Trajectory generation method, device, electronic device and storage medium

Abstract

The present invention relates to the field of image recognition, and an embodiment discloses a trajectory generation method, device, electronic device and storage medium. The method comprises: obtaining original trajectory data corresponding to a target user, and dividing the original trajectory data into at least one original trajectory sub-data according to time information; determining the target position information corresponding to the target user in each area based on the original trajectory sub-data; and determining the target trajectory information corresponding to the target user based on at least one target position information corresponding to each original trajectory sub-data. The technical solution of the embodiment of the present invention realizes compression processing of multiple original trajectory data, and can clearly obtain the trajectory data of the user, thereby achieving the technical effect of reducing the redundancy of trajectory data and the difficulty of data storage, as well as reducing the difficulty of calculation and processing when subsequently analyzing the trajectory data.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of image recognition technology, and in particular to a trajectory generation method, device, electronic device, and storage medium. Background Art

[0002] In the process of motion trajectory generation, the user can be photographed based on multiple monitoring devices set in the target area to obtain the user's facial image data, and the user's trajectory data can be generated based on the photographed facial image data. However, due to the large amount of facial image data, the facial image data of the target user needs to be extracted from a large amount of facial image data. In the process of facial image data extraction, there is a problem that the facial image data of the target user is difficult to extract. Furthermore, due to the large amount of facial image data of the target user, the amount of data generated for the trajectory data of the target user is also large, resulting in a high redundancy of the generated trajectory data, thereby increasing the storage burden and being unfavorable for subsequent calculation processing when analyzing the motion trajectory. Summary of the invention

[0003] The embodiments of the present invention provide a trajectory generation method, device, electronic device and storage medium to reduce the redundancy of trajectory data, thereby reducing the difficulty of data storage and the difficulty of subsequent calculation and processing when analyzing the trajectory data.

[0004] In a first aspect, an embodiment of the present invention provides a trajectory generation method, the method comprising:

[0005] Acquire original trajectory data corresponding to the target user, and divide the original trajectory data into at least one original trajectory sub-data according to time information;

[0006] Determining target location information corresponding to the target user in each area based on the original trajectory sub-data;

[0007] Based on at least one target position information corresponding to each original trajectory sub-data, target trajectory information corresponding to the target user is determined.

[0008] In a second aspect, an embodiment of the present invention further provides a trajectory generating device, the device comprising:

[0009] an original trajectory sub-data division module, configured to obtain original trajectory data corresponding to a target user, and divide the original trajectory data into at least one original trajectory sub-data according to time information;

[0010] A target location information determination module, used to determine the target location information corresponding to the target user in each area based on the original trajectory sub-data;

[0011] The target trajectory information determination module is used to determine the target trajectory information corresponding to the target user based on at least one target position information corresponding to each original trajectory sub-data.

[0012] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0013] one or more processors;

[0014] A storage device for storing one or more programs;

[0015] When the program is executed by the processor, the processor implements the trajectory generation method provided by any embodiment of the present invention.

[0016] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a trajectory generation method as provided in any embodiment of the present invention.

[0017] The technical solution of this embodiment can obtain the shooting time of the original trajectory data of the target user, the device identification of the camera device and the location information of the camera device by acquiring the original trajectory data corresponding to the target user, and divide the original trajectory data into at least one original trajectory sub-data according to the time information. By determining the target location information corresponding to the target user in each area based on the original trajectory sub-data. By determining the target trajectory information corresponding to the target user based on at least one target location information corresponding to each original trajectory sub-data, it is realized to compress multiple original trajectory data, and the user's trajectory data can be clearly obtained, which solves the technical problems of high redundancy of trajectory data, difficulty in storing trajectory data, and high difficulty in calculating and processing when analyzing subsequent trajectory data in the trajectory generation method in the prior art, and achieves the technical effect of reducing the redundancy of trajectory data and data storage difficulty, as well as reducing the difficulty of calculating and processing when analyzing subsequent trajectory data. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required to describe the embodiments. Obviously, the drawings introduced are only drawings of a part of the embodiments to be described in the present invention, rather than all the drawings. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 It is a schematic diagram of a trajectory generation method provided in Embodiment 1 of the present invention;

[0020] Figure 2It is a schematic diagram of a trajectory generation method provided by Embodiment 2 of the present invention;

[0021] Figure 3 This is a schematic diagram of a regional distribution structure provided by Embodiment 2 of the present invention;

[0022] Figure 4 It is a schematic diagram of a trajectory generation method provided by Embodiment 3 of the present invention;

[0023] Figure 5 It is a schematic diagram of a trajectory generation method provided by Embodiment 4 of the present invention;

[0024] Figure 6 is a schematic diagram of a trajectory generation system module provided by Embodiment 4 of the present invention;

[0025] Figure 7 It is a schematic diagram of a trajectory generating device module provided by Embodiment 5 of the present invention;

[0026] Figure 8 It is a structural schematic diagram of an electronic device provided in Embodiment 6 of the present invention. DETAILED DESCRIPTION

[0027] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0028] Embodiment 1

[0029] Figure 1 1 is a flow chart of a trajectory generation method provided in Embodiment 1 of the present invention. This embodiment is applicable to the case where the target trajectory information of the target user is obtained by processing the original trajectory data of the target user. The method can be executed by a trajectory generation device. The trajectory generation device can be implemented by software and / or hardware. The trajectory generation device can be integrated in an electronic device such as a computer or a server.

[0030] In order to facilitate the determination of the target user's trajectory in the target area, a scenario is briefly introduced here, where multiple cameras are deployed in the target area, and the target user is photographed based on the cameras deployed in the target area. It should be noted that when deploying the cameras, the location information of the cameras can be marked, and the marked location information of the cameras can be expressed in latitude and longitude, or can be first established based on a coordinate system at a preset position and then expressed in the form of coordinates.

[0031] like Figure 1 As shown, the method of this embodiment includes:

[0032] S110: Acquire original trajectory data corresponding to a target user, and divide the original trajectory data into at least one original trajectory sub-data according to time information.

[0033] Among them, the target user can be a person to be monitored in a preset place, such as a staff member of a building, a tourist in a scenic spot, etc. The information of the target user may include: identity information such as user identification and facial image data. The method of determining the target user may include: performing feature comparison on the facial image data of the target user with the facial image data pre-stored in the database to obtain a comparison result; according to the comparison result, determining the target user to identify the target user. Among them, the feature comparison method can adopt the facial recognition software or iris recognition software in the prior art to realize the identification of the target user. It should be noted that in the embodiment of the present invention, the feature comparison method is not limited, as long as the target user can be realized.

