fluctuation section of a sum S of distances of reference points at every adjacent two times among the plurality of times in a case where the vehicle has the parking behavior of the target parking area, may be set in advance based on the parking behavior of the target parking area. A distance range is adapted to all vehicle types, or a distance range is adapted to only one vehicle type, i.e., a distance range is set for each vehicle type. The misjudgment filter coefficient may be a deviation degree of a sum of distances of the reference points at every two adjacent time instants in the plurality of time instants with respect to the distance section. Accordingly, the coefficient condition is that the misjudgment filter coefficient is less than the deviation degree threshold.
In some embodiments, the misjudgment filtering coefficient may be C/S, where C is the arc length of the target arc, and S is the sum of the distances between the reference points at each two adjacent time instants. The target arc is an arc having the reference point at the start time and the reference point at the end time as end points, respectively. Alternatively, the false positive filter coefficient may be ln (C/S). The specific manner of acquiring the C/S can be described with reference to the following embodiments. Accordingly, the coefficient condition may be that the false positive filter coefficient is less than or equal to the coefficient threshold. When the misjudgment filter coefficient is C/S, the coefficient threshold may be 1, or may be a floating value around 1 (with a certain degree of fault tolerance). When the misjudgment filter coefficient is ln (C/S), the coefficient threshold value may be 0 or may be a floating value around 0 (with a certain degree of error tolerance).
The third method comprises the following steps: the misjudgment filtering coefficient can be obtained in a mode of combining the first mode and the second mode. Namely judging whether the reference point meets the misjudgment filtering condition or not; if the misjudgment filtering condition is met, determining the misjudgment filtering coefficient as a preset coefficient value; and if the misjudgment filtering condition is not met, acquiring a misjudgment filtering coefficient based on the distance between the reference points at different moments in the multiple moments.
The following detailed description mode three:
fig. 5 is a flowchart illustrating a vehicle parking behavior determination method according to still another embodiment of the present application. It should be noted that, if the result is substantially the same, the flow sequence shown in fig. 5 is not limited in this embodiment. The present embodiment is a further extension of S23. As shown in fig. 5, the present embodiment may include:
s41: and judging whether the reference point meets the misjudgment filtering condition or not.
The misjudgment filtering condition includes that the number of the reference points is larger than a number threshold, and the reference point at a specific time among the plurality of times is outside the target parking area, and the specific time includes at least a start time and an end time.
The erroneous judgment filter condition is a condition that can effectively judge whether or not the target vehicle has a parking behavior by the erroneous judgment filter coefficient. The number of the reference points is larger than a number threshold value and represents that the data quantity is enough; the reference point at the specific time is outside the target parking area, and represents that the target vehicle is directly judged to have no parking behavior under the condition that no reference vehicle exists in the target parking area, so that the possibility of misjudgment exists.
In some embodiments, the number threshold may be 3, 4, etc. The particular time may also include a time prior to the end time, two times prior, and so on. Therefore, the accuracy of the determination result of whether the erroneous determination filtering condition is satisfied can be improved.
If the misjudgment filtering condition is not met, executing S42 and S44; if the misjudgment filtering condition is satisfied, executing S43-S44.
S42: and determining the misjudgment filter coefficient as a preset coefficient value.
The preset coefficient value satisfies a coefficient condition.
S43: and acquiring a misjudgment filtering coefficient based on the distance between the reference points at different moments.
Referring to fig. 6 in combination, in case that the misjudgment filter coefficient is C/S or ln (C/S), S43 may include the following sub-steps:
s431: the sum of the distances of the reference points at each adjacent two of the plurality of time instants is obtained.
S432: and acquiring the arc length of the target arc.
The target arc is an arc having the reference point at the start time and the reference point at the end time as end points, respectively.
In some embodiments, a translation distance between the reference point at the start time and the reference point at the end time, and a straight-line distance (also called chord length) between the reference point at the start time and the reference point at the end time may be obtained; judging whether the translation distance meets a distance condition; if the distance condition is not met, acquiring the chord height of the target arc based on the horizontal distance; if the distance condition is met, acquiring the chord height of the target arc based on the linear distance; and determining the arc length of the target arc based on the linear distance and the chord height.
