A method and device for identifying the flow of people entering and leaving a scenic spot

Abstract

The present application discloses a method and device for identifying the flow of people entering and leaving a scenic spot. The method comprises the following steps: obtaining the location of the entrance and exit of a target scenic spot, setting an inner detection area and an outer detection area at the entrance and exit of the scenic spot; determining the first movement trajectory of tourists located in the inner detection area within a first preset time period in the inner detection area; based on the first movement trajectory, counting the target number of people entering the target scenic spot within the first preset time period; determining the second movement trajectory of each tourist located in the outer detection area within the outer detection area within the first preset time period; based on the second movement trajectory, counting the target number of people leaving the target scenic spot within the first preset time period; and determining the flow of people entering and leaving the target scenic spot in the first preset time period based on the target number of people entering and the target number of people leaving. The scheme can accurately determine the flow of tourists in the target scenic spot within a certain time period, and can help scenic spot managers optimize and change the management mode or system of the scenic spot.

Description

Technical Field

[0001] The present application relates to the technical field of identifying the flow of people entering and leaving a scenic area, and in particular to a method and device for identifying the flow of people entering and leaving a scenic area. Background Art

[0002] With the continuous development of the tourism industry, managers of the tourism industry often hope to accurately grasp the flow of people in and out of scenic spots, the changes and trends in the flow of people in and out, etc., so as to use it as a basis for further planning of the scenic spots. Therefore, accurate statistics on the number of people entering and leaving the scenic spots are very important.

[0003] The existing method of determining the number of people entering a scenic spot is to determine it by counting the number of tickets sold in the scenic spot, and the number of people leaving the scenic spot is determined by the number of people counters set up at the entrance and exit of the scenic spot. However, using the number of tickets sold or the number of people counters as the basis for determining the number of people is very inaccurate. For example, some tourists are unable to come due to temporary matters. Regardless of whether the tourists actually enter the scenic spot for fun or leave immediately after entering, they will be counted in the number of people entering the scenic spot. Therefore, if the flow of people in and out of the scenic spot within a certain period of time, changes or trends, etc. are to be determined based on inaccurate numbers of tourists entering and leaving the scenic spot, it will cause large errors, which is not conducive to further planning of the scenic spot. Summary of the invention

[0004] In view of this, the present application provides a method and device for identifying the flow of people entering and leaving a scenic spot, which is used to solve the problem that if the flow of people entering and leaving a scenic spot within a certain period of time, changes or trends, etc. are determined based on inaccurate numbers of tourists entering and leaving, it will cause large errors and be unfavorable for further planning of the scenic spot.

[0005] To achieve the above objectives, the proposed solution is as follows:

[0006] In a first aspect, a method for identifying the flow of people entering and leaving a scenic spot includes:

[0007] Obtain the location of the entrance and exit of the target scenic spot, and set an inner detection area and an outer detection area on the inner side and the outer side of the entrance and exit of the scenic spot respectively according to the location;

[0008] Determine a first movement trajectory of each visitor located in the inner detection area within the inner detection area within a first preset time period;

[0009] Based on the first movement trajectory, counting the number of target people entering the target scenic spot within the first preset time period;

[0010] Determine a second movement trajectory of each visitor located in the outer detection area within the outer detection area within the first preset time period;

[0011] Based on the second movement trajectory, counting the number of people who leave the target scenic spot within the first preset time period;

[0012] The flow of people entering and leaving the target scenic spot in the first preset time period is determined based on the target number of people entering and the target number of people leaving.

[0013] Preferably, counting the number of target persons entering the target scenic spot within the first preset time period based on the first movement trajectory includes:

[0014] Determine whether the starting point of the first moving trajectory of each tourist is at the entrance or exit of the scenic area, and whether the end point is on the boundary line of the inner detection area;

[0015] The number of tourists whose starting point of the first moving trajectory is at the entrance and exit of the scenic area and whose end point is on the boundary line of the inner detection area is counted as the target entry number.

[0016] Preferably, counting the number of people leaving the target scenic spot within the first preset time period based on the second movement trajectory includes:

[0017] Determine whether the starting point of the second moving trajectory of each of the tourists is at the entrance or exit of the scenic area, and whether the end point is on the boundary line of the outer detection area;

[0018] The number of tourists whose starting point of the second moving trajectory is at the entrance and exit of the scenic area and whose end point is on the boundary line of the outer detection area is counted as the target departure number.

[0019] Preferably, counting the number of target persons entering the target scenic spot within the first preset time period based on the first movement trajectory includes:

[0020] Determine whether the starting point of the first moving trajectory of each tourist is at the entrance or exit of the scenic area, and whether the end point is on the boundary line of the inner detection area;

[0021] Counting the number of tourists whose starting point of the first moving trajectory is at the entrance and exit of the scenic area and whose end point is at the boundary line of the inner detection area as the first number of visitors;

[0022] Determine a first total number of people present in the inner detection area within the first preset time period;

[0023] Calculating a first ratio of the first number of people entering to the first total number of people;

[0024] A target number of people entering the target scenic spot within a first preset time period is determined according to the first ratio.

[0025] Preferably, determining the target number of people entering the target scenic spot within a first preset time period according to the first ratio includes:

[0026] If the first ratio is less than a preset first threshold, the tourist whose starting point of the first movement trajectory is not at the entrance or exit of the scenic area and / or whose end point is not on the boundary line of the inner detection area is marked as a first marked tourist;

[0027] The second preset time period before the first preset time period, the second preset time period after the first preset time period, and the total time period of the first preset time period are used as the third preset time period;

[0028] Determine a third movement trajectory of each first-marked visitor located in the inner detection area within the inner detection area within the third preset time period;

[0029] Determine whether the starting point of the third moving track of each first marked tourist is at the entrance or exit of the scenic area, and whether the end point is on the boundary line of the inner detection area;

[0030] Counting the number of first-marked tourists whose starting point of the third moving trajectory is at the entrance and exit of the scenic area and whose end point is at the boundary line of the inner detection area as the second number of people entering;

[0031] Add the first number of people entering and the second number of people entering to obtain a target number of people entering;

[0032] If the first ratio is not less than the first threshold, the first number of entrants is used as the target number of entrants.