[0034] The original trajectory data may be data captured by one or more cameras. The information carried by the original trajectory data may include: user identification, shooting time, and device identification of the camera. The original trajectory data may be used to reflect the movement trajectory of the target user and provide basic data for the division of trajectory data.

[0035] Among them, obtaining the original trajectory data corresponding to the target user may include: determining the user identifier of the target user based on a preset face recognition method; obtaining captured image data corresponding to the user identifier according to the user identifier of the target user, that is, obtaining image data corresponding to the target user; and generating the original trajectory data of the target user according to the image data corresponding to the target user.

[0036] Further, generating the original trajectory data of the target user may include: pre-storing a device identification of each camera device and location information of the camera device corresponding to the device identification, and determining, based on image data corresponding to the target user, a shooting time corresponding to the image data and a device identification of the camera device; determining the location information of the camera device based on the device identification of the camera device and based on pre-stored device identification of the camera device and location information of the camera device corresponding to the device identification; and generating the original trajectory data of the target user based on the shooting time and the location information of the camera device.

[0037] The time information may include a time period corresponding to the original trajectory data and a time period corresponding to the original trajectory sub-data. For example, the time information is: the time period corresponding to the original trajectory data is 8:00 to 12:00 on XX / XX / XX, and the time period corresponding to the original trajectory sub-data is 8:00 to 9:00 on XX / XX / XX.

[0038] Among them, the original trajectory sub-data can be understood as the original trajectory data of the target user captured by the camera device within a preset time period (such as 8:00 to 10:00). Exemplarily, within the time period from 8:00 to 10:00, the target user can go to different areas. Correspondingly, the cameras set in different areas can capture the target user multiple times. If each shot is taken as an original trajectory sub-data, then there will be multiple original trajectory sub-data between 8 o'clock and 10 o'clock, and the collection of all original trajectory sub-data can be used as part of the original trajectory data in the original trajectory data. That is, the number of original trajectory sub-data can be one or more. The information in the original trajectory sub-data may include: the device identification of the camera device, the location information of the camera device, the shooting time, and the user identification of the target user.

[0039] The advantage of dividing the original trajectory data into at least one original trajectory sub-data according to the time information is that the data processing efficiency is improved, and the target position of the target user in each area can be determined more quickly.

[0040] Specifically, a face recognition method is preset, and time information for dividing the original trajectory data is preset. According to the preset face recognition method, the user identifier of the target user is determined. According to the user identifier of the target user, image data corresponding to the user identifier is acquired. According to the image data corresponding to the user identifier, the shooting time corresponding to the image data and the device identifier of the camera device are determined. According to the device identifier of the camera device, the location information of the camera device can be determined. According to the shooting time and the location information of the camera device, the original trajectory data of the target user is generated. According to the preset time information for dividing the original trajectory data, the original trajectory data of the target user is divided to obtain one or more original trajectory sub-data of the target user.

[0041] In order to reduce the repetitiveness of trajectory data and compress trajectory data more reasonably, dividing the original trajectory data into at least one original trajectory sub-data according to time information may include: dividing the original trajectory data into at least one original trajectory sub-data according to the data generation time of the original trajectory data and a preset time interval.

[0042] Among them, the data generation time of the original trajectory data can be the shooting time of the target user shot by the camera device (such as 9:20). The time interval can be a pre-set time interval (such as 1 hour or 4 hours). The time interval can be adjusted according to actual needs. For example, the time interval corresponding to each season can be set according to the season, such as the time interval in spring can be 1 hour; the time interval in summer can be 6 hours; the time interval in autumn can be 2 hours; the time interval in winter can be 4 hours. The corresponding time interval can also be set according to weekdays and Sundays, such as the time interval on weekdays can be 4 hours; the time interval on Sundays can be 2 hours.

[0043] Specifically, the time intervals for dividing the original trajectory data are preset. The original trajectory data is divided according to the pre-divided time intervals and the data generation time of the original trajectory data to obtain the original trajectory data corresponding to each time interval, that is, to obtain each original trajectory sub-data.

[0044] S120: Determine target location information corresponding to the target user in each area based on the original trajectory sub-data.

[0045] Among them, the area can be a pre-divided area in a preset place. The number of areas can be one or more. If there is one, the entire area is taken as one area, and if there are multiple areas, the target area is divided into multiple areas according to certain principles. Exemplarily, the preset place is a tourist attraction, and the area of ​​the tourist attraction is large. In order to determine the trajectory of each target user, the tourist attraction can be divided into multiple areas. In order to further improve the accuracy and universality of determining the trajectory, the scenic area can be divided into multiple sub-attraction areas, that is, the various areas obtained, based on the historical user's enthusiasm for each sub-attraction in the scenic spot, that is, the preference program. The target location information can be any location information in each area. The target location information can be characterized by longitude and latitude. Exemplarily, the longitude information can be represented by Lon, and the latitude information can be represented by Lat, that is, Lon = 116 degrees 23 minutes 29.22 seconds east longitude, Lat = 39 degrees 54 minutes 26.37 seconds north latitude, and the target location information is: (116 degrees 23 minutes 29.22 seconds east longitude, 39 degrees 54 minutes 26.37 seconds north latitude).

[0046] Before determining the target location information corresponding to the target user in each area, the relationship between the area identifier and the device identifier of the camera device can be established in advance. The relationship between the device identifier of the camera device and the location information of the camera device can be established in advance.

[0047] Specifically, a relationship between the area identifier and the device identifier of the camera device is pre-established. A relationship between the device identifier of the camera device and the location information of the camera device is pre-established. When it is detected that the division of the original trajectory sub-data corresponding to the target user is completed, that is, when the original trajectory sub-data corresponding to the target user is obtained, the shooting time of the original trajectory sub-data and the device identifier of the camera device can be determined. According to the pre-established relationship between the area identifier and the device identifier of the camera device, the pre-established relationship between the device identifier of the camera device and the location information of the camera device, and the shooting time of the original trajectory sub-data and the device identifier of the camera device, the target location information corresponding to the target user in each area is determined.

[0048] S130: Determine target trajectory information corresponding to the target user based on at least one target position information corresponding to each original trajectory sub-data.

[0049] The target trajectory information may be used to determine the trajectory of the target user, so as to analyze the trajectory of the target user. The target trajectory information may include at least one target position information.

[0050] It should be noted that when the time periods selected for the original trajectory data are different, or when the time intervals for dividing the original trajectory data are different, the target positions corresponding to the original trajectory sub-data may be the same or different. In this embodiment, the selection of the original trajectory data and the time intervals for dividing the original trajectory data may be input according to the actual needs of the user and are not limited here.

[0051] In order to more vividly reflect the target trajectory information corresponding to the target user, based on at least one target position information corresponding to each original trajectory sub-data, determining the target trajectory information corresponding to the target user can include: determining the target trajectory information corresponding to the target user by splicing at least one target position information corresponding to each original trajectory sub-data.

