WO2022127553A1 - 热点路线分析方法、装置、电子设备及存储介质 - Google Patents
热点路线分析方法、装置、电子设备及存储介质 Download PDFInfo
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- G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
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Definitions
- the invention relates to the field of archive data processing, and in particular to a method, device, electronic device and storage medium for analyzing a hotspot route.
- the urban population structure can be roughly divided into resident population and floating population.
- the scale of the floating population continues to expand. Due to the uncertainty of the floating population on the spatial scale and time scale, such as the uncertainty of the travel route and the uncertainty of the travel time of the floating population, under such uncertainty, the flow of The expansion of population has brought great difficulties to urban management, especially grassroots management is becoming more and more difficult.
- the traditional method is to register the floating population through the grass-roots police, and conduct regular visits to understand the situation of the floating population, so as to manage it.
- the grass-roots police have heavy work tasks and shortage of police resources.
- the mode of interview and inquiry is very inefficient, and the information obtained by the interview and inquiry is subjectively disclosed information, and there may be inaccurate information, resulting in unclear numbers of floating population in some jurisdictions and unknown conditions. Therefore, in the existing management of mobile personnel, there is a problem that it is difficult to obtain information on mobile personnel.
- the embodiment of the present invention provides a hotspot route analysis method, which can analyze the hotspot route of the mobile personnel through the traffic trajectory of the mobile personnel, so as to reduce the difficulty of obtaining information of the mobile personnel.
- an embodiment of the present invention provides a method for analyzing a hotspot route, the method comprising:
- the snapshot track information includes the personnel snapshot data of the target person, and the personnel snapshot data of the target person includes the target The capture time of the person and the code of the public transport unit;
- the hotspot route of the target person in the second preset time period is determined, and the second preset time period includes a plurality of first preset time periods.
- the acquiring the captured track information of the target person in the first preset time period includes:
- Obtaining personnel snapshot data collected by a snapshot device on a public transportation unit where the personnel snapshot data includes the person's face image, the snapshot time, the capture device code, and the public transportation unit code;
- the personnel snapshot data is archived to obtain the snapshot personnel file, and stored in the file information database;
- the target person file includes the person snapshot data of the target person
- the snapshot track information of the target person within the first preset time period is acquired.
- the method further includes:
- the face image of the person to be analyzed is the face image of the mobile person, the person to be analyzed is determined to be the target person.
- the determining the route code of the target person in the first preset time period based on the captured track information and the track information of the public transport unit includes:
- the travel trajectory is verified according to a preset verification rule, and the verified travel trajectory is determined as the route code of the target person in the first preset time period.
- the verification rule is that the itinerary track includes a plurality of snapshot data of the person, and the verification of the itinerary track according to a preset verification rule includes:
- the travel track includes multiple personnel snapshot data of the target person, it is determined that the travel track has passed the verification
- the travel track includes only one person snapshot data of the target person, it is determined that the travel track has not passed the verification.
- determining the verified travel track as the route code of the target person in the first preset time period including:
- the route code of the target person in the first preset time period is determined.
- determining the hotspot route of the target person in the second preset time period according to the route code of the target person in the first preset time period includes:
- an embodiment of the present invention further provides a hotspot route analysis device, the device comprising:
- the first acquisition module is configured to acquire the snapshot track information of the target person in the first preset time period, where the target person is a mobile person, and the snapshot track information includes the person snapshot data of the target person, and the target person's snapshot data.
- the personnel snapshot data includes the snapshot time of the target person and the code of the public transportation unit;
- a second acquisition module configured to acquire the public transport unit trajectory information corresponding to the public transport unit code in the first preset time period, where the public transport unit trajectory information includes the station code and the arrival time at the station;
- the first determination module is used to determine the route code of the target person in the first preset time period based on the captured track information and the public transport unit track information, and each of the route codes corresponds to a route;
- the second determination module is configured to determine the hotspot route of the target person in the second preset time period according to the route code of the target person in the first preset time period, and the second preset time period includes a plurality of the first preset time period.
- an embodiment of the present invention provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, when the processor executes the computer program The steps in the hotspot route analysis method provided by the embodiment of the present invention are implemented.
- an embodiment of the present invention provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, implements the hotspot route analysis method provided by the embodiment of the present invention. A step of.
- the snapshot trajectory information of the target person in the first preset time period is acquired, the target person is a mobile person, and the snapshot trajectory information includes the personnel snapshot data of the target person, the personnel of the target person
- the snapshot data includes the snapshot time of the target person and the public transportation unit code; obtain the public transportation unit trajectory information corresponding to the public transportation unit code in the first preset time period, and the public transportation unit trajectory information includes the station.
- the present invention can acquire the traffic track of the migrants through the snapshot data of the migrants, and then analyze the hotspot routes of the migrants through the traffic tracks of the migrants, thereby reducing the difficulty of obtaining the information of the migrants.
- FIG. 1 is a flowchart of a method for analyzing a hotspot route provided by an embodiment of the present invention
- FIG. 2 is a flowchart of a method for acquiring snapshot track information provided by an embodiment of the present invention
- FIG. 3 is a schematic structural diagram of a hot spot route analysis device provided by an embodiment of the present invention.
- FIG. 4 is a schematic structural diagram of a first acquisition module provided by an embodiment of the present invention.
- FIG. 5 is a schematic structural diagram of another hotspot route analysis device provided by an embodiment of the present invention.
- FIG. 6 is a schematic structural diagram of a first determination module provided by an embodiment of the present invention.
- FIG. 7 is a schematic structural diagram of a syndrome submodule provided by an embodiment of the present invention.
- FIG. 8 is a schematic structural diagram of another syndrome submodule provided by an embodiment of the present invention.
- FIG. 9 is a schematic structural diagram of a second determination module provided by an embodiment of the present invention.
- FIG. 10 is a schematic structural diagram of an electronic device provided by an embodiment of the present invention.
- FIG. 1 is a flowchart of a method for analyzing a hotspot route provided by an embodiment of the present invention. As shown in FIG. 1, the method includes the following steps:
- the target person is a mobile person
- the snapshot track information includes the person snapshot data of the target person
- the person snapshot data of the target person includes the capture time of the target person and the public transportation unit code.
- the above-mentioned mobile personnel can be compared according to the facial image of the target person by comparing the feature values in the personnel identity information database, and judged according to the comparison result.
- the above-mentioned personnel identity information database stores the personnel identity information of the resident personnel and floating personnel in the city. Further, after feature comparison, if a person is neither a resident person nor a mobile person, it can be judged as a mobile person.
- the above-mentioned personal identity information may be structured or semi-structured information, and the above-mentioned structured or semi-structured personal identity information includes information such as face image, name, household registration, address, ID card number, and the like.
- the above-mentioned first preset time period may be set by the user, for example, a time period such as 1 hour, 12 hours, 1 day, 15 days, and 1 month.
- the person snapshot data of the above-mentioned target person may be image data collected by a snapshot device set on a public transportation unit, and the person snapshot data of the target person may include the target person's face image, snapshot time, snapshot device code and public information. Traffic unit code.
- the snapshot track information of the target person can be represented by the snapshot time of the target person and the code of the public transportation unit.
- the above-mentioned capture device code may be an international code of the capture device, and the above-mentioned capture device may be set on a public transportation unit and bound with the public transportation unit. It can be understood that the code of the capture device and the code of the public transportation unit are bound together.
- the above-mentioned public transportation unit code can be understood as the identification of a public transportation vehicle.
