CN113806459A - Beidou grid-based peer identification method, system and storage medium - Google Patents

Beidou grid-based peer identification method, system and storage medium Download PDF

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CN113806459A
CN113806459A CN202110910133.2A CN202110910133A CN113806459A CN 113806459 A CN113806459 A CN 113806459A CN 202110910133 A CN202110910133 A CN 202110910133A CN 113806459 A CN113806459 A CN 113806459A
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person
track
trajectory
grids
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CN113806459B (en
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黄朔
任伏虎
刘越
王鹏
刘杰
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Beijing Beidou Fuxi Technology Co ltd
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Abstract

The invention discloses a method, a system and a storage medium for identifying the same-person based on Beidou grids, relates to the technical field of identification of the same-person, and can quickly and accurately identify the same-person. The technical scheme of the invention comprises the following steps: and (3) carrying out mesh generation and coding on the monitored area by utilizing the earth generation mesh coding technology of the Beidou mesh position code to obtain a mesh map. And gridding the personnel track to obtain a track grid area, wherein the grid size in the track grid area is the same as that of the grid map. All grids in each trajectory grid region constitute a trajectory grid set. And judging whether the trajectory grids in the trajectory grid set of the two persons meet, if the number of meeting grids exceeds a set threshold value, judging that the two persons are the same person.

Description

Beidou grid-based peer identification method, system and storage medium
Technical Field
The invention relates to the technical field of peer identification, in particular to a method, a system and a storage medium for identifying peers based on Beidou grids.
Background
The technology related to the identification of the people in the same row can be applied to various scenes, such as the field of security protection, internet social contact and the like.
At present, the technical scheme commonly adopted by the fellow passengers who recognize the designated person is that a face recognition technology of a camera is utilized to judge whether any person and the designated person continuously appear in one image, and because the conditions for capturing the face and accurately recognizing the face by the camera in reality are harsh, the data of the face of the person cannot be obtained due to angles, shelters and the like, so that the recognition errors and failures are caused, and the recognition accuracy of the fellow passengers is greatly reduced.
Meanwhile, in the post-determination, the obtained data is often the track data of all people in a time period, so that a rapid method is needed for extracting the same person from a large pile of track data.
Therefore, a scheme capable of rapidly and accurately identifying the fellow persons is needed.
Disclosure of Invention
In view of this, the invention provides a method, a system and a storage medium for identifying the fellow passengers based on the Beidou grid, which can quickly and accurately identify the fellow passengers.
In order to achieve the purpose, the technical scheme of the invention comprises the following steps:
s1: and (3) carrying out mesh generation and coding on the monitored area by utilizing the earth generation mesh coding technology of the Beidou mesh position code to obtain a mesh map.
S2: and gridding the personnel track to obtain a track grid area, wherein the grid size in the track grid area is the same as that of the grid map.
All grids in each trajectory grid region constitute a trajectory grid set.
S3: and judging whether the trajectory grids in the trajectory grid set of the two persons meet, if the number of meeting grids exceeds a set threshold value, judging that the two persons are the same person.
Further, all grids in each track grid area form a track grid set, and the following steps are specifically adopted:
and constructing a state relation index table aiming at the track grid area corresponding to each person.
The state relation index table comprises a personnel identity identification code ID, a moment t and a personnel state p; the person state p is the track grid code where the person is located at the time t.
And determining the personnel states p at all discrete moments in the time period to be analyzed according to the constructed state relation index table to form a track grid set.
Further, whether the trajectory grids in the trajectory grid set of the two persons meet is judged, and specifically, the following method is adopted:
the trajectory grid sets of the two persons are respectively L1And L2。
First person trajectory grid set L1＝{(p1 n，t1 n) N1.. N }; n is the total number of the track grids of the first person; t is t1 nThe moment corresponding to the nth track grid of the first person; p is a radical of1 nAnd the person state corresponding to the nth track grid of the first person.