[0052] The splicing process can be understood as a fitting process, which can be used to fit multiple target position information to obtain target trajectory information corresponding to the target user. In order to improve the accuracy of the fitting, a connection curve between each camera device can be established in advance, and at least one target position information corresponding to each original trajectory sub-data can be fitted according to the connection curve between each camera device to obtain the target trajectory information corresponding to the target user.

[0053] It should be noted that, in the fitted trajectory route, the arc, i.e., the curvature, of each route can be determined based on the position information passed at each time point, that is, the position information of the camera device that captures the target user. The position information at this time is different from the determined target position.

[0054] Specifically, a splicing processing method is pre-set. When the target position information corresponding to the target user in each area is determined from an original trajectory sub-data, the target position information corresponding to each original trajectory sub-data can be determined by traversal. According to the pre-set splicing processing method, the target position corresponding to each original trajectory sub-data can be fitted, that is, the target position corresponding to each original trajectory sub-data is connected by a curve. When it is detected that the fitting processing is completed, the trajectory data of the target user is generated, that is, the target trajectory information of the target user is obtained.

[0055] Exemplarily, the target location information is: 116 degrees 23 minutes 29.22 seconds east longitude, 39 degrees 54 minutes 26.37 seconds north latitude; 116 degrees 23 minutes 30 seconds east longitude, 39 degrees 54 minutes 27 seconds north latitude; 116 degrees 23 minutes 28 seconds east longitude, 39 degrees 54 minutes 25.22 seconds north latitude. The target trajectory information corresponding to the target user is: the line from 116 degrees 23 minutes 29.22 seconds east longitude, 39 degrees 54 minutes 26.37 seconds north latitude to 116 degrees 23 minutes 30 seconds east longitude, 39 degrees 54 minutes 27 seconds north latitude; and the line from 116 degrees 23 minutes 30 seconds east longitude, 39 degrees 54 minutes 27 seconds north latitude to 116 degrees 23 minutes 28 seconds east longitude, 39 degrees 54 minutes 25.22 seconds north latitude. At this time, the connection needs to take into account the possible obstacles between the location points, and the actual layout of the venue needs to be considered to connect the lines.

[0056] In order to facilitate the staff to analyze the trajectory data, after obtaining the target trajectory information, the target trajectory information can also be sent to the target terminal, so that the target terminal processes the data of each area according to the received target trajectory information.

[0057] The target terminal may be a pre-set terminal device, which may be used to store one or more target trajectory information.

[0058] Specifically, a terminal device for storing each target trajectory information is pre-set. When the target trajectory information of the target user is detected, the target trajectory information of the target user can be sent to the terminal device according to the pre-set terminal device, so that the terminal device receives each target trajectory information. When the terminal device receives each target trajectory information, the relevant staff can process the data of each area according to each target trajectory information.

[0059] The technical solution of this embodiment can obtain the shooting time of the original trajectory data of the target user, the device identification of the camera device and the location information of the camera device by acquiring the original trajectory data corresponding to the target user, and divide the original trajectory data into at least one original trajectory sub-data according to the time information. By determining the target location information corresponding to the target user in each area based on the original trajectory sub-data. By determining the target trajectory information corresponding to the target user based on at least one target location information corresponding to each original trajectory sub-data, it is realized to compress multiple original trajectory data, and the user's trajectory data can be clearly obtained, which solves the technical problems of high redundancy of trajectory data, difficulty in storing trajectory data, and high difficulty in calculating and processing when analyzing subsequent trajectory data in the trajectory generation method in the prior art, and achieves the technical effect of reducing the redundancy of trajectory data and data storage difficulty, as well as reducing the difficulty of calculating and processing when analyzing subsequent trajectory data.

[0060] Embodiment 2

[0061] Figure 2 This is a flow chart of a trajectory generation method provided by the second embodiment of the present invention. Based on the above embodiment, the first embodiment is optimized. The specific implementation method can be found in the following embodiment. The technical terms that are the same or corresponding to the above embodiment are not repeated here.

[0062] like Figure 2 As shown, the method of this embodiment may specifically include:

[0063] S210: Based on the camera devices pre-set in each area, capture a target image including a target user.

[0064] The number of regions may be one or more. The number of camera devices may be one or more. The relationship between regions and camera devices may be that one region is provided with one or more camera devices, and the number of camera devices provided in different regions may be the same or different. Figure 3 , 1 in the figure represents an area, and 2 in the figure represents a camera device. It should be noted that the number of camera devices set in each area can be set according to actual needs and is not limited here.

[0065] The information of the camera device may include the device identification of the camera device and the location information of the camera device. The location information of the camera device may include the longitude and latitude of the location of the camera device. The target image may be understood as an image obtained by shooting the target user, which is used to generate the original trajectory data of the target user. The information of the target image may include information such as the shooting time and the device identification of the camera device. The number of target images may be one or more.

[0066] Specifically, according to the actual needs of shooting, camera devices are pre-installed in various areas. Based on the camera devices installed in various areas, the target user is photographed to obtain the photographed image of the target user, that is, the target image including the target user is photographed.

[0067] S220 , generating trajectory data stored in a target storage location based on the target image, so that when receiving an instruction to generate target trajectory information, the original trajectory data is retrieved from the target storage location.

[0068] The target storage location may be a location where a preset storage path is stored, and may be used to store the original trajectory data. The instruction for generating the target trajectory information may be a program code or a trigger button, and may be used to generate the target trajectory information. The instruction for generating the target trajectory information may be generated based on a user trigger operation, and the user trigger operation method is not limited here, for example, a control trigger, a touch screen trigger, etc.

[0069] Specifically, a storage location of the target image is pre-set, and a storage location of the trajectory data is pre-set. According to the storage location of the pre-set target image, the captured target image is stored in the pre-set storage location. When a user operation is detected, an instruction to generate target trajectory information can be generated. So that when the instruction to generate target trajectory information is received, the original trajectory data of the target user can be extracted from the pre-set trajectory data storage location according to the pre-set trajectory data storage location.

[0070] Exemplarily, the storage path of the target image is d: / image. The storage path of the trajectory data is d: / trajectory data. d: / image stores the target image 1, target image 2, and target image 3 of the target user. Based on the target image 1, target image 2, and target image 3 of the target user, the original trajectory data of the target user is generated, and the original trajectory data is stored in d: / trajectory data.

[0071] S230: When receiving an instruction to generate target trajectory information, retrieve the original trajectory data of the target user within a preset time period from the target storage location, and divide the original trajectory data into at least one original trajectory sub-data according to the time information.