- each public transportation vehicle has a unique identification, and the unique identification can be a license plate number or an internal number of a public transportation system.
- the above-mentioned public transport units may be urban public transport vehicles for public travel, such as buses, subways, light rails, taxis, and the like.
- the above-mentioned capture devices are installed at the upper and lower doors of public transportation units. For public transportation units with multiple upper and lower doors, a capture device can be installed at each upper and lower door. Further, multiple capture devices can be jointly bound to a public transportation unit. .
- the floating population has uncertainty in the spatial and temporal dimensions. Therefore, most of the means of travel are urban public transport. Therefore, the hotspot activity routes of the floating population can be carried out using the traffic routes of the floating population. express.
- FIG. 2 is a flowchart of a method for acquiring snapshot track information provided by an embodiment of the present invention. As shown in FIG. 2, the method includes the following steps:
- the above-mentioned person snapshot data includes the person's face image, the snapshot time, the snapshot device code, and the public transportation unit code.
- the above-mentioned face image of the capturing person may be obtained by performing face detection on the image collected by the capturing device through a face detection engine, and is a small image including the face of the capturing person.
- a feature extraction engine can be used to extract features from a face image to obtain a feature value of the person's face.
- the image feature values are compared for feature values.
- the above feature value comparison can be used to calculate the similarity between the feature values of two face images. The higher the similarity, the closer it is. When the similarity reaches the threshold, it can be Confirm the corresponding identity information as the identity information of the capturing person.
- all the person's snapshot data are clustered and archived to obtain the person's file.
- the above-mentioned file information database stores the snapshot personnel files corresponding to all the snapshot personnel. Since the person snapping data includes human faces, you can enter the face image in the snapping person file library to find the corresponding snapping person file.
- the snapshot personnel files of the resident personnel and the mobile personnel can be stored separately to obtain the resident personnel archives and the mobile personnel archives. In this way, when the mobile personnel files need to be obtained, the mobile personnel can be directly In this way, the search scope can be reduced and the search speed can be improved.
- the face image of the person to be analyzed can be searched in the file information database, and the feature value comparison between the face image of the person to be analyzed and the face image in the snapshot file can be used to determine the Target personnel files, the above target personnel files include personnel snapshot data of the target personnel.
- the face image of the person to be analyzed may be obtained first; the feature value comparison of the face image of the person to be analyzed in the personnel identity information database is performed to determine the face image of the person to be analyzed. Whether it is the face image of the mobile person; if the face image of the person to be analyzed is the face image of the mobile person, it is determined that the person to be analyzed is the target person; at this time, the target person file can be searched in the mobile personnel file library.
- the target personnel file includes the personnel snapshot data of the target person
- the personnel snapshot data of the target person includes the target person's face image, the capture time, the capture device code, and the public transportation unit code, and the capture time can be extracted.
- the code of the public transport unit as the captured track information of the target person.
- An embodiment of the present invention provides a data structure for capturing track information, including capturing time, capturing device code, and public transportation unit encoding.
- the data structure of capturing track information may be as shown in Table 1:
- the captured track information of the target person that matches the first preset time period may be filtered out in the target file. For example, to filter out the captured track information of the target person on a certain day.
- the first preset time period can also be input as the search condition. In this way, the files without the captured personnel data within the first preset time period can be filtered out, and further Narrow your search.
- the track information of the public transportation unit includes the station code and the arrival time at the station.
- the above-mentioned trajectory information of public transport units may be the operation data of public transport units in the public transport service information database, that is, at what time and which station a public transport unit arrives at. Information compiled into the nearest site.
- the above-mentioned public transportation unit trajectory information can be understood as the travel route of the public transportation.
- the above site code identifies a site, and a site code corresponds to a site, and the site can be understood as a stop site of a public transport unit.
- the corresponding public transportation unit trajectory information can be obtained in the public transportation service information database according to the public transportation unit code that appears in the captured trajectory information of the target person.
- the embodiment of the present invention provides a public transportation unit trajectory information data structure, including the public transportation unit code, the arrival time and the station code.
- the data structure of the public transportation unit trajectory information can be as shown in Table 2:
- each route code corresponds to a route
- the above-mentioned route may be a section of a journey on the driving route of a public transportation unit.
- the driving route of a public transportation unit is site A, site B, site C, and site D in sequence.
- station E, station F, station G the route corresponding to the route code can be the route from station A to station B, or the route from station A to station C, further, the route from station A to station B
- the corresponding route code is different from the route code corresponding to the route from station A to station C.
- intersection calculation of the captured trajectory information and the public transportation unit trajectory information may be performed to obtain the travel trajectory of the target person in the first preset time period.
- the travel trajectory is verified according to a preset verification rule, and the verified travel trajectory is determined as the route code of the target person in the first preset time period.
- the above-mentioned travel trajectory includes the personnel snapshot data of the target person.
- the trajectory information of the public transportation unit code GJ1GJ1214419004J06M4 is found in the public transportation service information database, as shown in Table 2, and the intersection operation is performed on Table 2 and Table 1.
- the travel trajectory can be obtained as (2020/10/01-09:00:01, ST123416), (2020/10/01-09:09:12, ST674237), (2020/10/01-09:14:17 , ST234234), in the above travel trajectory, the personnel snapshot data of the target person is the snapshot time.
- the above verification rule is that the itinerary track includes multiple personnel snapshot data. Specifically, it can be determined whether the above-mentioned itinerary track includes the personnel snapshot data of multiple target persons; if the aforesaid itinerary track includes multiple target persons. If the above-mentioned travel trajectory only includes the personnel snapshot data of one target person, it is judged that the travel trajectory has not passed the verification.
- the above-mentioned itinerary track includes personnel snapshot data of a plurality of target persons, it can be indicated that the target persons have been captured and photographed multiple times on the public transport unit. Further, the earliest snapshot time and latest snapshot time in the verified travel track can be extracted, and the first arrival site time can be determined according to the earliest snapshot time, thereby determining the corresponding first site code according to the first arrival site time, and according to the latest arrival time.
- the late snapshot time determines the time of the second arrival site, so that the corresponding second site code is determined according to the second arrival time, and the route code of the target person in the first preset time period is determined according to the first site code and the second site code.
- the above travel trajectory is (2020/10/01-09:00:01, ST123416), (2020/10/01-09:09:12, ST674237), (2020/10/01-09:14:17 , ST234234), there are three personnel snapshot data (snapshot time) of the target person, it can be considered that the travel trajectory has passed the verification, the earliest snapshot time is 2020/10/01-09:00:01, and the corresponding first site code is ST123416 , the latest snapshot time is 2020/10/01-09:14:17, the corresponding second site code is ST234234, and according to the first site code ST123416 and the second site code ST234234, it is determined that the target person is at the first preset time
- the above itinerary track only includes the personnel snapshot data of one target person, it means that the target person in the itinerary track may be captured only
- the second preset time period includes a plurality of first preset time periods, and the second preset time period may be a time interval such as a month, a quarter, or a year. For example, if the first preset time period is days and the second preset time period is May, the second preset time period includes 31 first preset time periods.
- the second preset time period may be a statistical interval, and the number of route codes in the first preset time period may be counted;
- the N routes corresponding to the route codes are the hot routes of the target person in the second preset time period.
- Table 3 The above sorting of all route codes can be shown in Table 3:
- the number of occurrences is the number of the corresponding route codes in the second preset time period, and the descending order is performed according to the number of occurrences. Hot routes.