[0033] Preferably, counting the number of people leaving the target scenic spot within the first preset time period based on the second movement trajectory includes:

[0034] Determine whether the starting point of the second moving trajectory of each of the tourists is at the entrance or exit of the scenic area, and whether the end point is on the boundary line of the outer detection area;

[0035] Count the number of tourists whose starting point of the second moving trajectory is at the entrance and exit of the scenic area and whose end point is at the boundary line of the outer detection area as the first number of departures;

[0036] Determine a second total number of people present in the outer detection area within the first preset time period;

[0037] Calculate a second ratio of the first number of people leaving to the second total number of people;

[0038] The target number of people leaving the target scenic spot within a first preset time period is determined according to the second ratio.

[0039] Preferably, determining the target number of people leaving the target scenic spot within a first preset time period according to the second ratio includes:

[0040] If the second ratio is less than a preset second threshold, the tourist whose starting point of the second movement trajectory is not at the entrance or exit of the scenic area and / or whose end point is not on the boundary line of the outer detection area is marked as a second marked tourist;

[0041] The fourth preset time period before the first preset time period, the fourth preset time period after the first preset time period, and the total time period of the first preset time period are used as the fifth preset time period;

[0042] Determine a fourth movement trajectory of each of the second-marked visitors located in the outer detection area within the outer detection area within the fifth preset time period;

[0043] Determine whether the starting point of the fourth movement trajectory of each second marked tourist is at the entrance or exit of the scenic area, and whether the end point is on the boundary line of the outer detection area;

[0044] Counting the number of second-marked tourists whose starting point of the fourth moving trajectory is at the entrance and exit of the scenic area and whose end point is at the boundary line of the inner detection area as the second number of departures;

[0045] Add the first number of people leaving and the second number of people leaving to obtain a target number of people leaving;

[0046] If the second ratio is not less than the second threshold, the first number of people leaving is used as the target number of people leaving.

[0047] Preferably, counting the number of target persons entering the target scenic spot within the first preset time period based on the first movement trajectory includes:

[0048] Setting a first judgment area inside the inner detection area;

[0049] For each of the tourists, determining the number of intersections between the first movement trajectory of the tourist and the boundary line of the first judgment area;

[0050] If the number of intersection points is odd, it is determined that the tourist is a real entering tourist;

[0051] If the number of intersection points is an even number, the tourist is marked as a tourist to be confirmed;

[0052] Determining whether the visitor to be confirmed appears in the outer detection area within a sixth preset time period after the first preset time period;

[0053] If yes, the tourist is determined to be a non-entering tourist; if no, the tourist is determined to be a truly entering tourist;

[0054] The number of tourists who actually enter is counted and used as the target number of visitors.

[0055] Preferably, the determining of the flow of people entering and leaving the target scenic spot in the first preset time period based on the target number of people entering and the target number of people leaving includes:

[0056] Compare the target number of people entering and the target number of people leaving, and calculate the difference between the target number of people entering and the target number of people leaving;

[0057] If the target number of people entering is greater than the target number of people leaving, and the difference is greater than a preset third threshold, the first preset time period is used as the peak time period of the flow of people in the target scenic spot;

[0058] If the target number of people entering is greater than the target number of people leaving, and the difference is not greater than a preset third threshold, the first preset time period is used as a low-peak period of the flow of people in the target scenic spot;

[0059] If the target number of people leaving is greater than the target number of people entering, and the difference is greater than a preset fourth threshold, the first preset time period is used as the peak outflow period of the target scenic spot;

[0060] If the target number of people leaving is greater than the target number of people entering, and the difference is not greater than a preset fourth threshold, the first preset time period is used as a low-peak outflow period of the target scenic spot.

[0061] In a second aspect, a device for identifying the flow of people entering and leaving a scenic spot includes:

[0062] A detection area setting module is used to obtain the location of the entrance and exit of the target scenic spot, and set an inner detection area and an outer detection area on the inner side and the outer side of the entrance and exit of the scenic spot respectively according to the location;

[0063] A first movement trajectory determination module is used to determine a first movement trajectory of each visitor located in the inner detection area within a first preset time period;

[0064] A target entry number counting module, used for counting the number of target entry numbers in the target scenic spot within the first preset time period based on the first movement trajectory;

[0065] A second movement trajectory determination module is used to determine a second movement trajectory of each visitor located in the outer detection area within the outer detection area within the first preset time period;

[0066] A target departure number counting module, used for counting the number of targets leaving the target scenic spot within the first preset time period based on the second movement trajectory;

[0067] The module for determining the flow of people in and out is used to determine the flow of people in and out of the target scenic spot in the first preset time period based on the target number of people entering and the target number of people leaving.

[0068] It can be seen from the above technical scheme that the present application obtains the position of the entrance and exit of the target scenic spot, and sets up an inner detection area and an outer detection area on the inner and outer sides of the entrance and exit of the scenic spot respectively according to the position; determines a first movement trajectory of each tourist located in the inner detection area within a first preset time period within the inner detection area; based on the first movement trajectory, counts the target number of people entering the target scenic spot within the first preset time period; determines a second movement trajectory of each tourist located in the outer detection area within the outer detection area within the first preset time period; based on the second movement trajectory, counts the target number of people leaving the target scenic spot within the first preset time period; determines the in-and-out flow status of the target scenic spot within the first preset time period based on the target number of people entering and the target number of people leaving. The solution sets up detection areas on the inner and outer sides of the entrance and exit of the scenic area respectively, and determines the movement status of tourists based on their movement trajectories in the two detection areas, so as to judge the number of people entering and leaving the scenic area. The movement trajectory can intuitively and clearly indicate whether tourists have entered or left the scenic area, and based on these two numbers, the tourist flow status of the target scenic area within the first preset time period can be accurately known, such as whether there are more tourists entering the scenic area within a certain time period, or more tourists leaving the scenic area within a certain time period, so as to help scenic area managers optimize and change the management mode or system of the scenic area, etc., and improve tourists' travel experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0070] Figure 1 An optional flow chart of a method for identifying the flow of people entering and leaving a scenic spot provided in an embodiment of the present application;

[0071] Figure 2 A schematic diagram of a setting scenario of a detection area provided in an embodiment of the present application;

[0072] Figure 3~Figure 6 A schematic diagram of a scene of a first movement trajectory provided in an embodiment of the present application;

[0073] Figure 7 A schematic diagram of the structure of a device for identifying the flow of people entering and leaving a scenic spot provided in an embodiment of the present application;

[0074] Figure 8 A schematic diagram of the structure of a device for identifying the flow of people entering and leaving a scenic area provided in an embodiment of the present application. DETAILED DESCRIPTION

[0075] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0076] The embodiment of the present invention provides a method for identifying the flow of people entering and leaving a scenic spot. The method can be applied to various computer terminals or smart terminals. The execution subject can be a processor or server of the computer terminal or smart terminal. The method flow chart of the method is as follows: Figure 1 As shown, specifically including:

[0077] S1: Acquire the location of the entrance and exit of the target scenic spot, and set an inner detection area and an outer detection area on the inner side and the outer side of the entrance and exit of the scenic spot respectively according to the location.