[0072] Specifically, a trajectory data storage location is preset, a time period for extracting the original trajectory data is preset (e.g., 9:00 to 10:00), and time information for dividing the original trajectory data is preset. When an instruction to generate target trajectory information is received, the original trajectory data of the target user within the preset time period can be extracted from the preset trajectory data storage location according to the preset trajectory data storage location and the time period for extracting the original trajectory data.

[0073] Specifically, when it is detected that the original trajectory data of the target user within the preset time period is extracted, the original trajectory data of the target user may be divided according to the preset time information for dividing the original trajectory data, and one or more original trajectory sub-data of the target user may be obtained.

[0074] S240: Determine target location information corresponding to the target user in each area based on the original trajectory sub-data.

[0075] S250: Determine target trajectory information corresponding to the target user based on at least one target position information corresponding to each original trajectory sub-data.

[0076] The technical solution of this embodiment is to shoot a target image including a target user by using a camera device pre-set in each area. By generating trajectory data stored in a target storage location based on the target image, the original trajectory data is retrieved from the target storage location when an instruction to generate target trajectory information is received. When an instruction to generate target trajectory information is received, the original trajectory data of the target user within a preset time length is retrieved from the target storage location, and the original trajectory data is divided into at least one original trajectory sub-data according to time information, thereby achieving the acquisition of the original trajectory data of the target user, and achieving the technical effect of improving the accuracy of the original trajectory data.

[0077] Embodiment 3

[0078] Figure 4 This is a flow chart of a trajectory generation method provided by the third embodiment of the present invention. Based on the above embodiment, the step S120 in the first embodiment can be described in detail. The specific implementation method can refer to the technical solution of this embodiment. The technical terms that are the same or corresponding to the above embodiment are not repeated here.

[0079] like Figure 4 As shown, the method of this embodiment may specifically include:

[0080] S310: Acquire original trajectory data corresponding to a target user, and divide the original trajectory data into at least one original trajectory sub-data according to time information.

[0081] Wherein, obtaining the original trajectory data corresponding to the target user may be obtaining the original trajectory data of the target user within a preset duration. Exemplarily, the target user is faceid(i), the original trajectory data of the target user is trace_origin(faceid(i)), the starting time of obtaining the original trajectory data of the target user is T_start, the preset duration is T, and [T_start, T_start+T] can be used to represent obtaining the original trajectory data of the preset duration T.

[0082] Exemplarily, the time information can be understood as dividing the preset duration into a preset number of time periods. Exemplarily, if the preset number is p, the preset duration (T) is divided into p time periods, that is, the time periods can be [T(1)~T(2)],…,[T(p),T(p+1)]. Among them, the original trajectory data corresponding to the pth time period is t_duration(p), and the time period corresponding to t_duration(p) is [T(p),T(p+1)].

[0083] S320: Determine a hotspot area corresponding to the target user from multiple areas according to the original trajectory sub-data.

[0084] The hot spot area can be understood as an area where the target user stays for a long time. Exemplarily, the place identifier of the preset place is j, the area is zoi(j), and the hot spot area is hot_zoi(j). The number of hot spots can be one or more. The hot spot area can include at least one camera device.

[0085] Among them, determining a hot spot area corresponding to the target user from multiple areas based on the original trajectory sub-data can include: determining a shooting interval, a number of repeated shooting times, and a number of cameras that shoot the target user in one of the areas based on the original trajectory sub-data; and determining a hot spot area corresponding to the target user from multiple areas based on the shooting interval, the number of repeated shooting times, and the number of cameras.

[0086] The shooting interval can be understood as the time interval for a camera to repeatedly shoot the target user. For example, the shooting interval is 2 seconds, that is, the target user is shot at 9:10:20 and the target user is shot at 9:10:22. The number of repeated shootings can be understood as the number of times a camera continuously shoots the target user. The number of cameras that shoot the target user can be understood as: the number of cameras that include the target user in the shooting object (e.g., 3).

[0087] Specifically, when it is detected that the original trajectory data of the target user is divided, that is, when the original trajectory sub-data of the target user is obtained, the shooting time of the original trajectory sub-data, the device identification of the camera, and the location information of the camera can be obtained. When the data acquisition is completed, for an area, the shooting interval, the number of repeated shootings, and the number of cameras that include the target user in the shooting object can be obtained according to the shooting time and the device identification of the camera. When the shooting information of the target user in the area is obtained, each area can be traversed to obtain the shooting information of the target user in each area. When the shooting information of the target user in each area is obtained, the hot spot area corresponding to the target user can be determined from multiple areas.

[0088] Furthermore, based on the shooting interval, the number of repeated shootings and the number of cameras, a hot spot area corresponding to the target user is determined from multiple areas, which may include: when the shooting interval is less than a preset shooting interval, the number of repeated shootings is greater than or equal to a preset number of shootings, and the number of cameras is greater than or equal to a preset number of cameras, the area to which the camera device belongs is a hot spot area.

[0089] The preset shooting interval can be understood as the threshold of the time interval for repeatedly shooting the target user, which can be represented by wander_interval, such as wander_interval=10s. The preset shooting times can be understood as the threshold of the shooting times for a camera to repeatedly shoot the target user, which can be represented by R, such as R=10. The preset number of camera devices can be understood as the minimum number of camera devices that include the target user in the shooting object, which can be represented by S, such as S=3.

[0090] In this embodiment, there are at least two ways to determine a hotspot area. The first embodiment may be that, for an area, when the time interval for a camera device to shoot a target user is less than a preset shooting interval, and the number of times a camera device repeatedly shoots the target user is greater than a preset shooting number, and the number of cameras shooting the target user in the area is greater than a preset number of cameras, then the area can be determined to be a hotspot area.

[0091] A second implementation may be that, for an area, when the time interval for photographing a target user by a camera device is less than a preset shooting interval, and the sum of the number of times that each camera device in the area repeatedly photographs the target user is greater than a preset shooting number, and the number of cameras photographing the target user in the area is greater than a preset number of cameras, then the area may be determined to be a hotspot area.

[0092] Specifically, a method for determining hotspot areas is pre-set. When the division of the original trajectory data is completed, that is, when the original trajectory sub-data is obtained, the shooting information of the original trajectory sub-data can be obtained, that is, the shooting time of the original trajectory sub-data, the device identification of the camera device, and the location information of the camera device can be obtained. When the shooting information of the original trajectory sub-data is obtained, the shooting information of an area can be obtained, and the time interval for the camera device in the area to shoot the target user, the number of times each camera repeatedly shoots the target user, and the number of cameras that shoot the target user in the area can be calculated. According to the pre-set method for determining the hotspot area, and according to the calculated data, the area can be determined as a hotspot area. Using the above judgment conditions, each area is traversed, and the hotspot area corresponding to the target user can be determined from multiple areas.