In the image coordinate system, the reference point has a horizontal coordinate in the horizontal direction and a vertical coordinate in the vertical direction, and the translation distance between the reference point at the start time and the reference point at the end time may be a distance between the coordinates in the horizontal direction or the vertical direction.
The distance condition may be a translation distance of 0, or a fluctuation value around 0 (allowing some tolerance), or the like. If the distance condition is not satisfied, the chord height may be equal to the translation distance. Alternatively, the chord height may be a preset multiple of the translation distance. If the distance condition is not satisfied, the chord height may be one half, two thirds, etc. of the linear distance.
S433: and obtaining a misjudgment filtering coefficient based on the ratio of the arc length to the sum.
S44: and judging whether the misjudgment filtering coefficient meets the coefficient condition or not.
If the coefficient condition is satisfied, go to S45; if the coefficient condition is not satisfied, S46 is executed.
S45: and determining that the target vehicle has parking behavior.
S46: it is determined that the target vehicle does not have a parking behavior.
Different from the case that no reference license plate exists in the foregoing embodiment, the present embodiment directly determines that no parking behavior exists in the target vehicle, and can determine whether a parking behavior exists in the target vehicle through the reference point of the license plate position of the target vehicle in the case that no reference vehicle exists in the target parking area, further reduce the possibility that the parking behavior of the target vehicle is misjudged (that is, the parking behavior actually exists but the parking behavior is determined not to exist), and improve the accuracy of the parking behavior determination result of the target vehicle.
S41 to S46 are explained below in an exemplary form with reference to fig. 7:
recording license plate track information { p) in track information of target vehicle 1 ，p 2 ，p 3 …，p n }，p i (x i ,y i )，i＝1，…，n。x i And y i And coordinates of a reference point of the license plate position at the ith moment in the horizontal direction and the vertical direction of the image coordinate system are respectively expressed. With target parking area on one side of the laneThe parking space is parallel to the lane.
1) Judging whether a misjudgment filtering condition is met, wherein the misjudgment filtering condition is that n is more than or equal to 3 and p 1 、p n-1 、p n Outside the parking space; if the misjudgment filtering condition is met, entering 2) -4); otherwise, setting the misjudgment filtering coefficient alpha to be 0 and entering 5).
2) The sum of the distances of the reference points at each two adjacent time instants S:
3) calculating the arc length C of the target arc between P1 and Pn:
calculating p 1 And p n Distance therebetween, as chord length l of the target arc between P1 and Pn:
computing the chord height h of the target arc between P1 and Pn:
calculating the arc length C of the target arc between P1 and Pn based on h and l:
4) calculating a misjudgment filtering coefficient alpha based on S and C:
5) judging whether alpha is less than or equal to 0 or alpha is greater than 0; if alpha is less than or equal to 0, executing 6); if α >0, then 7) is performed.
6) And judging that the target vehicle has parking behaviors of parking spaces.
7) And judging that the target vehicle does not have parking behavior of a parking space.
Referring to fig. 7, fig. 7 is a schematic diagram illustrating a relationship between a reference point and a target parking area at each time point in the image coordinate system XOY. Fig. 7 (a) is a schematic diagram of the relationship between parking spaces and lanes; (b) a schematic diagram for calculating a misjudgment filter coefficient; (c) the parking space information is a relation schematic diagram of a reference point and a target parking area at each moment under the condition that parking behaviors of parking spaces do not exist; (d) the parking space is a schematic relation diagram of the reference point and the target parking area at each moment under the condition that parking behaviors of parking spaces exist.
Fig. 8 is a schematic structural diagram of an embodiment of the behavior determination device according to the present application. As shown in fig. 8, the behavior determination device may include a first judgment module 11 and a second judgment module 12.
The first determination module 11 may be configured to determine whether there is a reference vehicle in a stationary state in the target parking area for a delay time period after determining that the target vehicle enters the target parking area.