- the snapshot trajectory information of the target person in the first preset time period is obtained, the target person is a mobile person, the snapshot trajectory information includes the personnel snapshot data of the target person, the target person's
- the personnel snapshot data includes the snapshot time of the target person and the public transportation unit code; obtain the public transportation unit trajectory information corresponding to the public transportation unit code in the first preset time period, and the public transportation unit trajectory information includes site code and arrival time; based on the captured track information and the track information of the public transport unit, determine the route code of the target person in the first preset time period, and each route code corresponds to a route;
- the hotspot route of the target person in the second preset time period is determined, and the second preset time period includes a plurality of first preset time periods.
- the present invention can acquire the traffic track of the migrants through the snapshot data of the migrants, and then analyze the hotspot routes of the migrants through the traffic tracks of the migrants, thereby reducing the difficulty of
- hotspot route analysis method provided by the embodiment of the present invention can be applied to devices such as mobile phones, monitors, computers, and servers that can perform hotspot route analysis.
- FIG. 3 is a schematic structural diagram of a hotspot route analysis device provided by an embodiment of the present invention. As shown in FIG. 3, the device includes:
- the first acquisition module 301 is configured to acquire snapshot track information of a target person in a first preset time period, where the target person is a mobile person, and the snapshot track information includes the person snapshot data of the target person.
- the personnel snapshot data includes the snapshot time of the target person and the code of the public transportation unit;
- the second obtaining module 302 is configured to obtain the public transportation unit trajectory information corresponding to the public transportation unit code in the first preset time period, where the public transportation unit trajectory information includes the station code and the arrival time at the station;
- the first determination module 303 is configured to determine, based on the captured track information and the track information of the public transport unit, the route code of the target person in the first preset time period, and each route code corresponds to a route ;
- the second determination module 304 is configured to determine the hotspot route of the target person in the second preset time period according to the route code of the target person in the first preset time period, and the second preset time period includes multiple a first preset time period.
- the first obtaining module 301 includes:
- the first acquisition sub-module 3011 is used to acquire the personnel capture data collected by the capture device on the public transport unit, the personnel capture data including the person's face image, the capture time, the capture device code and the public transport unit code;
- the first comparison sub-module 3012 is used to compare the feature values of the face image in the personnel identity information database to obtain the identity information of the captured personnel;
- the filing submodule 3013 is used to archive the personnel snapshot data according to the identity information, obtain the personnel files for snapshots, and store them in the archives information base;
- a determination sub-module 3014 configured to determine a target personnel file based on the file information database, where the target personnel file includes the personnel snapshot data of the target person;
- the second acquisition sub-module 3015 is configured to acquire the snapshot track information of the target person within the first preset time period according to the target person file.
- the device further includes:
- the third acquisition module 305 is used to acquire the face image of the person to be analyzed
- the judgment module 306 is used to compare the feature value of the face image of the person to be analyzed in the personnel identity information database, and judge whether the face image of the person to be analyzed is the face image of a mobile person;
- the third determination module 307 is configured to determine that the person to be analyzed is a target person if the face image of the person to be analyzed is a face image of a mobile person.
- the first determining module 303 includes:
- the calculation sub-module 3031 is used to calculate the intersection of the captured track information and the track information of the public transportation unit to obtain the travel track of the target person in the first preset time period, and the travel track includes the target person personnel capture data;
- the verification sub-module 3032 is configured to verify the travel trajectory according to a preset verification rule, and determine the verified travel trajectory as the route code of the target person in the first preset time period.
- the verification rule is that the travel track includes a plurality of snapshot data of the person, and the verification sub-module 3032 includes:
- the judgment unit 30321 is used for judging whether the travel track includes a plurality of personnel snapshot data of the target personnel
- the first determining unit 30322 is configured to determine that the travel track has passed the verification if the travel track includes multiple personnel snapshot data of the target person;
- the second judging unit 30323 is configured to judge that the travel track has not passed the verification if the travel track includes only the person snapshot data of the target person.
- the syndrome sub-module 3032 further includes:
- the extraction unit 30324 is used to extract the earliest and latest snapshot time in the travel trajectory that has passed the verification;
- a first determining unit 30325 configured to determine the first arrival site time according to the earliest snapshot time, and determine the corresponding first site code according to the first arrival site time;
- the second determining unit 30326 is configured to determine the second arrival site time according to the latest snapshot time, and determine the corresponding second site code according to the second arrival site time;
- the third determining unit 30327 is configured to determine the route code of the target person in the first preset time period according to the first station code and the second station code.
- the second determining module 304 includes:
- the statistics sub-module 3041 is configured to use the second preset time period as a statistical interval to perform quantitative statistics on the route codes of the first preset time period;
- the selection sub-module 3042 is used for sorting all the route codes by quantity, and taking the N routes corresponding to the TOP-N route codes as the hotspot routes of the target person in the second preset time period.
- hotspot route analysis apparatus provided by the embodiment of the present invention may be applied to devices such as mobile phones, monitors, computers, and servers that can perform hotspot route analysis.
- the hotspot route analysis device provided by the embodiment of the present invention can implement each process implemented by the hotspot route analysis method in the above method embodiments, and can achieve the same beneficial effects. In order to avoid repetition, details are not repeated here.
- FIG. 10 is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. As shown in FIG. 10, it includes: a memory 1002, a processor 1001, and a memory 1002 and a processor A computer program running on 1001, where:
- the processor 1001 is used for calling the computer program stored in the memory 1002, and performs the following steps:
- the snapshot track information includes the personnel snapshot data of the target person, and the personnel snapshot data of the target person includes the target The capture time of the person and the code of the public transport unit;
- the hotspot route of the target person in the second preset time period is determined, and the second preset time period includes a plurality of first preset time periods.
- the acquisition of the captured track information of the target person in the first preset time period performed by the processor 1001 includes:
- Obtaining personnel snapshot data collected by a snapshot device on a public transportation unit where the personnel snapshot data includes the person's face image, the snapshot time, the capture device code, and the public transportation unit code;
- the personnel snapshot data is archived to obtain the snapshot personnel file, and stored in the file information database;
- the target person file includes the person snapshot data of the target person
- the snapshot track information of the target person within the first preset time period is acquired.
- processor 1001 further executes the steps of:
- the face image of the person to be analyzed is the face image of the mobile person, the person to be analyzed is determined to be the target person.
- the execution of the processor 1001 to determine the route code of the target person in the first preset time period based on the captured track information and the track information of the public transport unit includes:
- the travel trajectory is verified according to a preset verification rule, and the verified travel trajectory is determined as the route code of the target person in the first preset time period.
- the verification rule is that the travel track includes a plurality of the personnel snapshot data, and the verification of the travel track according to the preset verification rule executed by the processor 1001 includes:
- the travel track includes multiple personnel snapshot data of the target person, it is determined that the travel track has passed the verification
- the travel track includes only one person snapshot data of the target person, it is determined that the travel track has not passed the verification.
- the determination of the verified travel track performed by the processor 1001 as the route code of the target person in the first preset time period includes:
- the route code of the target person in the first preset time period is determined.
- determining the hotspot route of the target person in the second preset time period according to the route code of the target person in the first preset time period executed by the processor 1001 includes:
- the above electronic device may be a mobile phone, a monitor, a computer, a server and other devices that can be applied to hotspot route analysis.
- the electronic device provided in the embodiment of the present invention can implement each process implemented by the hotspot route analysis method in the above method embodiment, and can achieve the same beneficial effect. To avoid repetition, details are not repeated here.