[0093] S330: For each hot spot area, determine the shooting frequency of each camera device in the current hot spot area to shoot the target user.

[0094] The current hot spot area may be one of the multiple hot spot areas. The shooting frequency may be understood as the number of times the shooting device shoots the target user. For each hot spot area, determining the shooting frequency of each camera device in the current hot spot area shooting the target user may include: for each hot spot area, determining the number of times each camera device in the current hot spot area shoots the target user according to the original trajectory sub-data corresponding to the current hot spot area.

[0095] Specifically, when the hotspot area corresponding to the target user is determined from multiple areas, the number of hotspot areas corresponding to the target user can be determined. When it is detected that the number of hotspot areas corresponding to the target user is greater than 1, the original trajectory data of the target user in the current hotspot area can be obtained, that is, the shooting time of the original trajectory data and the device identification of the shooting device can be obtained. According to the shooting time and the device identification of the shooting device, the number of times the target user is included in the objects shot by each camera device in the current hotspot area can be determined.

[0096] Exemplarily, the target user is face(i), where i represents the user ID of the target user. The hot spot area is hot_zoi(j), where j represents the area ID. The original trajectory sub-data of the hot spot area hot_zoi(j) in time period q is t_duration(q). There are u cameras in hot_zoi(j) that capture face(i), where the number of times the first camera captures face(i) is cap_num(camera(1), t_duration(q)), the number of times the second camera captures face(i) is cap_num(camera(2), t_duration(q)), and the number of times the u-th camera captures face(i) is cap_num(camera(u), t_duration(q)). The number of times face(i) is photographed in hot_zoi(j) can be obtained as cap_num(hot_zoi(j),t_duration(q)). After obtaining the number of shots of each camera in hot_zoi(j), the sum of the number of shots of the target user taken by each camera in the current hot spot area can be obtained, that is, the sum of the number of shots can be expressed as:

[0097]

[0098] S340: For each hot spot area, based on the shooting frequency of each camera device in the current hot spot area and the camera position information of the corresponding camera device, determine the target position information of the target user in the current hot spot area.

[0099] The relative position information can be determined by establishing a spatial rectangular coordinate system based on a preset reference position (e.g., an entrance to a scenic spot) as the coordinate origin, and determining the relative position information based on the spatial rectangular coordinate system. The absolute position information can be longitude and latitude information. The camera position information can be the position information of the camera device in an area, and the position information can be relative position information or absolute position information.

[0100] Specifically, when it is determined that the shooting frequency of each camera device in each hot spot area shooting the target user is completed, the device identification, shooting frequency and corresponding device location information of the camera device that shoots the target user can be determined by traversing each camera device in a hot spot area. When it is determined that the device identification, shooting frequency and corresponding device location information of the camera device that shoots the target user in a hot spot area are completed, the target location information of the target user in a hot spot area can be determined. When the target location information of the user in a hot spot area is determined, the target location information of the user in each hot spot area can be determined by traversing each hot spot area.

[0101] Exemplarily, the device identification of the camera device that photographs the target user is k, the shooting frequency is 10 times, and the location information of the camera device is 116 degrees 23 minutes 29.22 seconds east longitude and 39 degrees 54 minutes 26.37 seconds north latitude.

[0102] In order to reduce the redundancy of the target user's trajectory data, based on the shooting frequency of each camera device in the current hotspot area and the camera position information of the corresponding camera device, the target position information of the target user in the current hotspot area is determined, which can include: determining the weight value of the corresponding camera device according to the shooting frequency of each camera device in the current hotspot area taking pictures including the target user; determining the target position information of the target user in the current hotspot area based on the weight value of each camera device and the position information of the corresponding camera device.

[0103] The weight value of the camera device may be: the ratio of the number of times a camera device takes photos of the target user in a hot spot area to the sum of the number of times all cameras in the current hot spot area take photos of the target user. The weight value of the camera device may be represented by w, that is, the weight value of the camera device may be represented as:

[0104]

[0105] Wherein, based on the weight value of each camera device and the location information of the corresponding camera device, determining the target location information of the target user in the current hot spot area may include: based on the weight value of each camera device in a hot spot area, marking the location information of the camera device corresponding to each camera device. When the marking of the location information of each camera device is completed, the number of cameras can be determined. Taking one camera device as an example, the longitude of the camera device can be multiplied by the corresponding weight value, and the latitude of the camera device can be multiplied by the weight value. According to the weight value of each camera device, the longitude and latitude of each camera device are respectively multiplied by the corresponding weight value.

[0106] Specifically, after multiplying the longitude and latitude of each camera device by the corresponding weight value, the results of multiplying the longitude of each camera device by the corresponding weight value can be summed, and the summed result can be used as the longitude of the hotspot area, that is, the longitude of the target user in the hotspot area can be obtained. At the same time, the results of multiplying the latitude of each camera device by the corresponding weight value can be summed, and the summed result can be used as the latitude of the hotspot area, that is, the latitude of the target user in the hotspot area can be obtained. When the longitude and latitude of the target user in the hotspot area are obtained, the target position information of the target user in the hotspot area can be determined.

[0107] Exemplarily, the hotspot area is a square area, and a camera is deployed at each vertex of the square area, wherein the longitude of camera 1 is Lon1 and the latitude is Lat1, the longitude of camera 2 is Lon2 and the latitude is Lat2, the longitude of camera 3 is Lon3 and the latitude is Lat3, and the longitude of camera 4 is Lon4 and the latitude is Lat4. Each camera shoots the target user 25 times, and the sum of the times the four cameras in the hotspot area shoot the target user is 100 times, so the weight of a camera is 25 / 100=0.25. The longitude of the user in the hotspot area is 0.25*Lon1+0.25*Lon2+0.25*Lon3+0.25*Lon4, and the latitude is 0.25*Lat1+0.25*Lat1+0.25*Lat1+0.25*Lat1, that is, the location information of the target user in the hotspot area is obtained.

[0108] S350: Determine target trajectory information corresponding to the target user based on at least one target position information corresponding to each original trajectory sub-data.

[0109] The technical solution of this embodiment determines the hot spot area corresponding to the target user from multiple areas according to the original trajectory sub-data. For each hot spot area, the shooting frequency of each camera device in the current hot spot area shooting the target user is determined, and the target position information of the target user in the current hot spot area is determined based on the shooting frequency of each camera device in the current hot spot area and the camera position information of the corresponding camera device. Based on at least one target position information corresponding to each original trajectory sub-data, the target trajectory information corresponding to the target user is determined, which solves the technical problems that the trajectory generation method in the prior art has high redundancy in the time and space dimensions, difficulty in storing trajectory data, and high difficulty in calculation and processing when analyzing the subsequent trajectory data, and achieves the technical effect of reducing the redundancy of trajectory data and data storage difficulty, as well as reducing the difficulty of calculation and processing when analyzing the subsequent trajectory data.

