Campus security monitoring method and apparatus

Abstract

This application relates to the field of smart campus technology and provides a campus security monitoring method and device. The campus security monitoring method includes: collecting facial images of personnel when they enter or exit the campus through a campus access control gate; acquiring historical combinations of people who have been identified by the personnel when they pass through the access control gate, and the corresponding sets of people for these historical combinations; searching for the personnel's identity information from the set of people corresponding to the historical combinations based on the facial images; if the personnel's identity information cannot be found from the set of people corresponding to the historical combinations, searching for the personnel's identity information based on the entire campus personnel set; and if the personnel's identity information is found, controlling the campus access control gate to switch to a preset open state and adjusting the historical combinations of people to monitor personnel entering and exiting the campus. The campus security monitoring method and device of this application can improve the efficiency of identity verification when entering and exiting the campus.

Description

Technical Field

[0001] This application relates to the field of smart campus technology, specifically to a campus security monitoring method and equipment. Background Technology

[0002] As a place with a high density and mobility of people, ensuring the safety of people entering and exiting the campus and improving the efficiency of passage are the core of campus security monitoring. To achieve secure control over the entry and exit of people on campus, identity verification of people passing through key entrances and exits is usually carried out.

[0003] Currently, the identity verification method in related technologies mainly uses facial recognition technology. When a person passes through the campus access control point, the person's facial image is collected. Then, the facial information and identity information of all registered students on campus are retrieved. The collected facial image is compared with the facial information of all students on campus one by one to find and confirm the person's identity information. After the identity verification is completed, the person is allowed to pass.

[0004] However, the full-scale comparison method used in the relevant technologies requires comparing facial information one by one from a large number of campus personnel. The comparison calculation is large, the single recognition takes a long time, and the identity verification efficiency is low. Summary of the Invention

[0005] In view of this, this application aims to propose a campus security monitoring method to improve the efficiency of identity verification.

[0006] To achieve the above objectives, the technical solution of this application is implemented as follows:

[0007] A campus security monitoring method includes:

[0008] When personnel enter or exit the campus through the campus access control checkpoint, the system collects the personnel's facial images and obtains the historical companion groups identified when the personnel passed through the campus access control checkpoint, as well as the personnel sets corresponding to the historical companion groups.

[0009] Based on the facial image, the identity information of the person is retrieved from the group of people corresponding to the historical group of people traveling together;

[0010] When the identity information of the person cannot be found in the personnel set corresponding to the historical peer group, the identity information of the person is searched based on the full campus personnel set;

[0011] Once the identity information of the person is found, the campus access control gate is switched to a preset open state, and the historical group of people traveling together is adjusted to monitor the people entering and leaving the campus.

[0012] Furthermore, when multiple historical peer-to-peer (PBP) combinations are obtained, the step of searching for the identity information of the individuals from the set of individuals corresponding to the PBP combinations includes:

[0013] Determine the priority of each of the aforementioned historical peer groups;

[0014] Based on the priority of each of the historical peer groups, the identity information of the person is searched sequentially from the personnel set corresponding to each of the historical peer groups until the identity information of the person is found or the personnel set corresponding to each of the historical peer groups does not contain the person.

[0015] Furthermore, the personnel set corresponding to the historical peer personnel combination includes at least one personnel subset, and each personnel subset corresponds to a preset search priority;

[0016] The step of searching for the identity information of the person from the person set corresponding to each of the aforementioned historical peer groups includes:

[0017] The subsets of personnel are sorted according to the preset search priority.

[0018] Starting from the first subset of personnel, search for the identity information of the personnel within the subset of personnel;

[0019] If the identity information of the person is not found, determine the next subset of people and search for the identity information of the person again until the identity information of the person is found, or the identity information of the person is not found in any of the subsets of people.