[0078] The target scenic spot in this application refers to any closed (with entrance / exit) recreation base, such as parks, amusement parks, mountains, scenic spots, etc.; some scenic spots have the same entrance and exit, while some scenic spots have separate entrances and exits, such as an entrance gate and an exit gate. For example, if the entrance and exit are the same, please refer to Figure 2 Taking this figure as an example, the left side of the scenic area entrance and exit is set as the target scenic area, and the right side is set as the outside of the target scenic area. Then, an inner detection area is set on the inner side of the scenic area entrance and exit, and an outer detection area is set on the outer side of the scenic area entrance and exit. The size of the inner detection area and the outer detection area can be determined according to the size of the target scenic area, or the shape of the detection area can be set arbitrarily according to the terrain, route and other features inside and outside the target scenic area, such as square, rectangle, circle, ellipse, etc., and it is composed of boundary lines. The size and shape of the inner detection area do not affect or interfere with the size and shape of the outer detection area; the scenic area entrance and exit can also be regarded as a boundary line.

[0079] It is understandable that if tourists enter the scenic area, they will first pass through the entrance and exit of the scenic area, and then enter the inner detection area; if tourists leave the scenic area, they will also pass through the entrance and exit of the scenic area, and then enter the outer detection area.

[0080] S2: Determine a first movement trajectory of each visitor located in the inner detection area within a first preset time period.

[0081] This step limits both the time period and the inner detection area, and only focuses on tourists who are in the inner detection area within the first preset time period. For example, if the scenic area manager only wants to determine the flow of tourists entering the scenic area within a certain time period, then the movement trajectory of tourists in the inner detection area within the first preset time period is determined, that is, the first movement trajectory. The first movement trajectory refers to the movement trajectory in the inner detection area.

[0082] It is understandable that, since the first preset time period can be set randomly, some tourists may have completed the process from the entrance and exit of the scenic area through the inner detection area to the interior of the scenic area within the first preset time period; some users may stay in the inner detection area and only enter the inner detection area from the entrance and exit of the scenic area within the first preset time period, but have not left the inner detection area to enter the actual scenic area; or the general direction of the first movement trajectory of some tourists is from the interior of the scenic area to the entrance and exit of the scenic area (which can be understood as leaving the scenic area). Therefore, the user's play status or play intention, etc. can be judged according to the moving direction or route of the first movement trajectory.

[0083] This solution is implemented based on the movement trajectory, which can accurately identify the flow of people entering the scenic area. Compared with existing methods, such as people counters, the number of scenic spot tickets, etc., it can improve the accuracy of recognition.

[0084] The first preset time period may be any time period, and the duration may be set arbitrarily. For example, the first preset time period may be 08:00-09:00, 16:30-17:30, etc. This embodiment does not impose any limitation on this.

[0085] S3: Based on the first movement trajectory, counting the number of people entering the target scenic spot within the first preset time period.

[0086] Since the movement trajectory can indicate the movement direction, status, etc. of the tourist, for example, the approximate direction of the first movement trajectory of a tourist in the inner detection area within the first preset time period is from the entrance of the scenic area to the boundary line of the inner detection area, such as Figure 3 As shown, it can be considered that the tourist has successfully entered the scenic area.

[0087] If a tourist's first movement trajectory in the inner detection area within the first preset time period starts from the entrance or exit of the scenic area but does not reach the boundary line of the inner detection area or near the boundary line, then it can be considered that the tourist has not actually entered the scenic area, or further judgment can be made on the tourist to improve accuracy.

[0088] S4: Determine a second movement trajectory of each visitor located in the outer detection area within the outer detection area within the first preset time period.

[0089] Similar to the idea of ​​determining the first movement trajectory, this step limits the time period and the external detection area at the same time, and only focuses on tourists who are in the external detection area within the first preset time period. For example, the scenic area manager only wants to determine the flow of tourists leaving the scenic area within a certain time period, then the movement trajectory of tourists in the external detection area within the first preset time period is determined, that is, the second movement trajectory.

[0090] Some tourists may have completed the process of leaving the scenic area from the entrance and exit of the scenic area through the outer detection area within the first preset time period, but some users may stay in the outer detection area or even enter the scenic area again. Therefore, these tourists only came out of the scenic area entrance and exit and walked to the outer detection area within the first preset time period, but did not actually leave the outer detection area. Therefore, the user's play status or play intention, etc. can also be judged according to the moving direction or route of the second movement trajectory.

[0091] S5: Based on the second movement trajectory, counting the number of people leaving the target scenic spot within the first preset time period.

[0092] For example, if a tourist's second moving trajectory in the outer detection area is roughly in the direction of moving from the entrance of the scenic area to the boundary line of the outer detection area within the first preset time period, then it can be considered that the tourist has actually left the scenic area.

[0093] If a tourist's second movement trajectory in the external detection area within the first preset time period starts from the entrance or exit of the scenic area, but does not leave the external detection area, or does not reach the boundary line of the external detection area, then it can be considered that the tourist did not actually leave the scenic area within the first preset time period, or further judgment can be made on the tourist to improve accuracy.

[0094] S6: Determine the flow of people entering and leaving the target scenic spot in the first preset time period based on the target number of people entering and leaving the target scenic spot.

[0095] After the target number of entries and the target number of exits of the target scenic spot within the first preset time period are determined, the approximate tourist flow situation and status of the target scenic spot within this time period can be clarified. For example, if the target number of entries is much greater than the target number of exits, it means that most tourists like to visit the target scenic spot during this time period. If the target number of exits is much greater than the target number of entries, it means that most tourists will leave the target scenic spot during this time period; if in a certain time period, the target number of exits is much greater than the target number of exits in other time periods, it means that the closing time may be too early or inappropriate, and the scenic spot management personnel can re-plan the closing time of the scenic spot based on this data comparison; if in a certain time period, the target number of entries is much greater than the target number of entries in other time periods, it means that the opening time may be relatively late or inappropriate, and the scenic spot management personnel can re-plan the opening time of the scenic spot based on this data comparison to prevent the crowd from being too crowded and reduce the waiting time for tourists.