[0110] Embodiment 4

[0111] Figure 5 1 is a flow chart of a trajectory generation method provided by the fourth embodiment of the present invention, and the fourth embodiment of the present invention is an optional embodiment of the present invention. The specific implementation method thereof can be referred to the following embodiments. Among them, the technical terms that are the same as or corresponding to the above embodiments are not repeated here.

[0112] Figure 61 is a schematic diagram of a trajectory generation system module provided by Embodiment 4 of the present invention. The trajectory generation system is a trajectory generation core service module 510. The trajectory generation core service module 510 may include: a parameter configuration submodule 520, a face capture and recognition submodule 530, a key personnel face data storage submodule 540, a geographic annotation submodule 550, a target trajectory calculation submodule 560 and a trajectory generation submodule 570.

[0113] Among them, the trajectory generation core service module 510 can be used to generate the target trajectory information of the target user; the parameter configuration submodule 520 can be used to configure the area identification, the device identification of the camera (camera), and the time information; the face capture and recognition submodule 530 can be used to capture the user and identify the user's facial image data to determine the user's user identification; the key personnel face data storage submodule 540 can be used to store the face image data of the target user; the geographic annotation submodule 550 can be used to configure the mapping relationship between the area and the camera (camera); the target trajectory calculation submodule 560 can be used to calculate the original trajectory subdata of the target user; the trajectory generation submodule 570 can be used to generate the target trajectory information corresponding to the target user based on the calculated original trajectory subdata.

[0114] Based on the above trajectory generation core service module, this embodiment provides a trajectory generation method, and its specific implementation method can refer to the technical solution of this embodiment.

[0115] like Figure 5 As shown, the method of this embodiment may specifically include:

[0116] S401, start the trajectory generation core service module.

[0117] Among them, the person who starts the trajectory generation core service module can be an administrator.

[0118] S402, determining whether the trajectory generation core service module is started for the first time, if so, executing S403; if not, executing S404.

[0119] S403, configuring the position information of the camera device;

[0120] Among them, the configuration information for configuring the location information of the camera device may include: configuring the mapping relationship between the zoi (area) and the camera device, and configuring the time information (such as T=7 days, t_duration=1 day), and R (preset number of shots, such as R=10), and wander_interval (preset shooting interval, such as wander_interval=2hour), and S (preset number of camera devices, such as S=3).

[0121] S404: Determine whether the camera device captures a target image including a target user.

[0122] S405 , obtaining the original trace data path trace_origin(faceid(i)).

[0123] Exemplarily, the target user is faceid(i), and the original trace data of the target user is trace_origin(faceid(i)).

[0124] S406 , dividing the time T (preset duration) of trajectory data analysis into p (preset number) time subsets, and initializing the traversal area identifier (zoi_id=1).

[0125] Among them, initialization traversal zoi_id=1 can be understood as traversing the area based on the area identifier.

[0126] S407 . For each time subset T_duration(q)=[T(q),(q+1)],q∈[1,p], obtain the currently traversed zoi_id.

[0127] For example, if the preset number is p, the preset duration (T) is divided into q time periods, that is, the time periods can be [T(1)~T(2)],…,[T(q),T(q+1)]. Among them, the original trajectory data corresponding to the qth time period is t_duration(q), and the time period corresponding to t_duration(p) is [T(q),T(q+1)].

[0128] S408, determine whether the time interval of repeated capture is less than or equal to wander_interval, if so, execute S409; if not, execute S412.

[0129] S409, determine whether the number of repeated captures is greater than or equal to R, if so, execute S410; if not, execute S412.

[0130] S410, determining whether the number of camera devices photographing the target user is greater than or equal to S, if so, executing S411; if not, executing S412.

[0131] S411. Determine the hot spot area hot_zoi(j) of faceid(i) (target user) in zoi(j) in time period t_duration(q), and update the data.

[0132] S412, loop to determine whether each zoi_id has been traversed, if so, execute S414; if not, execute S412.

[0133] S413, traverse zoi (area) and execute S407.

[0134] S414. For each time subset T_duration(q)=[T(q),T(q+1)],q∈[1,p], traverse each hot_zoi (hot spot area).

[0135] S415, obtain the capture times of each camera cap_num (camera(k), t_duration(q)).

[0136] S416, obtain the total number of times user faceid(i) is captured in hot_zoi, cap_num(hot_zoi(j), t_duration(q))

[0137] S417, calculate the target location Location_w(hot_zoi(j), t_duration(q)) of the target user at the current hotspot hot_zoi(j).

[0138] S418, loop to determine whether each hot_zoi is traversed, if so, execute S420; if not, execute S419.

[0139] S419: Merge the target positions in the hot spot area in p sub-time periods to obtain trace_hot_zoi_statistic(faceid(i)) (target trajectory information of the target user in the current hot spot area).

[0140] S420, traverse hot_zoi and execute S414.

[0141] S421 , query the trajectory of user faceid(i): original trajectory data trace_origin; and / or original trajectory sub-data trace_hot_zoi_statistic.

[0142] The technical solution of this embodiment realizes compression processing of multiple original trajectory data, and can clearly obtain the user's trajectory data, solves the technical problems of high redundancy of trajectory data, difficulty in storing trajectory data, and high difficulty in calculation and processing when analyzing subsequent trajectory data in the trajectory generation method in the prior art, and achieves the technical effect of reducing the redundancy of trajectory data and the difficulty of data storage, as well as reducing the difficulty of calculation and processing when analyzing subsequent trajectory data.

[0143] Embodiment 5

[0144] Figure 76 is a schematic diagram of a trajectory generation device module provided in Embodiment 5 of the present invention. The present invention provides a trajectory generation device, which includes: an original trajectory sub-data division module 610, a target position information determination module 620 and a target trajectory information determination module 630.

[0145] Among them, the original trajectory sub-data division module 610 is used to obtain the original trajectory data corresponding to the target user, and divide the original trajectory data into at least one original trajectory sub-data according to the time information; the target position information determination module 620 is used to determine the target position information corresponding to the target user in each area based on the original trajectory sub-data; the target trajectory information determination module 630 is used to determine the target trajectory information corresponding to the target user based on at least one target position information corresponding to each original trajectory sub-data.