Second person trajectory grid set L2＝{(p2 m，t2 m) M1.. M }; m is the total track grid number of the second person; t is t2 mThe moment corresponding to the mth track grid of the second person; p is a radical of2 mAnd the personnel state corresponding to the mth track grid of the second personnel.
Judgment of L1And L2If the meeting grids exist, and the number of the meeting grids exceeds a set threshold value, the two persons are judged to be the same person.
The set threshold is set as: r × min (L)1),Length(L2) ); wherein length (L)1) Represents L1Length of (d); length (L)2) Represents L2Length of (d); r is the set scale.
Further, L is judged1And L2Whether or notThe method for meeting grids comprises the following steps:
for the nth trajectory grid (p) in the first person trajectory grid set1 n，t1 n) And the mth trajectory grid (p) in the second set of person trajectory grids2 m，t2 m) If the following four conditions are simultaneously satisfied, the two are the meeting grids:
condition a: | distance (p)1 n,p2 m)|<dist; wherein | distance (p)1 n,p2 m) Represents p1 n,p2 mA linear distance between the center points of the two may be used; dist is a preset distance threshold.
Condition b: | t1 n-t2 m|<tim; where tim is a preset time threshold.
Condition c: p is a radical of2 mIs L2Satisfies the condition b and a distance p1 nThe nearest trajectory grid.
Condition d: if p of condition c is satisfied2 mIf the number of the cells exceeds 1, selecting t from the number1 n-t2 mThe minimum grid of is p1 nThe meeting grid.
Further, the preset time threshold tim is set to 15 seconds.
The invention further provides a peer identification system based on the Beidou grid, which comprises a monitoring area subdivision module, a gridding module and a peer judgment module.
And the monitoring area dividing module inputs a monitored area map, performs mesh division and coding on the monitored area by using the earth division mesh coding technology of the Beidou grid position code, and obtains and outputs the mesh map.
And the gridding module is used for inputting a person track, determining track grid areas according to the position of the person track on the grid map, forming a track grid set by all grids in each track grid area and outputting the track grid set.
And the co-pedestrian judging module is used for acquiring the track grid sets of the two persons to be judged, judging whether the track grids in the track grid sets of the two persons meet or not, and judging that the two persons are co-pedestrians if the number of meeting grids exceeds a set threshold value.
Further, the gridding module specifically adopts the following steps:
and constructing a state relation index table aiming at the track grid area corresponding to each person.
The state relation index table comprises a personnel identity identification code ID, a moment t and a personnel state p; the person state p is the track grid code where the person is located at the time t.
And determining the personnel states p at all discrete moments in the time period to be analyzed according to the constructed state relation index table to form a track grid set.
Further, the peer judgment module specifically adopts the following method:
the trajectory grid sets of the two persons are respectively L1And L2；
First person trajectory grid set L1＝{(p1 n，t1 n) N1.. N }; n is the total number of the track grids of the first person; t is t1 nThe moment corresponding to the nth track grid of the first person; p is a radical of1 nAnd the person state corresponding to the nth track grid of the first person.
Second person trajectory grid set L2＝{(p2 m，t2 m) M1.. M }; m is the total track grid number of the second person; t is t2 mThe moment corresponding to the mth track grid of the second person; p is a radical of2 mAnd the personnel state corresponding to the mth track grid of the second personnel.
Judgment of L1And L2If the meeting grids exist, and the number of the meeting grids exceeds a set threshold value, the two persons are judged to be the same person.
The set threshold is set as: r × min (L)1),Length(L2) ); wherein length (L)1) Represents L1Length of (d); length (L)2) Represents L2Length of (d); r is the set scale.
For the nth trajectory grid (p) in the first person trajectory grid set1 n，t1 n) And the mth trajectory grid (p) in the second set of person trajectory grids2 m，t2 m) If the following four conditions are simultaneously satisfied, the two are the meeting grids:
condition a: | distance (p)1 n,p2 m)|<dist; wherein | distance (p)1 n,p2 m) Represents p1 n,p2 mA linear distance between the center points of the two may be used; dist is a preset distance threshold;
condition b: | t1 n-t2 m|<tim; wherein tim is a preset time threshold;
condition c: p is a radical of2 mIs L2Satisfies the condition b and a distance p1 nA nearest trajectory grid;
condition d: if p of condition c is satisfied2 mIf the number of the cells exceeds 1, selecting t from the number1 n-t2 mThe minimum grid of is p1 nThe meeting grid.