[0096] The first moving trajectory and the second moving trajectory can be identified by using a surveillance camera installed in the target scenic area, and within the first preset time period, the surveillance camera cannot change its height and angle, so as not to affect the identification of the moving trajectories of multiple tourists due to height or angle problems. The YOLOv5 algorithm can be used to detect the head position of the tourists, and the optical flow method can be used to form the moving trajectory of each tourist. The YOLOv5 algorithm is a single-stage target detection algorithm with excellent detection speed and accuracy, which can improve the detection accuracy of the first moving trajectory and the second moving trajectory of the present application. The optical flow method is a method that uses the change of pixels in the time domain in the image sequence and the correlation between adjacent frames to find the corresponding relationship between the previous frame and the current frame, thereby calculating the motion information of the object between adjacent frames.

[0097] Another method used in the prior art is to obtain the location of the tourist's handheld terminal through the terminal's global positioning system (GPS), and then circle the latitude and longitude range of the scenic spot to screen the tourists in the scenic spot, and further obtain the flow of tourists in the scenic spot. However, when the tourist's terminal does not turn on the GPS, the tourist's location cannot be obtained, resulting in a low accuracy rate in the statistics of the flow of tourists in the scenic spot. On the other hand, the cost of installing equipment to identify the GPS is also relatively high. This solution does not require the identification of the tourist's GPS signal. Detection areas are set on both sides of the entrance and exit of the scenic spot, and the movement status of the tourists is determined by the movement trajectory of the tourists in the two detection areas. The number of people entering the scenic spot and the number of people leaving the scenic spot are determined by the movement trajectory. The movement trajectory can intuitively and clearly indicate whether the tourists have entered the scenic spot or left the scenic spot, and the tourist flow status of the target scenic spot within the first preset time period can be accurately known based on the two numbers. For example, more tourists enter the scenic spot within a certain time period, or more tourists leave the scenic spot within a certain time period, so as to help the scenic spot management personnel optimize and change the management mode or system of the scenic spot, etc., and improve the tourists' travel experience.

[0098] In the method provided in the embodiment of the present invention, there are multiple ways to count the number of target people entering the target scenic spot within the first preset time period based on the first moving trajectory, and to count the number of target people leaving the target scenic spot within the first preset time period based on the second moving trajectory, which are described one by one below:

[0099] 1. Determine once based on the starting point and the end point.

[0100] 1) Target number of entries:

[0101] Determine whether the starting point of the first moving trajectory of each tourist is at the entrance or exit of the scenic area, and whether the end point is on the boundary line of the inner detection area;

[0102] The number of tourists whose starting point of the first moving trajectory is at the entrance and exit of the scenic area and whose end point is on the boundary line of the inner detection area is counted as the target entry number.

[0103] In this method, we only need to pay attention to the starting point and end point of the first moving trajectory. If the starting point is at the entrance of the scenic area, it means that the tourist has entered the gate of the scenic area, and then passed through the inner detection area and left the inner detection area, that is, the end point of the first moving trajectory is on the boundary line of the inner detection area, then it can be said that the tourist has truly entered the target scenic area.

[0104] Taking the entrance and exit of a scenic spot as a boundary line as an example, the starting point at the entrance and exit of the scenic spot means that the starting point is on the boundary line.

[0105] 2) Target number of people leaving:

[0106] Determine whether the starting point of the second moving trajectory of each of the tourists is at the entrance or exit of the scenic area, and whether the end point is on the boundary line of the outer detection area;

[0107] The number of tourists whose starting point of the second moving trajectory is at the entrance and exit of the scenic area and whose end point is on the boundary line of the outer detection area is counted as the target departure number.

[0108] In this method, we only need to pay attention to the starting point and end point of the second moving trajectory. If the starting point is at the entrance or exit of the scenic area, it means that the tourist's general intention is to leave the scenic area, and he has passed through the outer detection area and left the outer detection area, that is, the end point of the second moving trajectory is on the boundary line of the outer detection area, then it can be said that the tourist has truly left the target scenic area.

[0109] In the above scheme, by limiting the starting point and the end point as judgment conditions at the same time, the number of tourists who actually enter the target scenic spot and the number of tourists who actually leave the target scenic spot can be accurately identified.

[0110] However, some tourists may move slowly, or stay in the inner detection area / outer detection area for too long for some reason, and fail to complete the process from the entrance and exit of the scenic area to the boundary line of the detection area within the first preset time period, so an incomplete first movement trajectory / second movement trajectory will be obtained. If only the target number of people entering and leaving the scenic area obtained in the above manner is used as the in-and-out flow data of the scenic area, the statistical results may be inaccurate. Therefore, in order to more accurately identify the entry and exit status of tourists, this application also provides the following identification method:

[0111] (ii) Secondary determination is made based on the starting point and the end point.

[0112] 1) Target number of entries:

[0113] Determine whether the starting point of the first moving trajectory of each tourist is at the entrance or exit of the scenic area, and whether the end point is on the boundary line of the inner detection area;

[0114] Counting the number of tourists whose starting point of the first moving trajectory is at the entrance and exit of the scenic area and whose end point is at the boundary line of the inner detection area as the first number of visitors;

[0115] Determine a first total number of people present in the inner detection area within the first preset time period;

[0116] Calculating a first ratio of the first number of people entering to the first total number of people;

[0117] A target number of people entering the target scenic spot within a first preset time period is determined according to the first ratio.

[0118] Specifically, the process of determining the target number of people entering the target scenic spot within the first preset time period according to the first ratio may include:

[0119] If the first ratio is less than a preset first threshold, the tourist whose starting point of the first movement trajectory is not at the entrance or exit of the scenic area and / or whose end point is not on the boundary line of the inner detection area is marked as a first marked tourist;

[0120] The second preset time period before the first preset time period, the second preset time period after the first preset time period, and the total time period of the first preset time period are used as the third preset time period;

[0121] Determine a third movement trajectory of each first-marked visitor located in the inner detection area within the inner detection area within the third preset time period;

[0122] Determine whether the starting point of the third moving track of each first marked tourist is at the entrance or exit of the scenic area, and whether the end point is on the boundary line of the inner detection area;

[0123] Counting the number of first-marked tourists whose starting point of the third moving trajectory is at the entrance and exit of the scenic area and whose end point is at the boundary line of the inner detection area as the second number of people entering;

[0124] Add the first number of people entering and the second number of people entering to obtain a target number of people entering;

[0125] If the first ratio is not less than the first threshold, the first number of entrants is used as the target number of entrants.