[0146] The technical solution of this embodiment obtains the original trajectory data corresponding to the target user through the original trajectory sub-data division module, and can obtain the shooting time of the original trajectory data of the target user, the device identification of the camera device and the location information of the camera device, and divide the original trajectory data into at least one original trajectory sub-data according to the time information. The target location information determination module determines the target location information corresponding to the target user in each area based on the original trajectory sub-data. The target trajectory information determination module determines the target trajectory information corresponding to the target user based on at least one target location information corresponding to each original trajectory sub-data, realizes the compression processing of multiple original trajectory data, and can clearly obtain the user's trajectory data, solves the technical problems of high redundancy of trajectory data, difficulty in storing trajectory data, and high difficulty in calculating and processing when analyzing subsequent trajectory data in the trajectory generation method in the prior art, and achieves the technical effect of reducing the redundancy of trajectory data and data storage difficulty, as well as reducing the difficulty of calculating and processing when analyzing subsequent trajectory data.

[0147] Optionally, before acquiring the original trajectory data corresponding to the target user, it also includes: an original trajectory data retrieval module, which is used to capture a target image including the target user based on a camera device pre-set in each area; and generate trajectory data stored in a target storage location based on the target image, so as to retrieve the original trajectory data from the target storage location when receiving an instruction to generate target trajectory information.

[0148] Optionally, the original trajectory data retrieving module is used to retrieve the original trajectory data of the target user within a preset time period from the target storage location when receiving the instruction to generate the target trajectory information.

[0149] Optionally, the original trajectory sub-data division module 610 is configured to divide the original trajectory data into at least one original trajectory sub-data according to the data generation time of the original trajectory data and a preset time interval.

[0150] Optionally, a target position information determination module 620 is used to determine a hot spot area corresponding to the target user from multiple areas based on the original trajectory sub-data; the hot spot area includes at least one camera device; for each hot spot area, the shooting frequency of each camera device in the current hot spot area shooting the target user is determined; for each hot spot area, based on the shooting frequency of each camera device in the current hot spot area and the camera position information of the corresponding camera device, the target position information of the target user in the current hot spot area is determined.

[0151] Optionally, the target position information determination module 620 is used to determine the shooting interval, the number of repeated shootings and the number of camera devices that shoot the target user in one of the areas based on the original trajectory sub-data; based on the shooting interval, the number of repeated shootings and the number of camera devices, determine the hot spot area corresponding to the target user from multiple areas.

[0152] Optionally, a target location information determination module is used to define the area to which the camera device belongs as a hotspot area when the shooting interval is less than a preset shooting interval, the number of repeated shootings is greater than or equal to a preset number of shootings, and the number of camera devices is greater than or equal to a preset number of camera devices.

[0153] Optionally, the target location information determination module 620 is used to determine, for each hotspot area, the number of times each camera device in the current hotspot area takes photos including the target user, based on the original trajectory sub-data corresponding to the current hotspot area.

[0154] Optionally, the target location information determination module 620 is used to determine the weight value of the corresponding camera device according to the shooting frequency of each camera device including the target user in the current hot spot area; based on the weight value of each camera device and the location information of the corresponding camera device, determine the target location information of the target user in the current hot spot area; wherein the target location information includes longitude and latitude information.

[0155] Optionally, the original trajectory sub-data includes a device identification of the camera device, location information of the camera device, shooting time, and a user identification of the target user.

[0156] Optionally, the target trajectory information determining module 630 is configured to determine the target trajectory information corresponding to the target user by performing splicing processing on at least one target position information corresponding to each original trajectory sub-data.

[0157] Optionally, after obtaining the target trajectory information, the method further includes: a target trajectory information sending module, configured to send the target trajectory information to a target terminal, so that the target terminal processes data of each area according to the received target trajectory information.

[0158] The above-mentioned device can execute the trajectory generation method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the trajectory generation method.

[0159] It is worth noting that the various units and modules included in the above-mentioned trajectory generation device are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be realized; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the protection scope of the embodiments of the present invention.

[0160] Embodiment 6

[0161] Figure 8 It is a structural schematic diagram of an electronic device provided in Embodiment 6 of the present invention. Figure 8 A block diagram of an exemplary electronic device 12 suitable for implementing any of the embodiments of the present invention is shown. Figure 8 The electronic device 12 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention. The device 12 is typically an electronic device that is responsible for processing configuration information.

[0162] like Figure 8 As shown, the electronic device 12 is in the form of a general purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a memory 28, and a bus 18 connecting the various components (including the memory 28 and the processing unit 16).

[0163] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures. For example, these architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.

[0164] The electronic device 12 typically includes a variety of computer readable media. These media can be any available media that can be accessed by the electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0165] The memory 28 may include computer device readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 8 Not shown, usually referred to as a "hard drive"). Although not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (such as a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (such as a read-only optical disk (Compact Disc-Read Only Memory, CD-ROM), a digital video disk (Digital Video Disc-Read Only Memory, DVD-ROM) or other optical media) can be provided. In these cases, each drive can be connected to the bus 18 via one or more data medium interfaces. The memory 28 can include at least one program product 40, which has a set of program modules 42, which are configured to perform the functions of various embodiments of the present invention. The program product 40 can be stored in, for example, the memory 28, and such program modules 42 include but are not limited to one or more application programs, other program modules and program data, each of which or some combination of these examples may include the implementation of a network environment. The program module 42 generally performs the functions and / or methods in the embodiments described in the present invention.

[0166] The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboard, mouse, camera, etc., and display), may also communicate with one or more devices that enable a user to interact with the electronic device 12, and / or communicate with any device that enables the electronic device 12 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication may be performed through an input / output (I / O) interface 22. In addition, the electronic device 12 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN) and / or a public network, such as the Internet) through a network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 through a bus 18. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, disk arrays (Redundant Arrays of Independent Disks, RAID) devices, tape drives, and data backup storage devices.

[0167] The processor 16 executes various functional applications and data processing by running the program stored in the memory 28, for example, implementing the trajectory generation method provided in the above embodiment of the present invention, the method comprising:

[0168] Original trajectory data corresponding to a target user is acquired, and the original trajectory data is divided into at least one original trajectory sub-data according to time information; target position information corresponding to the target user in each area is determined based on the original trajectory sub-data; and target trajectory information corresponding to the target user is determined based on at least one target position information corresponding to each original trajectory sub-data.

[0169] Of course, those skilled in the art can understand that the processor can also implement the technical solution of the trajectory generation method provided by any embodiment of the present invention.

[0170] Embodiment 7

[0171] Embodiment 7 of the present invention further provides a computer-readable storage medium on which a computer program is stored, characterized in that when the program is executed by a processor, for example, the trajectory generation method provided in the above embodiment of the present invention includes:

[0172] Acquire original trajectory data corresponding to the target user, and divide the original trajectory data into at least one original trajectory sub-data according to time information;

[0173] Determining target location information corresponding to the target user in each area based on the original trajectory sub-data;

[0174] Based on at least one target position information corresponding to each original trajectory sub-data, target trajectory information corresponding to the target user is determined.