Another embodiment of the present invention further provides a computer readable storage medium, on which computer instructions are stored, which when executed by a processor, can implement the steps of the method for identifying a peer based on the beidou mesh of any one of claims 1 to 6.
Has the advantages that:
the invention provides a peer identification scheme based on Beidou grids, which comprises the steps of firstly carrying out grid division and grid coding on a monitoring area; then establishing state relation indexes of the personnel and the gridding area to form a movement track grid set of the personnel; then, the length of the track overlapped with other target objects in a buffer area (dist) of the track of the person is searched, and if the overlapping ratio exceeds a certain value, two persons are determined as the same person; and repeating the steps until all the same pedestrian combinations are found. Compared with the defects of low recognition rate and easy error of the same-person people in the prior art, the invention provides a measurable and computer-programmable solution, and can greatly improve the accuracy and efficiency of the same-person recognition.
Drawings
Fig. 1 is a schematic flow chart of a peer identification method based on the Beidou grid, provided by the invention.
Detailed Description
The invention is described in detail below by way of example with reference to the accompanying drawings.
The invention provides a method for identifying fellow passengers based on Beidou grids, which has a process shown in figure 1 and comprises the following steps:
s1: carrying out mesh generation and coding on the monitored area by utilizing the earth generation mesh coding technology of the Beidou mesh position code to obtain a mesh map; the size of the grid can be subdivided as required, and is as small as centimeter level.
S2: and gridding the personnel track to obtain a track grid area, wherein the grid size in the track grid area is the same as that of the grid map.
All grids in each trajectory grid region constitute a trajectory grid set.
Constructing a state relation index table aiming at the corresponding track grid area of each person; the state relation index table comprises a personnel identity identification code ID, a moment t and a personnel state p; the person state p is the track grid code of the person at the moment t; and determining the personnel states p at all discrete moments in the time period to be analyzed according to the constructed state relation index table to form a track grid set.
S3: and judging whether the trajectory grids in the trajectory grid set of the two persons meet, if the number of meeting grids exceeds a set threshold value, judging that the two persons are the same person.
Specifically, the following method is adopted:
the trajectory grid sets of the two persons are respectively L1And L2；
First person trajectory grid set L1＝{(p1 n，t1 n) N1.. N }; n is the total number of the track grids of the first person; t is t1 nThe moment corresponding to the nth track grid of the first person; p is a radical of1 nThe personnel state corresponding to the nth track grid of the first personnel;
second person trajectory grid set L2＝{(p2 m，t2 m) M1.. M }; m is the total track grid number of the second person; t is t2 mThe moment corresponding to the mth track grid of the second person; p is a radical of2 mThe personnel state corresponding to the mth track grid of the second personnel;
judgment of L1And L2If the meeting grids exist, and the number of the meeting grids exceeds a set threshold value, judging that the two persons are the same person;
the set threshold is set as: r × min (L)1),Length(L2) ); wherein length (L)1) Represents L1Length of (the total number of grids in the set, N, can be used as a length scale); length (L)2) Represents L2Length of (d); r is the set scale (e.g., r is set to 80%).
Judgment of L1And L2Whether there is an encounter grid or not, the specific method is as follows:
for the nth trajectory grid (p) in the first person trajectory grid set1 n，t1 n) And the mth trajectory grid (p) in the second set of person trajectory grids2 m，t2 m) If the following four conditions are simultaneously satisfied, the two are the meeting grids:
condition a: | distance (p)1 n,p2 m)|<dist; wherein | distance (p)1 n,p2 m) Represents p1 n,p2 mA linear distance between the center points of the two may be used; dist is a preset distance threshold;
condition b: | t1 n-t2 m|<tim; wherein tim is a preset time threshold;
condition c: p is a radical of2 mIs L2Satisfies the condition b and a distance p1 nA nearest trajectory grid;
condition d: if p of condition c is satisfied2 mIf the number of the cells exceeds 1, selecting t from the number1 n-t2 mThe minimum grid of is p1 nThe meeting grid.