[0126] It can be understood that compared with the above-mentioned first solution, the second solution adds a judgment mechanism, that is, if the number of tourists whose starting point and end point meet the conditions (that is, the starting point is at the entrance and exit of the scenic area, and the end point is on the boundary line of the inner detection area) is significantly different from the number of all tourists who appear in the inner detection area within the first preset time period, then only using the number of tourists whose starting point and end point meet the conditions as the target number of visitors will cause a large deviation from the number of people who actually enter the target scenic area for sightseeing. Therefore, in the second solution, a certain amount of time is appropriately added to the first preset time period as a new first preset time period (that is, the third preset time period), and then the starting point and end point of the first movement trajectory (that is, the third movement trajectory) are judged again, which can reduce the error and improve the accuracy of judgment.

[0127] That is, the total number of tourists whose starting point of the first moving trajectory is at the entrance and exit of the scenic area and whose end point is on the boundary line of the inner detection area is taken as the first number of people entering; then the first number of people entering is compared with the first total number of people in the detection area within the first preset time period. The first number of people entering can be divided by the first total number in the form of a ratio to obtain a first ratio, and a first threshold value of 0.8 is set. A higher value needs to be set for the first threshold value to ensure a higher degree of recognition accuracy. If the first ratio is less than the first threshold value, it means that the time range set for the first preset time period is too short. Therefore, a second preset time period is set separately, and the total time period composed of the second preset time period before the first preset time period, the second preset time period after the first preset time period, and the first preset time period itself is taken as the third preset time period In one example, the first preset time period is 16:00~17:00, and the second preset time period is 15 minutes. The second preset time period can be considered as a time length or a time range corresponding to the first preset time period. Therefore, the second preset time period before the first preset time period is 15:45~16:00, and the second preset time period after the first preset time period is 17:00~17:15. Then the third preset time period is 15:45~17:15. In this way, the time period is expanded to determine whether the starting point and end point of the third movement trajectory of the first marked tourist within this third preset time period meet the conditions, and the number of first marked tourists who meet the conditions is taken as the second number of entries. The first number of entries is added to the second number of entries to obtain the final target number of entries.

[0128] If the first ratio is not less than the first threshold, the first number of entrants may be used as the target number of entrants.

[0129] Furthermore, after the time period is expanded, a new first ratio may be calculated again and compared with the first threshold, and the cycle may be repeated until the latest first ratio is not less than the first threshold. However, it should be noted that the expanded time period needs to be a relatively short time period to avoid overcorrection.

[0130] 2) Target number of people leaving:

[0131] Determine whether the starting point of the second moving trajectory of each of the tourists is at the entrance or exit of the scenic area, and whether the end point is on the boundary line of the outer detection area;

[0132] Count the number of tourists whose starting point of the second moving trajectory is at the entrance and exit of the scenic area and whose end point is at the boundary line of the outer detection area as the first number of departures;

[0133] Determine a second total number of people present in the outer detection area within the first preset time period;

[0134] Calculate a second ratio of the first number of people leaving to the second total number of people;

[0135] The target number of people leaving the target scenic spot within a first preset time period is determined according to the second ratio.

[0136] Specifically, determining the target number of people leaving the target scenic spot within the first preset time period according to the second ratio includes:

[0137] If the second ratio is less than a preset second threshold, the tourist whose starting point of the second movement trajectory is not at the entrance or exit of the scenic area and / or whose end point is not on the boundary line of the outer detection area is marked as a second marked tourist;

[0138] The fourth preset time period before the first preset time period, the fourth preset time period after the first preset time period, and the total time period of the first preset time period are used as the fifth preset time period;

[0139] Determine a fourth movement trajectory of each of the second-marked visitors located in the outer detection area within the outer detection area within the fifth preset time period;

[0140] Determine whether the starting point of the fourth movement trajectory of each second marked tourist is at the entrance or exit of the scenic area, and whether the end point is on the boundary line of the outer detection area;

[0141] Counting the number of second-marked tourists whose starting point of the fourth moving trajectory is at the entrance and exit of the scenic area and whose end point is at the boundary line of the inner detection area as the second number of departures;

[0142] Add the first number of people leaving and the second number of people leaving to obtain a target number of people leaving;

[0143] If the second ratio is not less than the second threshold, the first number of people leaving is used as the target number of people leaving.

[0144] In the above scheme, the process of twice determining the number of target people leaving by using the starting point position and the end point position is the same as the process of twice determining the number of target people entering by using the starting point position and the end point position, so it will not be repeated here.

[0145] The second preset time period and the fourth preset time period may be set to the same time length or different time lengths.

[0146] (III) The number of target persons entering the target area is identified by the number of intersections between the moving trajectory and the boundary line of the judgment area.

[0147] Setting a first judgment area inside the inner detection area;

[0148] For each of the tourists, determining the number of intersections between the first movement trajectory of the tourist and the boundary line of the first judgment area;

[0149] If the number of intersection points is odd, it is determined that the tourist is a real entering tourist;

[0150] If the number of intersection points is an even number, the tourist is marked as a tourist to be confirmed;

[0151] Determining whether the visitor to be confirmed appears in the outer detection area within a sixth preset time period after the first preset time period;

[0152] If yes, the tourist is determined to be a non-entering tourist; if no, the tourist is determined to be a truly entering tourist;

[0153] The number of tourists who actually enter is counted and used as the target number of visitors.