[0020] Furthermore, if the identity information of the person is found, adjusting the historical group of people traveling together includes:

[0021] If the identity information of the person is found in the set of people corresponding to the target historical peer group, the possible peer group of the person is determined based on the identity information of the person.

[0022] The personnel are assigned to the target historical peer group, and a new personnel group corresponding to the target historical peer group is determined based on the possible peer group of the personnel and the personnel group corresponding to the target historical peer group.

[0023] Furthermore, the target historical group of people includes at least one historical person who entered or exited the campus;

[0024] The step of determining the new set of people corresponding to the target historical combination of people based on the possible set of people traveling with the person and the set of people corresponding to the target historical combination of people traveling with the person includes:

[0025] Determine the possible sets of companions for each person entering and exiting the historical campus, and obtain the sets of companions for each historical campus.

[0026] Determine the possible sets of companions of the stated personnel, and the intersections of these sets with each of the stated historical sets of companions, to obtain each independent intersection;

[0027] Determine the common intersection between the stated personnel and all historical personnel who entered and exited the campus;

[0028] The preset search priority of the common intersection is determined as the highest priority, and the preset search priority corresponding to each of the independent intersections is determined respectively, so as to obtain the personnel set corresponding to the new target historical peer personnel combination.

[0029] Furthermore, determining the priority of each of the independent intersections includes:

[0030] Based on the order of entry and exit of historical campus personnel corresponding to each independent intersection, the priority of each independent intersection is determined sequentially.

[0031] The later the order in which people entered and exited the campus in the past, the higher the priority of the corresponding independent intersection.

[0032] Furthermore, determining the set of possible companions of the person based on their identity information includes:

[0033] Based on the identity information of the person, determine the preset group characteristic data corresponding to the person;

[0034] Based on the preset group characteristic data, determine the behavioral characteristics that the person may be involved in;

[0035] Based on the preset group characteristic data and the behavioral characteristics, the possible group of people traveling with each person is determined from the total number of campus personnel.

[0036] Compared with related technologies, this application has the following advantages:

[0037] The campus security monitoring method described in this application does not directly search for the identity information of a person entering or leaving the campus from the total number of campus personnel. Instead, it analyzes from the perspective of group behavior and first searches for the corresponding identity information from the personnel set corresponding to historical group combinations. In this way, when a person is traveling with the person in front of them, the person's identity information can be directly and quickly found from the personnel set corresponding to historical group combinations, thereby improving the efficiency of identity recognition when people enter or leave the campus and reducing congestion.

[0038] Another object of this application is to provide an electronic device comprising:

[0039] Memory, which stores computer programs;

[0040] A processor is used to execute the computer program stored in the memory to implement the campus security monitoring method described above.

[0041] Another objective of this application is to provide a campus security monitoring device, comprising:

[0042] The data acquisition module is used to acquire facial images of personnel when they enter or exit the campus through the campus access control gate, and to obtain historical pairs of people identified when personnel pass through the campus access control gate, as well as the set of people corresponding to the historical pairs of people.

[0043] The first identity lookup module is used to look up the identity information of a person from the set of people corresponding to the historical group of people based on the facial image;

[0044] The second identity lookup module is used to look up the identity information of a person based on the full set of campus personnel when the identity information of the person cannot be found in the personnel set corresponding to the historical peer group.

[0045] The control module is used to control the campus access control gate to switch to a preset open state when the identity information of the person is found, and to adjust the historical group of people traveling together, so as to monitor the people entering and leaving the campus.

[0046] Another objective of this application is to provide a computer-readable storage medium storing a computer program that, when executed by a processor, enables the implementation of the aforementioned campus security monitoring method.