The preset distance threshold Dist is determined according to the size of the track grid, and the Dist is set to be not more than 2 times of the size of the track grid. The preset time threshold tim is set to 15 seconds.
The invention further provides a peer identification system based on the Beidou grid, which comprises a monitoring area subdivision module, a gridding module and a peer judgment module.
And the monitoring area dividing module inputs a monitored area map, performs mesh division and coding on the monitored area by using the earth division mesh coding technology of the Beidou grid position code, and obtains and outputs the mesh map.
And the gridding module is used for inputting a person track, determining track grid areas according to the position of the person track on the grid map, forming a track grid set by all grids in each track grid area and outputting the track grid set.
And the co-pedestrian judging module is used for acquiring the track grid sets of the two persons to be judged, judging whether the track grids in the track grid sets of the two persons meet or not, and judging that the two persons are co-pedestrians if the number of meeting grids exceeds a set threshold value.
The gridding module specifically comprises the following steps:
and constructing a state relation index table aiming at the track grid area corresponding to each person.
The state relation index table comprises a personnel identity identification code ID, a moment t and a personnel state p; the person state p is the track grid code where the person is located at the time t.
And determining the personnel states p at all discrete moments in the time period to be analyzed according to the constructed state relation index table to form a track grid set.
The pedestrian judgment module specifically adopts the following method:
the trajectory grid sets of the two persons are respectively L1And L2。
First person trajectory grid set L1＝{(p1 n，t1 n) N1.. N }; n is the total number of the track grids of the first person; t is t1 nThe moment corresponding to the nth track grid of the first person; p is a radical of1 nAnd the person state corresponding to the nth track grid of the first person.
Second person trajectory grid set L2＝{(p2 m，t2 m) M1.. M }; m is the total track grid number of the second person; t is t2 mThe moment corresponding to the mth track grid of the second person; p is a radical of2 mAnd the personnel state corresponding to the mth track grid of the second personnel.
Judgment of L1And L2If the meeting grids exist, and the number of the meeting grids exceeds a set threshold value, the two persons are judged to be the same person.
The set threshold is set as: r × min (L)1),Length(L2) ); wherein length (L)1) Represents L1Length of (the total number of grids in the set, N, can be used as a length scale); length (L)2) Represents L2Length of (d); r is the set scale (e.g., r is set to 80%).
For the nth trajectory grid (p) in the first person trajectory grid set1 n，t1 n) And the mth trajectory grid (p) in the second set of person trajectory grids2 m，t2 m) If the following four conditions are simultaneously satisfied, the two are the meeting grids:
condition a: | distance (p)1 n,p2 m)|<dist; wherein | distance (p)1 n,p2 m) Represents p1 n,p2 mA linear distance between the center points of the two may be used; dist is a preset distance threshold.
Condition b: | t1 n-t2 m|<tim; where tim is a preset time threshold.
Condition c: p is a radical of2 mIs L2Satisfies the condition b and a distance p1 nThe nearest trajectory grid.
Condition d: if p of condition c is satisfied2 mIf the number of the cells exceeds 1, selecting t from the number1 n-t2 mThe minimum grid of is p1 nThe meeting grid.
The embodiment of the invention also provides a computer readable storage medium, wherein computer instructions are stored on the computer readable storage medium, and when the computer instructions are executed by a processor, the steps in the peer identification method based on the Beidou grid can be realized.