[0154] Specifically, in addition to using the starting point and the end point as the identification criteria, the present application also provides an identification method, such as Figure 4 As shown, first, a first judgment area is set inside the inner detection area. One of the boundary lines of the first judgment area overlaps with the entrance and exit of the scenic area, and the other boundary lines are distributed inside the inner detection area, that is, the area of ​​the first judgment area is smaller than that of the inner detection area. It should be noted that although the area of ​​the first judgment area is smaller than that of the inner detection area, it cannot be too small, otherwise it will affect the accuracy of the recognition result. At the same time, the boundary line of the first judgment area cannot be infinitely close to the boundary line of the inner detection area, so the number of intersections between the moving trajectory and the first judgment area cannot be accurately identified. Except for the boundary line overlapping with the entrance and exit of the scenic area, each point on the other boundary lines of the first judgment area is equal to the distance between the corresponding point on the boundary line of the inner detection area. For example, Figure 4 In the figure, the first boundary line 1 is parallel to the first boundary line 11, and the distance between the first boundary line 1 and the first boundary line 11 is L1; the second boundary line 2 is parallel to the second boundary line 22, and the distance between the second boundary line 2 and the second boundary line 22 is also L1, and the same is true for the remaining boundary lines.

[0155] The intersection between the first moving trajectory and the entrance and exit of the scenic area is not included. Please refer to Figure 4 , it can be seen that there is only one intersection point between the first moving trajectory and the first judgment area; similarly, please refer to Figure 5 , it can be seen that there are two intersections between the first moving trajectory and the first judgment area. Therefore, according to the judgment condition of whether the number of intersections is odd (odd) or even (even), it can be determined whether the tourist is a real tourist or a tourist to be confirmed. In addition, if the number of intersections is zero, it also belongs to the case of an even number of intersections, and the tourist will also be marked as a tourist to be confirmed.

[0156] If a certain tourist is currently considered to be a tourist to be confirmed, the outer detection area is considered. For example, if a tourist enters the scenic area and leaves soon, the number of intersections between the tourist and the first judgment area is even, and then enters the outer detection area again within a certain period of time, and this time is set as the sixth preset time period. Similarly, the sixth preset time period also needs to be set to a shorter time period to avoid overcorrection, such as Figure 6 As shown, the tourist can be identified as a non-entering tourist. If he does not appear in the outer detection area, he can be identified as a real entering tourist, and the number of real entering tourists is counted as the target number of entering tourists.

[0157] It is understandable that, considering that most tourists need to buy new tickets or be counted again in the number of people entering the scenic area after leaving the scenic area, this plan believes that the number of tourists who leave the scenic area and then re-enter the scenic area is relatively small, so this plan does not calculate the number of tourists leaving based on the intersection point; on the other hand, if a tourist leaves the scenic area and then re-enters the scenic area, it is considered that the tourist will be a tourist who actually enters the scenic area for fun, so he will be included in the count when counting the target number of people entering.

[0158] Furthermore, the process of determining the flow of people entering and leaving the target scenic spot in the first preset time period based on the target number of people entering and the target number of people leaving in the present application may specifically include:

[0159] Compare the target number of people entering and the target number of people leaving, and calculate the difference between the target number of people entering and the target number of people leaving;

[0160] If the target number of people entering is greater than the target number of people leaving, and the difference is greater than a preset third threshold, the first preset time period is used as the peak time period of the flow of people in the target scenic spot;

[0161] If the target number of people entering is greater than the target number of people leaving, and the difference is not greater than a preset third threshold, the first preset time period is used as a low-peak period of the flow of people in the target scenic spot;

[0162] If the target number of people leaving is greater than the target number of people entering, and the difference is greater than a preset fourth threshold, the first preset time period is used as the peak outflow period of the target scenic spot;

[0163] If the target number of people leaving is greater than the target number of people entering, and the difference is not greater than a preset fourth threshold, the first preset time period is used as a low-peak outflow period of the target scenic spot.

[0164] Specifically, in real scenarios, when counting the flow of people, only the number of people entering the scenic area is counted. If you want to know the flow of people entering and leaving within a certain time period, the existing method cannot be used to accurately count the number. Therefore, the present application approaches from two aspects, namely, counting the target number of people entering and the target number of people leaving within the same time period, and comparing the target number of people entering and the target number of people leaving to identify the tourist flow situation of the target scenic spot, such as whether there are many tourists in a certain time period, which may cause congestion. If the target number of people entering in a certain time period is much larger than the target number of people leaving, or even no tourists leave the target scenic spot during this time period, the manager of the target scenic spot can dynamically reduce the activities or attractions in the target scenic spot through these data comparison and identification situations, so as to avoid congestion in a certain scenic spot area or activity area, or limit the number of people entering the target scenic spot per unit time; if the target number of people entering in a certain time period is small, and the target number of people leaving is also small, it means that the overall number of tourists in the target scenic spot is relatively small, and it lacks highlights and the degree of attracting tourists. In this case, the activities or attractions in the target scenic spot can be dynamically increased to attract tourists to play.

[0165] Among them, when the target number of people entering is greater than the target number of people leaving, the difference between the target number of people entering and the target number of people leaving is calculated as follows: the target number of people entering minus the target number of people leaving; when the target number of people leaving is greater than the target number of people entering, the difference between the target number of people entering and the target number of people leaving is calculated as follows: the target number of people leaving minus the target number of people entering. In another case, the target number of people entering is equal to the target number of people leaving, which means that the first preset time period is the low-peak / peak time period for entering and leaving the target scenic spot. Whether it is a low-peak situation or a peak situation is determined by the number of target people entering / target people leaving.

[0166] and Figure 1 Corresponding to the method described above, the embodiment of the present invention also provides a device for identifying the flow of people entering and leaving a scenic spot, for Figure 1 In the specific implementation of the method, the identification device for the flow of people entering and leaving the scenic area provided by the embodiment of the present invention can be used in a computer terminal or various mobile devices, combined with Figure 7 , introduce the identification device of the flow of people entering and leaving the scenic area, such as Figure 7 As shown, the device may include:

[0167] A detection area setting module 10 is used to obtain the location of the entrance and exit of the target scenic spot, and to set an inner detection area and an outer detection area on the inner side and the outer side of the entrance and exit of the scenic spot respectively according to the location;

[0168] A first movement trajectory determination module 20, for determining a first movement trajectory of each visitor located in the inner detection area within a first preset time period;

[0169] A target entry number counting module 30, configured to count the number of target entry numbers in the target scenic spot within the first preset time period based on the first movement trajectory;

[0170] A second movement trajectory determination module 40 is used to determine a second movement trajectory of each visitor located in the outer detection area within the outer detection area within the first preset time period;

[0171] A target departure number counting module 50, configured to count the number of targets leaving the target scenic spot within the first preset time period based on the second movement trajectory;

[0172] The in-and-out crowd flow state determination module 60 is used to determine the in-and-out crowd flow state of the target scenic spot in the first preset time period based on the target number of people entering and the target number of people leaving.