[0047] The electronic devices, campus security monitoring devices, and computer-readable storage media described in this application can directly and quickly retrieve the identity information of personnel from the corresponding personnel set of historical group members when personnel enter or leave the campus, without having to traverse the information of all personnel. This can improve the efficiency of identity recognition when personnel enter or leave the campus and reduce congestion. Attached Figure Description

[0048] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0049] Figure 1 This is a flowchart illustrating the campus security monitoring method described in the embodiments of this application;

[0050] Figure 2This is a schematic diagram illustrating the structure of the electronic device described in the embodiments of this application;

[0051] Figure 3 This is a schematic diagram illustrating the structure of the campus security monitoring device described in the embodiments of this application;

[0052] Explanation of reference numerals in the attached figures:

[0053] 210. Processor; 220. Memory;

[0054] 310. Data Acquisition Module; 320. First Identity Lookup Module; 330. Second Identity Lookup Module; 340. Control Module. Detailed Implementation

[0055] To make the technical solution and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0056] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other.

[0057] Furthermore, it should be noted that in the description of this application, if terms such as "upper," "lower," "inner," or "outer" appear, indicating orientation or positional relationship, these are based on the orientation or positional relationship shown in the accompanying drawings and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this application. In addition, if terms such as "first" or "second" appear, they are also used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0058] Furthermore, in the description of this application, unless otherwise expressly defined, the terms "installation," "connection," "joining," and "connector" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application in light of the specific circumstances.

[0059] In this application, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0060] The present application will now be described in detail through exemplary embodiments. However, it should be understood that, without further description, elements, structures, and features in one embodiment may be advantageously incorporated into other embodiments.

[0061] The first aspect of this application provides a campus security monitoring method. When personnel enter or leave the campus, instead of directly searching for the personnel's identity information from the entire campus population, the method analyzes group behavior and first searches for the corresponding identity information from the population corresponding to historical group members. In this way, when the personnel are in the same group as the preceding personnel, the personnel's identity information can be directly and quickly found from the population corresponding to historical group members, thereby improving the efficiency of identity recognition when personnel enter or leave the campus and reducing congestion.

[0062] In related technologies, campuses, as places with high population density and mobility, are the core of campus security monitoring work, which is to ensure the safety of people entering and leaving the campus and improve the efficiency of passage.

[0063] In related technologies, in order to achieve security control of personnel entering and exiting the campus, campus access control checkpoints are usually set up at key entrances and exits such as the main gate and side gates. Students, teachers, logistics staff and other campus-related personnel, as well as registered visitors, must complete identity verification through the campus access control checkpoints before they can pass.

[0064] Currently, the identity verification method in related technologies mainly uses facial recognition technology. Its core implementation logic is as follows: when a person passes through the campus access control checkpoint, the access control device set up at the campus access control checkpoint will collect the person's facial image, and then directly call the full set of campus personnel (including the facial information and identity information of all registered personnel on campus), compare the collected facial image with the facial information in the full set of campus personnel one by one, so as to find and determine the person's identity information, and release the person after completing the identity verification.

[0065] However, the full-scale comparison method used in related technologies requires comparing facial information one by one from a large pool of campus personnel, regardless of whether the person entering or exiting is in the same group as the person preceding them. This results in a large computational load, long recognition time per session, and low efficiency in verifying individual identities. During peak campus periods (such as morning arrival and evening dismissal), the concentration of people entering and exiting leads to long queues for identification, which can easily cause congestion at access control points. This not only affects the passage experience but may also lead to safety hazards such as stampedes due to congestion.

[0066] In view of this, in order to overcome the shortcomings of related technologies, the campus security monitoring method in this embodiment combines... Figure 1 In terms of overall design, it includes the following steps S110-S140.

[0067] Step S110: When personnel enter or exit the campus through the campus access control gate, collect the personnel's facial images, and obtain the historical companion groups identified when personnel pass through the campus access control gate, as well as the personnel sets corresponding to the historical companion groups.

[0068] Among them, the historical companion group is the companion group formed when people enter and exit within a preset historical time period. The personnel set corresponding to this historical companion group is composed of the possible companion groups corresponding to each companion in the group.

[0069] The set of possible companions for each person is the set of people who may travel with that person.