The second judging module 12 may be configured to judge whether the target vehicle exists in each reference vehicle in the case that the reference vehicle exists in the target parking area, so as to determine whether the target vehicle has parking behavior.
For further details of this embodiment, please refer to the previous method embodiment, which is not repeated herein.
By implementing the embodiment, the application judges whether the reference vehicle in a static state exists in the target parking area (judges whether the possibility of the target vehicle stopping stably exists) by utilizing the first judging module in the delay time period after the target vehicle enters the target parking area; in the case where there are reference vehicles (there is a possibility that the target vehicle is stationary), it is determined whether there is a target vehicle in each of the reference vehicles (it is determined whether the target vehicle is actually stationary) using a second determination module to determine whether there is a parking behavior of the target vehicle. Therefore, according to the parking behavior determining method and device, the parking behavior of the target vehicle is not directly determined when the target vehicle enters the target parking area, the target vehicle is considered to possibly have the parking behavior, whether the target vehicle is parked stably is further determined on the basis, and whether the target vehicle has the parking behavior is determined on the basis of whether the target vehicle is parked stably, so that the possibility that the parking behavior of the target vehicle is misjudged can be reduced, and the accuracy of the parking behavior determining result of the target vehicle is improved.
Fig. 9 is a schematic structural diagram of an embodiment of the electronic device of the present application. As shown in fig. 9, the electronic device includes a processor 21, and a memory 22 coupled to the processor 21.
Wherein the memory 22 stores program instructions for implementing the method of any of the above embodiments; processor 21 is operative to execute program instructions stored by memory 22 to implement the steps of the above-described method embodiments. The processor 21 may also be referred to as a CPU (Central Processing Unit). The processor 21 may be an integrated circuit chip having signal processing capabilities. The processor 21 may also be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The electronic device may be a camera, a server that establishes a communication connection with the camera, or a behavior determination terminal that establishes a communication connection with the camera. The camera may be configured to obtain video data of the target area, and the camera/server/behavior determination terminal may be configured to analyze the video data to determine a parking behavior of the target vehicle in the video data. For a specific parking behavior determination method, please refer to the foregoing method embodiments, which are not described herein again.
FIG. 10 is a schematic structural diagram of an embodiment of a computer-readable storage medium of the present application. As shown in fig. 10, the computer readable storage medium 30 of the embodiment of the present application stores program instructions 31, and when executed, the program instructions 31 implement the method provided by the above-mentioned embodiment of the present application. The program instructions 31 may form a program file stored in the computer-readable storage medium 30 in the form of a software product, so that a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) executes all or part of the steps of the method according to the embodiments of the present application. And the aforementioned computer-readable storage medium 30 includes: various media capable of storing program codes, such as a usb disk, a mobile hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, or terminal devices, such as a computer, a server, a mobile phone, and a tablet.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is only a logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. The above are only embodiments of the present application, and not intended to limit the scope of the present application, and all equivalent structures or equivalent processes performed by the present application and the contents of the attached drawings, which are directly or indirectly applied to other related technical fields, are also included in the scope of the present application.
Claims (12)
1. A vehicle parking behavior determination method, characterized by comprising:
determining whether a reference vehicle in a stationary state exists in a target parking area within a delay time period after it is determined that a target vehicle enters the target parking area;
if the reference vehicles exist in the target parking area, judging whether the target vehicles exist in the reference vehicles or not so as to determine whether parking behaviors exist in the target vehicles or not.
2. The method according to claim 1, wherein after the determining whether the reference vehicle in a stationary state exists in the target parking area, the method further comprises:
if the reference vehicle in the static state does not exist in the target parking area, judging whether the target vehicle has a parking behavior or not based on the license plate track information of the target vehicle;
the license plate track information of the target vehicle comprises license plate positions of the target vehicle at multiple moments in an original time period and the delay time period, wherein the original time period is a time period before and during the process that the target vehicle drives into the target parking area.