[0173] It can be seen from the above technical scheme that the scheme sets up detection areas on the inner and outer sides of the entrance and exit of the scenic area respectively, and determines the movement status of tourists based on the movement trajectories of tourists in these two detection areas, so as to judge the number of people entering and leaving the scenic area. The movement trajectory can intuitively and clearly indicate whether tourists have entered and left the scenic area, and based on these two numbers, the tourist flow status of the target scenic area within the first preset time period can be accurately known, such as whether there are more tourists entering the scenic area within a certain time period, or more tourists leaving the scenic area within a certain time period, so as to help scenic area managers optimize and change the management mode or system of the scenic area, etc., and improve tourists' travel experience.

[0174] Furthermore, the embodiment of the present application provides a device for identifying the flow of people entering and leaving a scenic spot. Figure 8 The hardware structure diagram of the identification device for the flow of people entering and leaving the scenic area is shown in FIG. Figure 8 The hardware structure of the device for identifying the flow of people entering and leaving a scenic spot may include: at least one processor 01, at least one communication interface 02, at least one memory 03 and at least one communication bus 04.

[0175] In the embodiment of the present application, the number of the processor 01 , the communication interface 02 , the memory 03 , and the communication bus 04 is at least one, and the processor 01 , the communication interface 02 , and the memory 03 communicate with each other through the communication bus 04 .

[0176] The processor 01 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention.

[0177] The memory 03 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), etc., such as at least one disk memory.

[0178] The memory stores a program, and the processor can call the program stored in the memory, and the program is used to execute the following method for identifying the flow of people entering and leaving the scenic spot, including:

[0179] Obtain the location of the entrance and exit of the target scenic spot, and set an inner detection area and an outer detection area on the inner side and the outer side of the entrance and exit of the scenic spot respectively according to the location;

[0180] Determine a first movement trajectory of each visitor located in the inner detection area within the inner detection area within a first preset time period;

[0181] Based on the first movement trajectory, counting the number of target people entering the target scenic spot within the first preset time period;

[0182] Determine a second movement trajectory of each visitor located in the outer detection area within the outer detection area within the first preset time period;

[0183] Based on the second movement trajectory, counting the number of people who leave the target scenic spot within the first preset time period;

[0184] The flow of people entering and leaving the target scenic spot in the first preset time period is determined based on the target number of people entering and the target number of people leaving.

[0185] Optionally, the detailed functions and extended functions of the program may refer to the description of the method for identifying the flow of people entering and leaving a scenic area in the method embodiment.

[0186] The embodiment of the present application further provides a storage medium, which may store a program suitable for execution by a processor, and when the program is executed, controls the device where the storage medium is located to execute the following method for identifying the flow of people entering and leaving a scenic spot, including:

[0187] Obtain the location of the entrance and exit of the target scenic spot, and set an inner detection area and an outer detection area on the inner side and the outer side of the entrance and exit of the scenic spot respectively according to the location;

[0188] Determine a first movement trajectory of each visitor located in the inner detection area within the inner detection area within a first preset time period;

[0189] Based on the first movement trajectory, counting the number of target people entering the target scenic spot within the first preset time period;

[0190] Determine a second movement trajectory of each visitor located in the outer detection area within the outer detection area within the first preset time period;

[0191] Based on the second movement trajectory, counting the number of people who leave the target scenic spot within the first preset time period;

[0192] The flow of people entering and leaving the target scenic spot in the first preset time period is determined based on the target number of people entering and the target number of people leaving.

[0193] Specifically, the storage medium may be a computer-readable storage medium, and the computer-readable storage medium may be an electronic memory such as a flash memory, an EEPROM (Electrically Erasable Programmable Read-Only Memory), an EPROM, a hard disk or a ROM.

[0194] Optionally, the detailed functions and extended functions of the program may refer to the description of the method for identifying the flow of people entering and leaving a scenic area in the method embodiment.

[0195] In addition, the functional modules in the various embodiments of the present disclosure can be integrated together to form an independent part, or each module can exist separately, or two or more modules can be integrated to form an independent part. If the function is implemented in the form of a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present disclosure is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for a computer device (which can be a personal computer, a live broadcast device, or a network device, etc.) to perform all or part of the steps of the methods of the various embodiments of the present disclosure.

[0196] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0197] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0198] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for identifying the flow of people entering and leaving a scenic spot, characterized in that: include: Obtain the location of the entrance and exit of the target scenic spot, and set an inner detection area and an outer detection area on the inner side and the outer side of the entrance and exit of the scenic spot respectively according to the location; Determine a first movement trajectory of each visitor located in the inner detection area within the inner detection area within a first preset time period; Based on the first movement trajectory, counting the number of target people entering the target scenic spot within the first preset time period; Determine a second movement trajectory of each visitor located in the outer detection area within the outer detection area within the first preset time period; Based on the second movement trajectory, the target number of people leaving the target scenic spot within the first preset time period is counted; including: judging whether the starting point of the second movement trajectory of each tourist is at the entrance and exit of the scenic spot, and whether the end point is on the boundary line of the outer detection area; counting the number of tourists whose starting point of the second movement trajectory is at the entrance and exit of the scenic spot and whose end point is on the boundary line of the outer detection area as the first number of people leaving; determining the second total number of people appearing in the outer detection area within the first preset time period; calculating a second ratio of the first number of people leaving to the second total number of people; if the second ratio is less than a preset second threshold, marking the tourists whose starting point of the second movement trajectory is not at the entrance and exit of the scenic spot and / or whose end point is not on the boundary line of the outer detection area as the second marked tourists; and marking the tourists whose starting point of the second movement trajectory is not at the entrance and exit of the scenic spot and / or whose end point is not on the boundary line of the outer detection area as the second marked tourists. The fourth preset time period before the time period, the fourth preset time period after the first preset time period, and the total time period of the first preset time period are taken as the fifth preset time period; determining the fourth movement trajectory of each second-marked tourist located in the outer detection area within the fifth preset time period in the outer detection area; judging whether the starting point of the fourth movement trajectory of each second-marked tourist is at the entrance and exit of the scenic area, and whether the end point is on the boundary line of the outer detection area; counting the number of second-marked tourists whose starting point of the fourth movement trajectory is at the entrance and exit of the scenic area and whose end point is on the boundary line of the inner detection area as the second departure number; adding the first departure number and the second departure number to obtain the target departure number; if the second ratio is not less than the second threshold value, taking the first departure number as the target departure number; The flow of people entering and leaving the target scenic spot in the first preset time period is determined based on the target number of people entering and the target number of people leaving.