The embodiment of the invention provides an operation example:
(1) gridding the tracks of the alternative personnel so that the state of each personnel in the grid along with the time (such as the grid l occupied by the personnel A at the time t) can be indexed;
(2) selecting a person name (A) and a time period to be used as a basic trajectory of analysis of the same person
(3) Setting space limit dist grid number, setting time limit tim and setting r value
(4) Confirmation, entry into peer analysis
And (3) calculating flow:
1. obtaining a grid track A of the basic personnel and calculating the grid number W of the grid track lengtha；
2. Making a buffer area by using the dist value according to the track;
3. searching and recording other personnel tracks falling into the buffer area, setting the personnel tracks as an X track set, and calculating the grid number WX _ i of each track in the buffer area;
4. track starting point grid marking and ending in X is searched one by oneThe grid of points is labeled and recorded as X _ i (X)1， xn)；
5. And searching the nearest grid in the track A by using the X1 grid in the X _ i, and recording the nearest grid as X _ i/a1；
6. And searching the nearest grid in the track A by using the X2 grid in the X _ i, and recording the nearest grid as X _ i/a2；
7. Searching the nearest grid in the track A by using xn grid in X _ i, and recording as X _ i/an；
8. Comparison a1And anIf anEarlier than a1Then the track X _ i is the reverse track of the track A, all the reverse tracks are deleted to obtain a reduced set of equidirectional tracks X _ i (X1, xn), and X _ i (a)1,an) Positioning the starting and stopping position relation between the track in the X and the track A;
9. for tracks X _ i in X set, one by one, from X1Corresponds to a1Begin grid-by-grid comparison of time difference | Xt with the grid in track Ai–Ati|<tim, and | distance (X)i,Ai)|<Recording grids on an X _ i track meeting requirements until an end point xn grid is reached according to the dist distance difference, and summarizing the grid number MX _ i meeting dist and tim;
10. calculating the value r, wherein r is MX _ i/WX _ i, and when r is more than or equal to 80%, the person X _ i is considered as the co-pedestrian of the person A;
11. and displaying the trajectories of the co-pedestrians on the main page and outputting a co-pedestrian list.
In summary, the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (9)

1. A peer identification method based on Beidou grids is characterized by comprising the following steps:
s1: carrying out mesh generation and coding on the monitored area by utilizing the earth generation mesh coding technology of the Beidou mesh position code to obtain a mesh map;
s2: gridding the personnel track to obtain a track grid area, wherein the grid size in the track grid area is the same as that of the grid map;
all grids in each track grid area form a track grid set;
s3: and judging whether the trajectory grids in the trajectory grid set of the two persons meet, if the number of meeting grids exceeds a set threshold value, judging that the two persons are the same person.
2. The method of claim 1, wherein all grids in each of the trajectory grid regions form a trajectory grid set, using the following steps:
constructing a state relation index table aiming at the corresponding track grid area of each person;
the state relation index table comprises a personnel identity identification code ID, a moment t and a personnel state p; the person state p is the track grid code of the person at the moment t;
and determining the personnel states p at all discrete moments in the time period to be analyzed according to the constructed state relation index table to form a track grid set.
3. The method as claimed in claim 1, wherein the determining whether the trajectory meshes in the trajectory mesh sets of two persons meet each other is performed by:
the trajectory grid sets of the two persons are respectively L1And L2；
First person trajectory grid set L1＝{(p1 n，t1 n) N1.. N }; n is the total number of the track grids of the first person; t is t1 nThe moment corresponding to the nth track grid of the first person; p is a radical of1 nThe personnel state corresponding to the nth track grid of the first personnel;
second person trajectory grid set L2＝{(p2 m，t2 m) M1.. M }; m is a trajectory grid of the second personTotal number; t is t2 mThe moment corresponding to the mth track grid of the second person; p is a radical of2 mThe personnel state corresponding to the mth track grid of the second personnel;
judgment of L1And L2If the meeting grids exist, and the number of the meeting grids exceeds a set threshold value, judging that the two persons are the same person;
the set threshold is set as: r × min (L)1),Length(L2) ); wherein length (L)1) Represents L1Length of (d); length (L)2) Represents L2Length of (d); r is the set scale.