- Embodiments of the present invention further provide a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, implements each process of the hotspot route analysis method provided by the embodiment of the present invention, and can To achieve the same technical effect, in order to avoid repetition, details are not repeated here.
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Abstract
一种热点路线分析方法、装置、电子设备及存储介质,所述方法包括:获取第一预设时间段的目标人员的抓拍轨迹信息,所述目标人员为流动人员(101);获取所述第一预设时间段的与所述公共交通单位编码对应的公共交通单位轨迹信息,所述公共交通单位轨迹信息包括站点编码以及到达站点时间(102);基于所述抓拍轨迹信息与所述公共交通单位轨迹信息,确定所述目标人员在所述第一预设时间段的路线编码,每个所述路线编码对应一条路线(103);根据目标人员在所述第一预设时间段的路线编码,确定所述目标人员在第二预设时间段的热点路线,所述第二预设时间段包括多个第一预设时间段(104)。所述方法能够降低流动人员信息获取的难度。
Description
本申请要求于2020年12月16日提交中国专利局,申请号为202011489564.8、发明名称为“热点路线分析方法、装置、电子设备及存储介质”的中国专利申请的优先权,其全部内容通过引用结合在本申请中。
本发明涉及档案数据处理领域,尤其涉及一种热点路线分析方法、装置、电子设备及存储介质。
随着城市化发展,越来越多的人口流入城市,使得城市人口结构发生变化,城市人口结构大致可以分为常驻人口和流动人口。随着城市的不断发展,流动人口规模不断扩大,由于流动人口在空间尺度和时间尺度上的不确定性,比如流动人口出行路线不确定,出行时间不确定,在这样的不确定性下,流动人口的扩大,为城市管理带来了极大的难题,特别基层管理难度越来越大。传统的方法是通过基层民警对流动人口进行登记,且定期进行查访进行了解流动人口的情况,从而进行管理,但随着流动人口的扩大,基层民警工作任务繁重、警力资源短缺,原有定期上门查访询问的模式效率很低,且查访询问得到的信息都是主观上透露的信息,可能存在信息不准确的情况,从而造成流动人口在部分辖区内底数不清、情况不明。因此,现有的流动人员管理中,存在流动人员信息获取难度大的问题。
发明内容
本发明实施例提供一种热点路线分析方法,能够通过流动人员的交通轨迹对流动人员的热点路线进行分析,降低流动人员信息获取的难度。
第一方面,本发明实施例提供一种热点路线分析方法,所述方法包括:
获取第一预设时间段的目标人员的抓拍轨迹信息,所述目标人员为流动人员,所述抓拍轨迹信息包括所述目标人员的人员抓拍数据,所述目标人员的人 员抓拍数据包括所述目标人员的抓拍时间以及公共交通单位编码;
获取所述第一预设时间段的与所述公共交通单位编码对应的公共交通单位轨迹信息,所述公共交通单位轨迹信息包括站点编码以及到达站点时间;
基于所述抓拍轨迹信息与所述公共交通单位轨迹信息,确定所述目标人员在所述第一预设时间段的路线编码,每个所述路线编码对应一条路线;
根据目标人员在所述第一预设时间段的路线编码,确定所述目标人员在第二预设时间段的热点路线,所述第二预设时间段包括多个第一预设时间段。
可选的,所述获取第一预设时间段的目标人员的抓拍轨迹信息,包括:
获取公共交通单位上的抓拍设备采集的人员抓拍数据,所述人员抓拍数据包括抓拍人员的人脸图像、抓拍时间、抓拍设备编码以及公共交通单位编码;
将所述人脸图像在人员身份信息库中进行特征值比对,得到所述抓拍人员的身份信息;
根据所述身份信息,对所述人员抓拍数据进行归档,得到抓拍人员档案,并存储到档案信息库中;
基于所述档案信息库,确定目标人员档案,所述目标人员档案包括目标人员的人员抓拍数据;
根据所述目标人员档案,获取第一预设时间段内的目标人员的抓拍轨迹信息。
可选的,所述方法还包括:
获取待分析人员的人脸图像;
将所述待分析人员的人脸图像在人员身份信息库中进行特征值比对,判断所述待分析人员的人脸图像是否为流动人员的人脸图像;
若所述待分析人员的人脸图像为流动人员的人脸图像,则确定所述待分析人员为目标人员。
可选的,所述基于所述抓拍轨迹信息与所述公共交通单位轨迹信息,确定所述目标人员在所述第一预设时间段的路线编码,包括:
将所述抓拍轨迹信息与所述公共交通单位轨迹信息进行交集计算,得到所述目标人员在所述第一预设时间段的行程轨迹,所述行程轨迹包括目标人员的人员抓拍数据;
根据预设的校验规则对所述行程轨迹进行校验,将通过校验的行程轨迹确定为所述目标人员在所述第一预设时间段的路线编码。
可选的,所述校验规则为所述行程轨迹中包括多个所述人员抓拍数据,所述根据预设的校验规则对所述行程轨迹进行校验,包括:
判断所述行程轨迹中是否包括多个所述目标人员的人员抓拍数据;
若所述行程轨迹中包括多个所述目标人员的人员抓拍数据,则判定所述行程轨迹通过校验;
若所述行程轨迹中只包括一个所述目标人员的人员抓拍数据,则判断所述行程轨迹未通过校验。
可选的,所述将通过校验的行程轨迹确定为所述目标人员在所述第一预设时间段的路线编码,包括:
提取通过校验的行程轨迹中最早抓拍时间与最晚抓拍时间;
根据所述最早抓拍时间确定第一到达站点时间,并根据所述第一到达站点时间确定对应的第一站点编码;
根据所述最晚抓拍时间确定第二到达站点时间,并根据所述第二到达站点时间确定对应的第二站点编码;
根据所述第一站点编码与所述第二站点编码,确定所述目标人员在所述第一预设时间段的路线编码。
可选的,所述根据目标人员在所述第一预设时间段的路线编码,确定所述目标人员在第二预设时间段的热点路线,包括:
以所述第二预设时间段为统计区间,对所述第一预设时间段的路线编码进行数量统计;
按数量对所有的路线编码进行排序,取前N个路线编码所对应的N个路线为所述目标人员在第二预设时间段的热点路线。
第二方面,本发明实施例还提供一种热点路线分析装置,所述装置包括:
第一获取模块,用于获取第一预设时间段的目标人员的抓拍轨迹信息,所述目标人员为流动人员,所述抓拍轨迹信息包括所述目标人员的人员抓拍数据,所述目标人员的人员抓拍数据包括所述目标人员的抓拍时间以及公共交通单位编码;
第二获取模块,用于获取所述第一预设时间段的与所述公共交通单位编码对应的公共交通单位轨迹信息,所述公共交通单位轨迹信息包括站点编码以及到达站点时间;
第一确定模块,用于基于所述抓拍轨迹信息与所述公共交通单位轨迹信 息,确定所述目标人员在所述第一预设时间段的路线编码,每个所述路线编码对应一条路线;