3. The method of claim 2, wherein the determining whether parking behavior exists in the target vehicle based on the license plate track information of the target vehicle comprises:
acquiring misjudgment filter coefficients of parking behaviors based on the reference points of the license plate positions at the multiple moments;
if the coefficient condition is met, judging that the target vehicle has a parking behavior;
and if the coefficient condition is not met, judging that the target vehicle has no parking behavior.
4. The method of claim 3, wherein the obtaining of the misjudgment filtering coefficient of the parking behavior based on the reference points of the license plate positions at the plurality of moments comprises:
judging whether the reference points meet misjudgment filtering conditions or not, wherein the misjudgment filtering conditions comprise that the number of the reference points is larger than a number threshold, and the reference point at a specific moment in the multiple moments is outside the target parking area, and the specific moment at least comprises a starting moment and an ending moment;
if the misjudgment filtering condition is not met, determining the misjudgment filtering coefficient as a preset coefficient value, wherein the preset coefficient value meets the coefficient condition;
and if the misjudgment filtering condition is met, acquiring the misjudgment filtering coefficient based on the distance between the reference points at different moments in the multiple moments.
5. The method according to claim 4, wherein the obtaining the false positive filter coefficient based on the distance between the reference points at different time instants comprises:
acquiring the sum of the distances between the reference points of every two adjacent moments in the multiple moments;
acquiring the arc length of a target arc, wherein the target arc takes the reference point of the starting moment and the reference point of the ending moment as end points respectively;
and obtaining the misjudgment filtering coefficient based on the ratio of the arc length to the sum.
6. The method of claim 5, wherein the obtaining the arc length of the target arc comprises:
acquiring a translation distance between the reference point at the starting moment and the reference point at the ending moment, and a linear distance between the reference point at the starting moment and the reference point at the ending moment;
judging whether the translation distance meets a distance condition;
if the distance condition is not met, acquiring the chord height of the target circular arc based on the translation distance; if the distance condition is met, acquiring the chord height of the target circular arc based on the linear distance;
and determining the arc length of the target circular arc based on the linear distance and the chord height.
7. The method according to claim 1, wherein the step of determining that the target vehicle enters the target parking area includes:
acquiring first video data of a target area, wherein the target area comprises the target parking area and a surrounding area thereof;
tracking vehicles based on the first video data to obtain track information of a plurality of vehicles in the first video data;
and taking at least one vehicle in the first video data as the target vehicle, and judging whether the target vehicle enters the target parking area or not based on the relation between the position of the target vehicle at the latest moment in the track information of the target vehicle and the target parking area.
8. The method of claim 7, wherein the trajectory information of the target vehicle comprises first license plate trajectory information of the target vehicle, the method further comprising:
acquiring second video data of the target area within a delay time period after the target vehicle is judged to drive into the target parking area;
tracking a license plate based on the second video data to obtain second license plate sub-track information of the target vehicle;
and combining the first license plate track information of the target vehicle and the second license plate track information of the target vehicle to obtain license plate track information of the target vehicle.
9. The method of claim 1, wherein the determining whether the target parking area has the reference vehicle in a stationary state comprises:
acquiring second video data of a target area in a delay time period after the target vehicle is judged to drive into the target parking area, wherein the target area comprises the target parking area and a surrounding area thereof;
tracking a license plate based on the second video data to obtain a plurality of second license plate sub-track information in the second video data;
and determining whether the reference vehicle exists in the target parking area or not based on the relation between the license plate positions at different moments in the second license plate trajectory information.
10. The method of claim 9, wherein the second license plate sub-track information includes a license plate number, and the determining whether the target vehicle is present in each of the reference vehicles comprises:
judging whether second license plate sub-track information meeting the requirements exists or not, wherein license plate numbers included in the second license plate sub-track information meeting the requirements are consistent with target license plate numbers of the target vehicles;
and if so, determining that the target vehicle exists in the reference vehicles.
11. An electronic device comprising a processor, a memory coupled to the processor, wherein,
the memory stores program instructions;
the processor is to execute the program instructions stored by the memory to implement the method of any of claims 1-10.
12. A computer-readable storage medium, characterized in that it stores program instructions executable by a processor, which when executed, implement the method of any one of claims 1-10.
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