2. The method according to claim 1, characterized in that The counting of the number of target persons entering the target scenic spot within the first preset time period based on the first movement trajectory includes: Determine whether the starting point of the first moving trajectory of each tourist is at the entrance or exit of the scenic area, and whether the end point is on the boundary line of the inner detection area; The number of tourists whose starting point of the first moving trajectory is at the entrance and exit of the scenic area and whose end point is on the boundary line of the inner detection area is counted as the target entry number.

3. The method according to claim 1, characterized in that The counting of the number of target persons entering the target scenic spot within the first preset time period based on the first movement trajectory includes: Determine whether the starting point of the first moving trajectory of each tourist is at the entrance or exit of the scenic area, and whether the end point is on the boundary line of the inner detection area; Counting the number of tourists whose starting point of the first moving trajectory is at the entrance and exit of the scenic area and whose end point is at the boundary line of the inner detection area as the first number of visitors; Determine a first total number of people present in the inner detection area within the first preset time period; Calculating a first ratio of the first number of people entering to the first total number of people; A target number of people entering the target scenic spot within a first preset time period is determined according to the first ratio.

4. The method according to claim 3, characterized in that Determining the target number of people entering the target scenic spot within a first preset time period according to the first ratio includes: If the first ratio is less than a preset first threshold, the tourist whose starting point of the first movement trajectory is not at the entrance or exit of the scenic area and / or whose end point is not on the boundary line of the inner detection area is marked as a first marked tourist; The second preset time period before the first preset time period, the second preset time period after the first preset time period, and the total time period of the first preset time period are used as the third preset time period; Determine a third movement trajectory of each first-marked visitor located in the inner detection area within the inner detection area within the third preset time period; Determine whether the starting point of the third moving track of each first marked tourist is at the entrance or exit of the scenic area, and whether the end point is on the boundary line of the inner detection area; Counting the number of first-marked tourists whose starting point of the third moving trajectory is at the entrance and exit of the scenic area and whose end point is at the boundary line of the inner detection area as the second number of people entering; Add the first number of people entering and the second number of people entering to obtain a target number of people entering; If the first ratio is not less than the first threshold, the first number of entrants is used as the target number of entrants.

5. The method according to claim 1, characterized in that The counting of the number of target persons entering the target scenic spot within the first preset time period based on the first movement trajectory includes: Setting a first judgment area inside the inner detection area; For each of the tourists, determining the number of intersections between the first movement trajectory of the tourist and the boundary line of the first judgment area; If the number of intersection points is odd, it is determined that the tourist is a real entering tourist; If the number of intersection points is an even number, the tourist is marked as a tourist to be confirmed; Determining whether the visitor to be confirmed appears in the outer detection area within a sixth preset time period after the first preset time period; If yes, the tourist is determined to be a non-entering tourist; if no, the tourist is determined to be a truly entering tourist; The number of tourists who actually enter is counted and used as the target number of visitors.

6. The method according to claim 1, characterized in that The determining of the flow of people entering and leaving the target scenic spot in the first preset time period based on the target number of people entering and the target number of people leaving includes: Compare the target number of people entering and the target number of people leaving, and calculate the difference between the target number of people entering and the target number of people leaving; If the target number of people entering is greater than the target number of people leaving, and the difference is greater than a preset third threshold, the first preset time period is used as the peak time period of the flow of people in the target scenic spot; If the target number of people entering is greater than the target number of people leaving, and the difference is not greater than a preset third threshold, the first preset time period is used as a low-peak period of the flow of people in the target scenic spot; If the target number of people leaving is greater than the target number of people entering, and the difference is greater than a preset fourth threshold, the first preset time period is used as the peak outflow period of the target scenic spot; If the target number of people leaving is greater than the target number of people entering, and the difference is not greater than a preset fourth threshold, the first preset time period is used as a low-peak outflow period of the target scenic spot.

7. A device for identifying the flow of people entering and leaving a scenic area, characterized in that: include: A detection area setting module is used to obtain the location of the entrance and exit of the target scenic spot, and set an inner detection area and an outer detection area on the inner side and the outer side of the entrance and exit of the scenic spot respectively according to the location; A first movement trajectory determination module is used to determine a first movement trajectory of each visitor located in the inner detection area within a first preset time period; A target entry number counting module, used for counting the number of target entry numbers in the target scenic spot within the first preset time period based on the first movement trajectory; A second movement trajectory determination module is used to determine a second movement trajectory of each visitor located in the outer detection area within the outer detection area within the first preset time period; A target departure number counting module is used to count the target departure number of the target scenic spot within the first preset time period based on the second movement trajectory; including: judging whether the starting point of the second movement trajectory of each tourist is at the entrance and exit of the scenic spot, and whether the end point is on the boundary line of the outer detection area; counting the number of tourists whose starting point of the second movement trajectory is at the entrance and exit of the scenic spot and whose end point is on the boundary line of the outer detection area as the first departure number; determining the second total number of people who appear in the outer detection area within the first preset time period; calculating the second ratio of the first departure number to the second total number; if the second ratio is less than a preset second threshold, marking the tourists whose starting point of the second movement trajectory is not at the entrance and exit of the scenic spot and / or whose end point is not on the boundary line of the outer detection area as the second marked tourists; The fourth preset time period before the first preset time period, the fourth preset time period after the first preset time period, and the total time period of the first preset time period are taken as the fifth preset time period; determining the fourth movement trajectory of each second-marked tourist located in the outer detection area within the fifth preset time period in the outer detection area; judging whether the starting point of the fourth movement trajectory of each second-marked tourist is at the entrance and exit of the scenic area, and whether the end point is on the boundary line of the outer detection area; counting the number of second-marked tourists whose starting point of the fourth movement trajectory is at the entrance and exit of the scenic area and whose end point is on the boundary line of the inner detection area as the second departure number; adding the first departure number and the second departure number to obtain the target departure number; if the second ratio is not less than the second threshold value, taking the first departure number as the target departure number; The module for determining the flow of people in and out is used to determine the flow of people in and out of the target scenic spot in the first preset time period based on the target number of people entering and the target number of people leaving.

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