[0070] In step S110, the facial images of the personnel being collected can be facial images collected by access control equipment (such as cameras) installed at the campus access control checkpoints.

[0071] Taking student A1 as an example, when student A1 enters the campus, they need to pass through the campus access control checkpoint. The camera of the access control device will capture a facial image of student A1. The access control device will then verify the identity of student A1 based on the facial image. If the identity verification is successful, the student can enter. If the identity verification fails (the relevant identity information of student A1 cannot be found), the student will not be allowed to enter the campus.

[0072] Therefore, in step S110, when personnel enter or exit the campus through the campus access control gate, their facial images are first collected, and then the facial images are used for identity verification.

[0073] To improve the efficiency of personnel identity verification, in this embodiment, after acquiring a face image, the historical group of people traveling together and the corresponding group of people are first obtained. Then, steps S120-S140 are executed to use the group of people corresponding to the historical group of people traveling together and the face image to perform identity verification.

[0074] Step S120: Based on the facial image, search for the identity information of the person from the group of people corresponding to the historical group of people.

[0075] Step S130: When the identity information of a person cannot be found in the personnel set corresponding to the historical peer personnel combination, the identity information of the person is searched based on the full campus personnel set.

[0076] In steps S120 and S130, finding a person's identity information can be achieved by comparing the face image with each pre-stored face image in the personnel set. If the comparison is successful, the identity information corresponding to the successfully matched pre-stored face image is the person's identity information. (The personnel set includes preset face images and the identity information corresponding to each preset face image. This identity information can be information indicating the person's identity, such as the person's ID number, and is not limited here.)

[0077] Alternatively, to find the identity information of a person based on the full set of campus personnel, one can remove the personnel set corresponding to the historical peer group obtained in step S110 above from the full set of campus personnel, obtain the remaining personnel set, and then search for the identity information of the person from the remaining personnel set.

[0078] Step S140: After finding the identity information of the person, control the campus access control gate to switch to the preset open state and adjust the historical group of people traveling together in order to monitor the people entering and leaving the campus.

[0079] For example, when the first student (e.g., student A11) enters the campus, assuming that no one has entered the campus within a preset time period before student A11, the historical group of people who accompanied the student obtained in step S110 is an empty set. Therefore, the identity information of student A11 cannot be found through step S120. In this case, the identity information of student A11 is searched from the entire set of campus personnel. If the identity information of student A11 is found, the campus access control gate is switched to the preset open state, that is, the campus access control gate is opened, so that student A1 can pass through and enter the campus.

[0080] After student A11 enters the campus, a historical peer group X1 is established. This historical peer group X1 includes student A11, and the possible peer group corresponding to student A11 is the peer group Y1 corresponding to the historical peer group X1.

[0081] Assuming student A12 and student A11 are roommates and friends, A12 belongs to student A11's possible companion set B11. Assuming student A12 and student A11 enter the school together, after student A11 passes through the campus access control, student A12 will often arrive at the campus access control within a preset historical time period. At this time, when student A12 arrives at the campus access control, in step S110, student A12's facial image is captured, and the historical companion combination X1 is obtained. Then, in step S120, student A2's identity information is first searched from the personnel set Y1 (that is, the possible companion set B11) corresponding to the historical companion combination X1, and then student A12's identity information is found, thus completing the passage of student A12.

[0082] This eliminates the need to perform step S130, which involves searching for student A12's identity information one by one from the entire campus population. Instead, it first filters out individuals who are likely to enter or leave the campus from the perspective of their companions, and then searches for them first. This reduces the number of facial image comparisons, the time required for facial recognition, and improves the efficiency of people entering and leaving the campus, thereby reducing congestion.

[0083] In some embodiments, in step S140 above, if the identity information of the person is found, it is also necessary to adjust the currently obtained historical peer group in order to update the historical peer group and divide each person in the same peer group into a historical peer group.