第二确定模块,用于根据目标人员在所述第一预设时间段的路线编码,确定所述目标人员在第二预设时间段的热点路线,所述第二预设时间段包括多个第一预设时间段。
第三方面,本发明实施例提供一种电子设备,包括:存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序,所述处理器执行所述计算机程序时实现本发明实施例提供的热点路线分析方法中的步骤。
第四方面,本发明实施例提供一种计算机可读存储介质,所述计算机可读存储介质上存储有计算机程序,所述计算机程序被处理器执行时实现发明实施例提供的热点路线分析方法中的步骤。
本发明实施例中,获取第一预设时间段的目标人员的抓拍轨迹信息,所述目标人员为流动人员,所述抓拍轨迹信息包括所述目标人员的人员抓拍数据,所述目标人员的人员抓拍数据包括所述目标人员的抓拍时间以及公共交通单位编码;获取所述第一预设时间段的与所述公共交通单位编码对应的公共交通单位轨迹信息,所述公共交通单位轨迹信息包括站点编码以及到达站点时间;基于所述抓拍轨迹信息与所述公共交通单位轨迹信息,确定所述目标人员在所述第一预设时间段的路线编码,每个所述路线编码对应一条路线;根据目标人员在所述第一预设时间段的路线编码,确定所述目标人员在第二预设时间段的热点路线,所述第二预设时间段包括多个第一预设时间段。本发明能够通过流动人员的抓拍数据来获取流动人员的交通轨迹,进而通过流动人员的交通轨迹对流动人员的热点路线进行分析,降低流动人员信息获取的难度。
图1是本发明实施例提供的一种热点路线分析方法的流程图;
图2是本发明实施例提供的一种抓拍轨迹信息获取方法的流程图;
图3是本发明实施例提供的一种热点路线分析装置的结构示意图;
图4是本发明实施例提供的一种第一获取模块的结构示意图;
图5是本发明实施例提供的另一种热点路线分析装置的结构示意图;
图6是本发明实施例提供的一种第一确定模块的结构示意图;
图7是本发明实施例提供的一种校验子模块的结构示意图;
图8是本发明实施例提供的另一种校验子模块的结构示意图;
图9是本发明实施例提供的一种第二确定模块的结构示意图;
图10是本发明实施例提供的一种电子设备的结构示意图。
请参见图1,图1是本发明实施例提供的一种热点路线分析方法的流程图,如图1所示,包括以下步骤:
101、获取第一预设时间段的目标人员的抓拍轨迹信息。
在本发明实施例中,上述目标人员为流动人员,上述抓拍轨迹信息包括目标人员的人员抓拍数据,上述目标人员的人员抓拍数据包括目标人员的抓拍时间以及公共交通单位编码。
上述的流动人员可以根据目标人员的人脸图像在人员身份信息库中进行特征值比对来进行比对,根据比对结果来判断。
上述人员身份信息库中存储有城市常驻人员与流动人员的人员身份信息。进一步的,在特征比对后,若一个人员不是常驻人员也不是流动人员,则可以判断为流动人员。上述的人员身份信息可以是结构化或半结构化信息,上述结构化或半结构化的人员身份身份信息包括人脸图像、姓名、户籍、住址、身份证号码等信息。
上述第一预设时间段可以是用户自行设定的,比如1小时、12小时、1天、15天、1个月等时间段。
上述目标人员的人员抓拍数据可以是通过设置在公共交通单位上的抓拍设备所采集到的图像数据,上述目标人员的人员抓拍数据可以包括目标人员的人脸图像、抓拍时间、抓拍设备编码以及公共交通单位编码。在本发明实施例中,可以通过目标人员的抓拍时间和公共交通单位编码,来表示目标人员的抓拍轨迹信息。
上述抓拍设备编码可以是抓拍设备的国际编码,上述抓拍设备可以设置在公共交通单位上,并与该公共交通单位进行绑定。可以理解为抓拍设备编码与公共交通单位编码为绑定关系。
上述公共交通单位编码可以理解为一个公共交通工具的标识,在本发明实 施例中,每个公共交通工具都具有一个唯一的标识,该唯一标识可以是车牌号或是公交***的内部编号。上述公共交通单位可以是供公众出行的城市公共交通工具,比如公交车、地铁、轻轨、出租车等。上述抓拍设备设置在公共交通单位上下门处,对于存在多个上下门的公共交通单位,可以在每个上下门处都设置抓拍设备,进一步的,多个抓拍设备可以共同绑定一个公共交通单位。
需要说明的是,流动人口在空间维度和时间维度上的具有不确定性,因此,出行的交通工具大部分是城市公共交通工具,因此,流动人口的热点活动路线可以使用流动人口的交通路线进行表示。
可选的,请参见图2,图2是本发明实施例提供的一种抓拍轨迹信息获取方法的流程图,如图2所示,包括以下步骤:
201、获取公共交通单位上的抓拍设备采集的人员抓拍数据。
在本发明实施例中,上述人员抓拍数据包括抓拍人员的人脸图像、抓拍时间、抓拍设备编码以及公共交通单位编码。
上述抓拍人员的人脸图像可以是通过人脸检测引擎对抓拍设备采集到的图像进行人脸检测得到的,是一张包含抓拍人员人脸的一张小图。
202、将人脸图像在人员身份信息库中进行特征值比对,得到抓拍人员的身份信息。
在本发明实施例中,可以将人脸图像通过特征提取引擎进行特征提取,得到抓拍人员的人脸特征值,将抓拍人员的人脸图像特征值与人员身份信息库中的所有人员的人脸图像特征值进行特征值比对,上述特征值比对可以是计算两个人脸图像特征值之间的相似度,相似度越高,则说明越相近,在相似度达到阈值的情况下,则可以将对应的身份信息确认为抓拍人员的身份信息。
203、根据抓拍人员的身份信息,对抓拍人员的人员抓拍数据进行归档,得到抓拍人员档案,并存储到档案信息库中。
在本发明实施例中,对于同一个抓拍人员,将其所有的人员抓拍数据进行聚类归档,得到抓拍人员档案。上述档案信息库中存储所有抓拍人员对应的抓拍人员档案。由于人员抓拍数据中包括人脸,因此,可以在抓拍人员档案库中输入人脸图像,查找到对应的抓拍人员档案。
在一种可能的实施例中,可以将常住人员与流动人员的抓拍人员档案进行分开存储,得到常住人员档案库与流动人员档案库,这样,在需要获取流动人员档案时,可以直接在流动人员档案库中进行查找,这样,可以减少搜索范围, 提高搜索速度。
204、基于档案信息库,确定目标人员档案。
在本发明实施例中,可以通过待分析人员的人脸图像,在档案信息库中进行查找,通过待分析人员的人脸图像与抓拍人员档案中的人脸图像进行特征值比对,从而确定目标人员档案,上述目标人员档案包括目标人员的人员抓拍数据。
可选的,在本发明实施例中,可以先获取待分析人员的人脸图像;将待分析人员的人脸图像在人员身份信息库中进行特征值比对,判断待分析人员的人脸图像是否为流动人员的人脸图像;若待分析人员的人脸图像为流动人员的人脸图像,则确定待分析人员为目标人员;此时,可以在流动人员档案库中查找目标人员档案。
205、根据目标人员档案,获取第一预设时间段内的目标人员的抓拍轨迹信息。
在本发明实施例中,目标人员档案包括目标人员的人员抓拍数据,目标人员的人员抓拍数据包括目标人员的人脸图像、抓拍时间、抓拍设备编码以及公共交通单位编码,可以提取其中的抓拍时间以及公共交通单位编码作为目标人员的抓拍轨迹信息。本发明实施例提供一种抓拍轨迹信息的数据结构,包括抓拍时间、抓拍设备编码以及公共交通单位编码,具体的,抓拍轨迹信息的数据结构可以如表1所示:
表1
可以在目标档案中,筛选出符合第一预设时间段的目标人员的抓拍轨迹信息。比如筛选出某一天的目标人员的抓拍轨迹信息。当然,也可以是在输入待分析人员的人脸图像时,也同时输入第一预设时间段作为查找条件,这样,可以过滤掉该第一预设时间段内没有抓拍人员数据的档案,进一步缩小查找范围。
102、获取第一预设时间段的与公共交通单位编码对应的公共交通单位轨迹信息。
在本发明实施例中,公共交通单位轨迹信息包括站点编码以及到达站点时间。上述公共交通单位轨迹信息可以是公共交通服务信息库中的公共交通单位运营数据,即一个公共交通单位在哪个时间,到达哪个站点,对于无站点停靠的公共交通单位,则可以根据停靠时的位置信息编入最近的站点。上述公共交通单位轨迹信息可以理解为公共交通工具的行驶路线。上述站点编码对一个站点进行标识,一个站点对应的一个站点编码,上述站点可以理解为公共交通单位的停靠站点。
具体的,可以根据目标人员的抓拍轨迹信息中出现过的公共交通单位编码,在公共交通服务信息库中获取对应的公共交通单位轨迹信息。
本发明实施例提供一种公共交通单位轨迹信息数据结构,包括公共交通单位编码、到达站点时间以及站点编码,具体的,公共交通单位轨迹信息的数据结构可以如表2所示:
序号 | 城市公共交通单位编码 | 到达站点时间 | 站点编码 |
1 | GJ1GJ1214419004J06M4 | 2020/10/01 09:00:01 | ST123416 |
2 | GJ1GJ1214419004J06M4 | 2020/10/01 09:04:31 | ST674436 |
3 | GJ1GJ1214419004J06M4 | 2020/10/01 09:09:12 | ST674237 |
4 | GJ1GJ1214419004J06M4 | 2020/10/01 09:14:17 | ST234234 |
5 | GJ1GJ1214419004J06M4 | 2020/10/01 09:21:01 | ST232334 |
6 | GJ1GJ1214419004J06M4 | 2020/10/01 09:27:09 | ST239934 |
表2
103、基于抓拍轨迹信息与公共交通单位轨迹信息,确定目标人员在第一预设时间段的路线编码。
在本发明实施例中,每个路线编码对应一条路线,上述路线可以是公共交通单位行驶路线上的一段行程,比如一个公共交通单位的行驶路线依次为站点A、站点B、站点C、站点D、站点E、站点F、站点G,则与路线编码对应的路线可以是由站点A到站点B的路线,也可以是由站点A到站点C的路线,进一步的,站点A到站点B的路线对应的路线编码与站点A到站点C的路线对应的路线编码不同。
可选的,可以将抓拍轨迹信息与公共交通单位轨迹信息进行交集计算,得到目标人员在第一预设时间段的行程轨迹。根据预设的校验规则对行程轨迹进行校验,将通过校验的行程轨迹确定为目标人员在第一预设时间段的路线编码。上述行程轨迹包括目标人员的人员抓拍数据。
以表1与表2为例,由表1中的公共交通单位编码GJ1GJ1214419004J06M4,在公共交通服务信息库中查找到公共交通单位编码GJ1GJ1214419004J06M4的轨迹信息如表2,对表2与表1进行交集操作,可以得到行程轨迹为(2020/10/01-09:00:01,ST123416),(2020/10/01-09:09:12,ST674237),(2020/10/01-09:14:17,ST234234),在上述行程轨迹中,目标人员的人员抓拍数据为抓拍时间。
可选的,上述的校验规则为行程轨迹中包括多个人员抓拍数据,具体的,可以判断上述行程轨迹中是否包括多个目标人员的人员抓拍数据;若上述行程轨迹中包括多个目标人员的人员抓拍数据,则判定上述行程轨迹通过校验;若上述行程轨迹中只包括一个目标人员的人员抓拍数据,则判断行程轨迹未通过校验。
具体的,若上述行程轨迹中包括多个目标人员的人员抓拍数据,则可以说明目标人员在公共交通单位上被抓拍多次。进一步的,可以提取通过校验的行程轨迹中最早抓拍时间与最晚抓拍时间,并根据最早抓拍时间确定第一到达站点时间,从而根据第一到达站点时间确定对应的第一站点编码,根据最晚抓拍时间确定第二到达站点时间,从而根据第二到达站点时间确定对应的第二站点编码,根据第一站点编码与第二站点编码,确定目标人员在第一预设时间段的路线编码。比如,上述行程轨迹为(2020/10/01-09:00:01,ST123416),(2020/10/01-09:09:12,ST674237),(2020/10/01-09:14:17,ST234234), 目标人员的人员抓拍数据(抓拍时间)有三个,可以认为该行程轨迹通过校验,最早抓拍时间为2020/10/01-09:00:01,对应的第一站点编码为ST123416,最晚抓拍时间为2020/10/01-09:14:17,对应的第二站点编码为ST234234,并根据第一站点编码ST123416与第二站点编码ST234234,确定目标人员在第一预设时间段的路线编码C=f(ST234234,ST234234),其中,f为站点编码到路线编码的映射函数。另外,若上述行程轨迹中只包括一个目标人员的人员抓拍数据,则说明该行程轨迹中目标人员可能只被抓拍到一次,是不准确的,不能使用,可以将该条行程轨迹进行放弃。
104、根据目标人员在所述第一预设时间段的路线编码,确定目标人员在第二预设时间段的热点路线。
在本发明实施例中,上述第二预设时间段包括多个第一预设时间段,上述第二预设时间段可以是月、季度或年等时间区间。比如,上述第一预设时间段为天,上述第二预设时间段为5月,则第二预设时间段包括31个第一预设时间段。
可选的,在本发明实施例中,可以将第二预设时间段为统计区间,对第一预设时间段的路线编码进行数量统计;按数量对所有的路线编码进行排序,取前N个路线编码所对应的N个路线为目标人员在第二预设时间段的热点路线。上述对所有的路线编码进行排序可以如表3所示:
序号 | 路线编码 | 城市公共交通单位编码 | 出现次数 |
1 | R9128374 | GJ1GJ1214419004J06M4 | 25 |
2 | R9328334 | GJ2GJ212441900K87DCJ | 8 |
3 | R9300371 | GJ2GJ212441900783KS3 | 3 |
表3
在表3中,出现次数为对应路线编码在第二预设时间段的数量,根据出现次数进行降序排列,可以取前N个路线编码所对应的路线为目标人员在第二预设时间段的热点路线。