4. The method of claim 3, wherein said determining L1And L2Whether there is an encounter grid or not, the specific method is as follows:
for the nth trajectory grid (p) in the first person trajectory grid set1 n，t1 n) And the mth trajectory grid (p) in the second set of person trajectory grids2 m，t2 m) If the following four conditions are simultaneously satisfied, the two are the meeting grids:
condition a: | distance (p)1 n,p2 m)|<dist; wherein | distance (p)1 n,p2 m) Represents p1 n,p2 mA linear distance between the center points of the two may be used; dist is a preset distance threshold;
condition b: | t1 n-t2 m|<tim; wherein tim is a preset time threshold;
condition c: p is a radical of2 mIs L2Satisfies the condition b and a distance p1 nA nearest trajectory grid;
condition d: if p of condition c is satisfied2 mIf the number of the cells exceeds 1, selecting t from the number1 n-t2 mThe minimum grid of is p1 nMeet the grid。
5. The method of claim 4, wherein the preset time threshold tim is set to 15 seconds.
6. A peer identification system based on Beidou grids is characterized by comprising a monitoring area subdivision module, a gridding module and a peer judgment module;
the monitoring area dividing module inputs a monitored area map, and performs mesh division and coding on the monitored area by using the earth division mesh coding technology of the Beidou grid position code to obtain and output the mesh map;
the gridding module is used for inputting a person track, determining track grid areas according to the position of the person track on the grid map, forming a track grid set by all grids in each track grid area and outputting the track grid set;
the co-pedestrian judging module acquires the track grid sets of the two persons to be judged, judges whether the track grids in the track grid sets of the two persons meet or not, and judges that the two persons are co-pedestrians if the number of meeting grids exceeds a set threshold value.
7. The system of claim 6, wherein the gridding module is further configured to:
constructing a state relation index table aiming at the corresponding track grid area of each person;
the state relation index table comprises a personnel identity identification code ID, a moment t and a personnel state p; the person state p is the track grid code of the person at the moment t;
and determining the personnel states p at all discrete moments in the time period to be analyzed according to the constructed state relation index table to form a track grid set.
8. The system according to claim 6, wherein the co-pedestrian determination module employs the following method:
the trajectory grid sets of the two persons are respectively L1And L2；
First person trajectory grid set L1＝{(p1 n，t1 n) N1.. N }; n is the total number of the track grids of the first person; t is t1 nThe moment corresponding to the nth track grid of the first person; p is a radical of1 nThe personnel state corresponding to the nth track grid of the first personnel;
second person trajectory grid set L2＝{(p2 m，t2 m) M1.. M }; m is the total track grid number of the second person; t is t2 mThe moment corresponding to the mth track grid of the second person; p is a radical of2 mThe personnel state corresponding to the mth track grid of the second personnel;
judgment of L1And L2If the meeting grids exist, and the number of the meeting grids exceeds a set threshold value, judging that the two persons are the same person;
the set threshold is set as: r × min (L)1),Length(L2) ); wherein length (L)1) Represents L1Length of (d); length (L)2) Represents L2Length of (d); r is a set scale;
for the nth trajectory grid (p) in the first person trajectory grid set1 n，t1 n) And the mth trajectory grid (p) in the second set of person trajectory grids2 m，t2 m) If the following four conditions are simultaneously satisfied, the two are the meeting grids:
condition a: | distance (p)1 n,p2 m)|<dist; wherein | distance (p)1 n,p2 m) Represents p1 n,p2 mA linear distance between the center points of the two may be used; dist is a preset distance threshold;
condition b: | t1 n-t2 m|<tim; wherein tim is predeterminedA time threshold of (d);
condition c: p is a radical of2 mIs L2Satisfies the condition b and a distance p1 nA nearest trajectory grid;
condition d: if p of condition c is satisfied2 mIf the number of the cells exceeds 1, selecting t from the number1 n-t2 mThe minimum grid of is p1 nThe meeting grid.
9. A computer readable storage medium having stored thereon computer instructions, wherein said instructions when executed by a processor implement the steps of the Beidou grid based peer identification method of any of claims 1-5.
CN202110910133.2A 2021-08-09 2021-08-09 Method, system and storage medium for identifying staff on basis of Beidou grid Active CN113806459B (en)

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