[0084] Specifically, step S140, which involves adjusting the historical group of people traveling together, may include:

[0085] If the identity information of a person is found in the set of people corresponding to the target historical peer group, the possible peer group of the person is determined based on the identity information of the person; the person is assigned to the target historical peer group, and the set of people corresponding to the new target historical peer group is determined based on the possible peer group of the person and the set of people corresponding to the target historical peer group.

[0086] If, in step S120, the identity information of the person currently entering or leaving the campus is not found from the personnel set corresponding to the historical companion personnel combination, but is found from the entire campus personnel set in step S130, then when adjusting the historical companion personnel combination, a new companion personnel combination can be added, and the person can be assigned to the newly added companion personnel combination. When the next person enters or leaves the campus, this newly added companion personnel combination will be obtained as a historical companion personnel combination.

[0087] For example, continuing with the example of students A11 and A12 traveling together, when student A12 enters the campus, the identity information of student A12 is found in the personnel set Y1 corresponding to the historical companion personnel combination X1 corresponding to student A11. Therefore, student A12 is merged into the historical companion personnel combination X1, that is, the historical companion personnel combination X1 is updated to include student A11 and student A12. The personnel set Y1 corresponding to the historical companion personnel combination X1 includes the possible companion personnel set B11 of student A11 and the possible companion personnel set B12 corresponding to student A12.

[0088] Suppose that after student A11, student A21 enters the campus. Student A21 and student A11 are not traveling together. When student A21 enters the campus, it is often impossible to find student A21's identity information from the personnel set Y1; instead, the identity information of student A21 can only be found from the entire campus personnel set. At this time, the historical travel companion combination X1 still only includes student A11. A new historical travel companion combination X2 is added, and student A21 is assigned to this historical travel companion combination X2. The possible travel companion set B21 of student A21 is the personnel set Y2 of the historical travel companion combination X2. In this way, when the next student enters the campus, the obtained historical travel companion combination will include both historical travel companion combination X1 and historical travel companion combination X2.

[0089] It is worth noting that if a group of historical companions has not been updated within a preset historical time period, it indicates that the current group of companions has most likely entered (or left) the campus, and in this case, the historical companion group is deleted. That is, in this embodiment, only historical companion groups within a preset historical time period are retained. These historical companion groups within the preset historical time period include: historical companion groups established within the preset historical time period and updated within the preset historical time period.

[0090] It is also worth noting that in this embodiment, the historical companion groups for those entering the campus and those leaving the campus are managed separately and do not interfere with each other. For those entering the campus, their identity information is identified using the historical companion groups corresponding to their entry into the campus; for those leaving the campus, their identity information is identified using the historical companion groups corresponding to their departure from the campus. Further details will not be elaborated here.

[0091] In some embodiments, the step of determining the set of possible companions of a person based on their identity information may specifically include: determining the preset group characteristic data corresponding to the person based on their identity information; determining the behavioral characteristics that the person may be involved in based on the preset group characteristic data; and determining the set of possible companions of the person from the entire campus population based on the preset group characteristic data and the behavioral characteristics.

[0092] Specifically, the preset group characteristic data can be the person's campus identity information. In particular, the campus identity information can include the person's identity attributes (such as student / teacher / logistics staff, etc.), the student's corresponding class / dormitory / club / timetable information, the teacher's corresponding teaching and research group / office area information, and the logistics staff's corresponding work group information.

[0093] Taking students as an example, the preset group characteristic data corresponding to the student may include the student's campus identity (student), major, class, dormitory, club / class group, and class schedule information (including class time, class location, and classmates).

[0094] The preset group characteristic data can be directly extracted from the campus management system based on the current personnel's identity information (such as student ID, teacher employee ID).

[0095] Then, based on the preset group characteristic data, the behavioral characteristics of the person are determined. These behavioral characteristics refer to the group behaviors that the person may be involved in, as determined based on the preset group characteristic data. For example, the group behaviors that students may be involved in on campus include: class-related group behaviors, dormitory-related group behaviors, major-related group behaviors, and club-related group behaviors.