在本发明实施例中,获取第一预设时间段的目标人员的抓拍轨迹信息,所述目标人员为流动人员,所述抓拍轨迹信息包括所述目标人员的人员抓拍数据,所述目标人员的人员抓拍数据包括所述目标人员的抓拍时间以及公共交通单位编码;获取所述第一预设时间段的与所述公共交通单位编码对应的公共交 通单位轨迹信息,所述公共交通单位轨迹信息包括站点编码以及到达站点时间;基于所述抓拍轨迹信息与所述公共交通单位轨迹信息,确定所述目标人员在所述第一预设时间段的路线编码,每个所述路线编码对应一条路线;根据目标人员在所述第一预设时间段的路线编码,确定所述目标人员在第二预设时间段的热点路线,所述第二预设时间段包括多个第一预设时间段。本发明能够通过流动人员的抓拍数据来获取流动人员的交通轨迹,进而通过流动人员的交通轨迹对流动人员的热点路线进行分析,降低流动人员信息获取的难度。
需要说明的是,本发明实施例提供的热点路线分析方法可以应用于可以进行热点路线分析的手机、监控器、计算机、服务器等设备。
请参见图3,图3是本发明实施例提供的一种热点路线分析装置的结构示意图,如图3所示,所述装置包括:
第一获取模块301,用于获取第一预设时间段的目标人员的抓拍轨迹信息,所述目标人员为流动人员,所述抓拍轨迹信息包括所述目标人员的人员抓拍数据,所述目标人员的人员抓拍数据包括所述目标人员的抓拍时间以及公共交通单位编码;
第二获取模块302,用于获取所述第一预设时间段的与所述公共交通单位编码对应的公共交通单位轨迹信息,所述公共交通单位轨迹信息包括站点编码以及到达站点时间;
第一确定模块303,用于基于所述抓拍轨迹信息与所述公共交通单位轨迹信息,确定所述目标人员在所述第一预设时间段的路线编码,每个所述路线编码对应一条路线;
第二确定模块304,用于根据目标人员在所述第一预设时间段的路线编码,确定所述目标人员在第二预设时间段的热点路线,所述第二预设时间段包括多个第一预设时间段。
可选的,如图4所示,所述第一获取模块301,包括:
第一获取子模块3011,用于获取公共交通单位上的抓拍设备采集的人员抓拍数据,所述人员抓拍数据包括抓拍人员的人脸图像、抓拍时间、抓拍设备编码以及公共交通单位编码;
第一比对子模块3012,用于将所述人脸图像在人员身份信息库中进行特征值比对,得到所述抓拍人员的身份信息;
归档子模块3013,用于根据所述身份信息,对所述人员抓拍数据进行归 档,得到抓拍人员档案,并存储到档案信息库中;
确定子模块3014,用于基于所述档案信息库,确定目标人员档案,所述目标人员档案包括目标人员的人员抓拍数据;
第二获取子模块3015,用于根据所述目标人员档案,获取第一预设时间段内的目标人员的抓拍轨迹信息。
可选的,如图5所示,所述装置还包括:
第三获取模块305,用于获取待分析人员的人脸图像;
判断模块306,用于将所述待分析人员的人脸图像在人员身份信息库中进行特征值比对,判断所述待分析人员的人脸图像是否为流动人员的人脸图像;
第三确定模块307,用于若所述待分析人员的人脸图像为流动人员的人脸图像,则确定所述待分析人员为目标人员。
可选的,如图6所示,所述第一确定模块303,包括:
计算子模块3031,用于将所述抓拍轨迹信息与所述公共交通单位轨迹信息进行交集计算,得到所述目标人员在所述第一预设时间段的行程轨迹,所述行程轨迹包括目标人员的人员抓拍数据;
校验子模块3032,用于根据预设的校验规则对所述行程轨迹进行校验,将通过校验的行程轨迹确定为所述目标人员在所述第一预设时间段的路线编码。
可选的,如图7所示,所述校验规则为所述行程轨迹中包括多个所述人员抓拍数据,所述校验子模块3032,包括:
判断单元30321,用于判断所述行程轨迹中是否包括多个所述目标人员的人员抓拍数据;
第一判定单元30322,用于若所述行程轨迹中包括多个所述目标人员的人员抓拍数据,则判定所述行程轨迹通过校验;
第二判断单元30323,用于若所述行程轨迹中只包括一个所述目标人员的人员抓拍数据,则判断所述行程轨迹未通过校验。
可选的,如图8所示,所述校验子模块3032,还包括:
提取单元30324,用于提取通过校验的行程轨迹中最早抓拍时间与最晚抓拍时间;
第一确定单元30325,用于根据所述最早抓拍时间确定第一到达站点时间,并根据所述第一到达站点时间确定对应的第一站点编码;
第二确定单元30326,用于根据所述最晚抓拍时间确定第二到达站点时间,并根据所述第二到达站点时间确定对应的第二站点编码;
第三确定单元30327,用于根据所述第一站点编码与所述第二站点编码,确定所述目标人员在所述第一预设时间段的路线编码。
可选的,如图9所示,所述第二确定模块304,包括:
统计子模块3041,用于以第二预设时间段为统计区间,对所述第一预设时间段的路线编码进行数量统计;
选取子模块3042,用于按数量对所有的路线编码进行排序,取TOP-N个路线编码所对应的N个路线为所述目标人员在第二预设时间段的热点路线。
需要说明的是,本发明实施例提供的热点路线分析装置可以应用于可以进行热点路线分析的手机、监控器、计算机、服务器等设备。
本发明实施例提供的热点路线分析装置能够实现上述方法实施例中热点路线分析方法实现的各个过程,且可以达到相同的有益效果。为避免重复,这里不再赘述。
参见图10,图10是本发明实施例提供的一种电子设备的结构示意图,如图10所示,包括:存储器1002、处理器1001及存储在所述存储器1002上并可在所述处理器1001上运行的计算机程序,其中:
处理器1001用于调用存储器1002存储的计算机程序,执行如下步骤:
获取第一预设时间段的目标人员的抓拍轨迹信息,所述目标人员为流动人员,所述抓拍轨迹信息包括所述目标人员的人员抓拍数据,所述目标人员的人员抓拍数据包括所述目标人员的抓拍时间以及公共交通单位编码;
获取所述第一预设时间段的与所述公共交通单位编码对应的公共交通单位轨迹信息,所述公共交通单位轨迹信息包括站点编码以及到达站点时间;
基于所述抓拍轨迹信息与所述公共交通单位轨迹信息,确定所述目标人员在所述第一预设时间段的路线编码,每个所述路线编码对应一条路线;
根据目标人员在所述第一预设时间段的路线编码,确定所述目标人员在第二预设时间段的热点路线,所述第二预设时间段包括多个第一预设时间段。
可选的,处理器1001执行的所述获取第一预设时间段的目标人员的抓拍轨迹信息,包括:
获取公共交通单位上的抓拍设备采集的人员抓拍数据,所述人员抓拍数据包括抓拍人员的人脸图像、抓拍时间、抓拍设备编码以及公共交通单位编码;
将所述人脸图像在人员身份信息库中进行特征值比对,得到所述抓拍人员的身份信息;
根据所述身份信息,对所述人员抓拍数据进行归档,得到抓拍人员档案,并存储到档案信息库中;
基于所述档案信息库,确定目标人员档案,所述目标人员档案包括目标人员的人员抓拍数据;
根据所述目标人员档案,获取第一预设时间段内的目标人员的抓拍轨迹信息。
可选的,处理器1001还执行包括:
获取待分析人员的人脸图像;
将所述待分析人员的人脸图像在人员身份信息库中进行特征值比对,判断所述待分析人员的人脸图像是否为流动人员的人脸图像;
若所述待分析人员的人脸图像为流动人员的人脸图像,则确定所述待分析人员为目标人员。
可选的,处理器1001执行的所述基于所述抓拍轨迹信息与所述公共交通单位轨迹信息,确定所述目标人员在所述第一预设时间段的路线编码,包括:
将所述抓拍轨迹信息与所述公共交通单位轨迹信息进行交集计算,得到所述目标人员在所述第一预设时间段的行程轨迹,所述行程轨迹包括目标人员的人员抓拍数据;