[0175] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0176] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0177] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0178] Computer program code for performing the operation of embodiments of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0179] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A trajectory generation method, characterized in that: include: Acquire original trajectory data corresponding to the target user, and divide the original trajectory data into at least one original trajectory sub-data according to time information; Determining target location information corresponding to the target user in each area based on the original trajectory sub-data; Determining target trajectory information corresponding to the target user based on at least one target position information corresponding to each original trajectory sub-data; The determining, based on the original trajectory sub-data, target location information corresponding to the target user in each area includes: Determine, according to the original trajectory sub-data, a hot spot area corresponding to the target user from a plurality of areas, wherein the hot spot area includes at least one camera device; For each hot spot area, determining the shooting frequency of each camera device shooting the target user in the current hot spot area; For each hot spot area, based on the shooting frequency of each camera device in the current hot spot area and the camera position information of the corresponding camera device, determine the target position information of the target user in the current hot spot area; Wherein, determining the target location information of the target user in the current hot spot area based on the shooting frequency of each camera device in the current hot spot area and the camera location information of the corresponding camera device includes: Determine the weight value of the corresponding camera device according to the shooting frequency of each camera device shooting the target user in the current hot spot area; Based on the weight value of each camera device and the location information of the corresponding camera device, determine the target location information of the target user in the current hot spot area; wherein the target location information includes longitude and latitude information; The step of determining the target location information of the target user in the current hotspot area based on the weight value of each camera device and the location information of the corresponding camera device includes: Based on the weight value of each camera device in each hot spot area, the position information of the camera device corresponding to each camera device is marked to determine the number of the camera devices; For each camera device, multiply the longitude of the camera device by the weight value of the longitude, and multiply the latitude of the camera device by the weight value of the latitude; The result of summing the multiplication results of the longitudes is used as the longitude of the hotspot area, and the result of summing the multiplication results of the latitudes is used as the latitude of the hotspot area, and the target location information of the target user in the hotspot area is determined according to the longitude and latitude of the hotspot area.

2. The method according to claim 1, characterized in that Before obtaining the original trajectory data corresponding to the target user, the method further includes: Based on the camera devices pre-set in each area, capturing a target image including a target user; The trajectory data stored in the target storage location is generated based on the target image, so that when an instruction to generate target trajectory information is received, the original trajectory data is retrieved from the target storage location.

3. The method according to claim 2, characterized in that The obtaining of original trajectory data corresponding to the target user includes: When the instruction to generate the target trajectory information is received, the original trajectory data of the target user within a preset time period is retrieved from the target storage location.

4. The method according to claim 1, characterized in that: The dividing the original trajectory data into at least one original trajectory sub-data according to the time information includes: The original trajectory data is divided into at least one original trajectory sub-data according to the data generation time of the original trajectory data and a preset time interval.

5. The method according to claim 1, characterized in that The step of determining a hotspot area corresponding to the target user from a plurality of areas according to the original trajectory sub-data includes: Determine, according to the original trajectory sub-data, a shooting interval, a number of repeated shootings, and a number of camera devices that shoot the target user in one of the areas; Based on the shooting interval, the number of repeated shootings and the number of camera devices, a hot spot area corresponding to the target user is determined from multiple areas.

6. The method according to claim 5, characterized in that The determining a hotspot area corresponding to the target user from a plurality of areas based on the shooting interval, the number of repeated shootings, and the number of camera devices includes: When the shooting interval is less than a preset shooting interval, the number of repeated shootings is greater than or equal to a preset number of shootings, and the number of camera devices is greater than or equal to a preset number of camera devices, the area to which the camera devices belong is regarded as a hot spot area.

7. The method according to claim 1, characterized in that The step of determining, for each hot spot area, the shooting frequency of each camera device in the current hot spot area shooting the target user includes: For each hot spot area, the number of times each camera device takes photos including the target user in the current hot spot area is determined according to the original trajectory sub-data corresponding to the current hot spot area.

8. The method according to any one of claims 1 to 7, characterized in that: The original trajectory sub-data includes a device identification of the camera device, location information of the camera device, shooting time, and a user identification of the target user.

9. The method according to claim 1, characterized in that: The determining the target trajectory information corresponding to the target user based on at least one target position information corresponding to each original trajectory sub-data includes: The target trajectory information corresponding to the target user is determined by performing splicing processing on at least one target position information corresponding to each original trajectory sub-data.

10. The method according to claim 1, characterized in that After obtaining the target trajectory information, the method further includes: The target trajectory information is sent to the target terminal, so that the target terminal processes the data of each area according to the received target trajectory information.

11. A trajectory generating device, characterized in that: include: an original trajectory sub-data division module, configured to obtain original trajectory data corresponding to a target user, and divide the original trajectory data into at least one original trajectory sub-data according to time information; A target location information determination module, used to determine the target location information corresponding to the target user in each area based on the original trajectory sub-data; a target trajectory information determination module, configured to determine the target trajectory information corresponding to the target user based on at least one target position information corresponding to each original trajectory sub-data; The target location information determination module is used to: According to the original trajectory sub-data, a hot spot area corresponding to the target user is determined from multiple areas; the hot spot area includes at least one camera device; for each hot spot area, a shooting frequency of each camera device in the current hot spot area shooting the target user is determined; for each hot spot area, based on the shooting frequency of each camera device in the current hot spot area and the camera position information of the corresponding camera device, the target position information of the target user in the current hot spot area is determined; The target location information determination module is used to: Determine the weight value of the corresponding camera device according to the shooting frequency of each camera device in the current hot spot area including the target user; determine the target location information of the target user in the current hot spot area based on the weight value of each camera device and the location information of the corresponding camera device; wherein the target location information includes latitude and longitude information; The target location information determination module is specifically used to: Based on the weight value of each camera device in each hot spot area, the position information of the camera device corresponding to each camera device is marked to determine the number of the camera devices; For each camera device, multiply the longitude of the camera device by the weight value of the longitude, and multiply the latitude of the camera device by the weight value of the latitude; The result of summing the multiplication results of the longitudes is used as the longitude of the hotspot area, and the result of summing the multiplication results of the latitudes is used as the latitude of the hotspot area, and the target location information of the target user in the hotspot area is determined according to the longitude and latitude of the hotspot area.

12. An electronic device, characterized in that: The electronic device comprises: one or more processors; A storage device for storing one or more programs; When the program is executed by the processor, the processor implements the trajectory generation method as described in any one of claims 1-10.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the trajectory generation method as described in any one of claims 1 to 10 is implemented.

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