根据预设的校验规则对所述行程轨迹进行校验,将通过校验的行程轨迹确定为所述目标人员在所述第一预设时间段的路线编码。
可选的,所述校验规则为所述行程轨迹中包括多个所述人员抓拍数据,处理器1001执行的所述根据预设的校验规则对所述行程轨迹进行校验,包括:
判断所述行程轨迹中是否包括多个所述目标人员的人员抓拍数据;
若所述行程轨迹中包括多个所述目标人员的人员抓拍数据,则判定所述行程轨迹通过校验;
若所述行程轨迹中只包括一个所述目标人员的人员抓拍数据,则判断所述行程轨迹未通过校验。
可选的,处理器1001执行的所述将通过校验的行程轨迹确定为所述目标人员在所述第一预设时间段的路线编码,包括:
提取通过校验的行程轨迹中最早抓拍时间与最晚抓拍时间;
根据所述最早抓拍时间确定第一到达站点时间,并根据所述第一到达站点时间确定对应的第一站点编码;
根据所述最晚抓拍时间确定第二到达站点时间,并根据所述第二到达站点时间确定对应的第二站点编码;
根据所述第一站点编码与所述第二站点编码,确定所述目标人员在所述第一预设时间段的路线编码。
可选的,处理器1001执行的所述根据目标人员在所述第一预设时间段的路线编码,确定所述目标人员在第二预设时间段的热点路线,包括:
以第二预设时间段为统计区间,对所述第一预设时间段的路线编码进行数量统计;
按数量对所有的路线编码进行排序,取前N个路线编码所对应的N个路线为所述目标人员在第二预设时间段的热点路线。
需要说明的是,上述电子设备可以是可以应用于可以进行热点路线分析的手机、监控器、计算机、服务器等设备。
本发明实施例提供的电子设备能够实现上述方法实施例中热点路线分析方法实现的各个过程,且可以达到相同的有益效果,为避免重复,这里不再赘述。
本发明实施例还提供一种计算机可读存储介质,计算机可读存储介质上存储有计算机程序,该计算机程序被处理器执行时实现本发明实施例提供的热点路线分析方法的各个过程,且能达到相同的技术效果,为避免重复,这里不再赘述。
Claims (10)
- 一种热点路线分析方法,其特征在于,包括以下步骤:获取第一预设时间段的目标人员的抓拍轨迹信息,所述目标人员为流动人员,所述抓拍轨迹信息包括所述目标人员的人员抓拍数据,所述目标人员的人员抓拍数据包括所述目标人员的抓拍时间以及公共交通单位编码;获取所述第一预设时间段的与所述公共交通单位编码对应的公共交通单位轨迹信息,所述公共交通单位轨迹信息包括站点编码以及到达站点时间;基于所述抓拍轨迹信息与所述公共交通单位轨迹信息,确定所述目标人员在所述第一预设时间段的路线编码,每个所述路线编码对应一条路线;根据目标人员在所述第一预设时间段的路线编码,确定所述目标人员在第二预设时间段的热点路线,所述第二预设时间段包括多个第一预设时间段。
- 如权利要求1所述的方法,其特征在于,所述获取第一预设时间段的目标人员的抓拍轨迹信息,包括:获取公共交通单位上的抓拍设备采集的人员抓拍数据,所述人员抓拍数据包括抓拍人员的人脸图像、抓拍时间、抓拍设备编码以及公共交通单位编码;将所述人脸图像在人员身份信息库中进行特征值比对,得到所述抓拍人员的身份信息;根据所述身份信息,对所述人员抓拍数据进行归档,得到抓拍人员档案,并存储到档案信息库中;基于所述档案信息库,确定目标人员档案,所述目标人员档案包括目标人员的人员抓拍数据;根据所述目标人员档案,获取第一预设时间段内的目标人员的抓拍轨迹信息。
- 如权利要求2所述的方法,其特征在于,所述方法还包括:获取待分析人员的人脸图像;将所述待分析人员的人脸图像在人员身份信息库中进行特征值比对,判断所述待分析人员的人脸图像是否为流动人员的人脸图像;若所述待分析人员的人脸图像为流动人员的人脸图像,则确定所述待分析人员为目标人员。
- 如权利要求3所述的方法,其特征在于,所述基于所述抓拍轨迹信息与所述公共交通单位轨迹信息,确定所述目标人员在所述第一预设时间段的路线 编码,包括:将所述抓拍轨迹信息与所述公共交通单位轨迹信息进行交集计算,得到所述目标人员在所述第一预设时间段的行程轨迹,所述行程轨迹包括目标人员的人员抓拍数据;根据预设的校验规则对所述行程轨迹进行校验,将通过校验的行程轨迹确定为所述目标人员在所述第一预设时间段的路线编码。
- 如权利要求4所述的方法,其特征在于,所述校验规则为所述行程轨迹中包括多个所述人员抓拍数据,所述根据预设的校验规则对所述行程轨迹进行校验,包括:判断所述行程轨迹中是否包括多个所述目标人员的人员抓拍数据;若所述行程轨迹中包括多个所述目标人员的人员抓拍数据,则判定所述行程轨迹通过校验;若所述行程轨迹中只包括一个所述目标人员的人员抓拍数据,则判断所述行程轨迹未通过校验。
- 如权利要求5所述的方法,其特征在于,所述将通过校验的行程轨迹确定为所述目标人员在所述第一预设时间段的路线编码,包括:提取通过校验的行程轨迹中最早抓拍时间与最晚抓拍时间;根据所述最早抓拍时间确定第一到达站点时间,并根据所述第一到达站点时间确定对应的第一站点编码;根据所述最晚抓拍时间确定第二到达站点时间,并根据所述第二到达站点时间确定对应的第二站点编码;根据所述第一站点编码与所述第二站点编码,确定所述目标人员在所述第一预设时间段的路线编码。
- 如权利要求1至6中任一所述的方法,其特征在于,所述根据目标人员在所述第一预设时间段的路线编码,确定所述目标人员在第二预设时间段的热点路线,包括:以所述第二预设时间段为统计区间,对所述第一预设时间段的路线编码进行数量统计;按数量对所有的路线编码进行排序,取前N个路线编码所对应的N个路线为所述目标人员在第二预设时间段的热点路线。
- 一种热点路线分析装置,其特征在于,所述装置包括:第一获取模块,用于获取第一预设时间段的目标人员的抓拍轨迹信息,所述目标人员为流动人员,所述抓拍轨迹信息包括所述目标人员的人员抓拍数据,所述目标人员的人员抓拍数据包括所述目标人员的抓拍时间以及公共交通单位编码;第二获取模块,用于获取所述第一预设时间段的与所述公共交通单位编码对应的公共交通单位轨迹信息,所述公共交通单位轨迹信息包括站点编码以及到达站点时间;第一确定模块,用于基于所述抓拍轨迹信息与所述公共交通单位轨迹信息,确定所述目标人员在所述第一预设时间段的路线编码,每个所述路线编码对应一条路线;第二确定模块,用于根据目标人员在所述第一预设时间段的路线编码,确定所述目标人员在第二预设时间段的热点路线,所述第二预设时间段包括多个第一预设时间段。
- 一种电子设备,其特征在于,包括:存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序,所述处理器执行所述计算机程序时实现如权利要求1至7中任一项所述的热点路线分析方法中的步骤。
- 一种计算机可读存储介质,其特征在于,所述计算机可读存储介质上存储有计算机程序,所述计算机程序被处理器执行时实现如权利要求1至7中任一项所述的热点路线分析方法中的步骤。
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