[0096] Among them, class-related group behavior refers to the high probability that students in the same class, who need to attend and leave school together before class and after class, will enter and leave school together. Class-related group behavior can be determined based on group characteristic data such as "class and timetable".

[0097] Dormitory-related group behavior: Students in the same dormitory have similar schedules and are likely to arrive at school together in the morning and leave together in the evening, or go out and return to school together on weekends. Based on the individual's dormitory group characteristic data, the dormitory-related group behavior can be determined.

[0098] Professionally Associated Group Behavior: Students in the same major and taking the same courses (including electives) at the same locations and times are highly likely to travel to and from campus together. Professionally associated group behavior can be determined based on the individual's professional group characteristics data.

[0099] Club-related group behavior: Students in the same club or class group are highly likely to enter and leave campus together after participating in club or group activities. Club-related group behavior can be determined based on the individual's "club-specific" group characteristic data.

[0100] Subsequently, in this embodiment, when determining the set of possible companions for a person, individuals who may engage in various group behaviors with that person are selected from the entire campus population to form the set of possible companions.

[0101] For example, select all members of the same dormitory, all members of the same class, students of the same major who have one or more common courses, members of the same club, and members who may participate in club activities, as a group of potential travel companions.

[0102] Furthermore, in some embodiments, when student A11 and student A12 are traveling together, it is possible that after student A11 enters, student A21 enters first, and then student A12 enters (students A11 and A12 are traveling together, while student A21 is not traveling with student A11). Assuming that in this case, student A11 and student A21 have already passed through the campus access control checkpoint, and student A12 is currently undergoing identity verification at the campus access control checkpoint.

[0103] At this point, in step S110, two historical companion groups will be obtained: historical companion group X1 containing student A11, and historical companion group X2 containing student A21. In the case of obtaining multiple historical companion groups, step S120 above, which involves searching for the identity information of individuals from the group corresponding to each historical companion group, may specifically include:

[0104] Determine the priority of each historical peer group; based on the priority of each historical peer group, search for the identity information of the person in the person set corresponding to each historical peer group in turn, until the identity information of the person is found or the person set corresponding to each historical peer group does not contain any person.

[0105] The priority of historical peer groups can be determined based on the order of passage. The closer the last person in a historical peer group passed through the campus access control point to the current time, the higher the priority of that historical peer group. In other words, the closer the update time of a historical peer group is to the current time, the higher its priority.

[0106] That is, in the example above, the person to be identified is student A12. Among the two historical peer groups that have passed, student A21 passed later than student A11. Therefore, the historical peer group X2 (including student A21) has a higher priority than the historical peer group X1 (including student A11). The priority order is: X2 > X1.

[0107] When searching for the identity information of the person to be identified, first search from the highest priority historical peer group X2, and then search from the historical peer group X1.

[0108] If student A21 enters the campus first, and student A11 enters later, meaning student A21's entry time is earlier than student A11's, then the priority of historical companion group X2 (including student A21) will be lower than that of historical companion group X1 (including student A11). The priority order is: X2 < X1. When searching for the identity information of the person to be identified, the search is first performed from the highest priority historical companion group X1, and then from the historical companion group X2.

[0109] This prioritizes searching for recently frequented historical peer groups. Since the probability of the person to be identified being in the same group as a recently frequented historical peer group is higher than in the past, this prioritizes searching for recently frequented historical peer groups, which can further shorten the search time. Even if a peer is cut in line, the person's identity information can still be identified from the corresponding historical peer group later.

[0110] Furthermore, assuming that students A11 and A21 enter the campus one after the other, student A12, who is traveling with student A11, arrives at the campus access control checkpoint. After retrieving student A12's identity information from the historical companion group X1, student A12 enters the campus. At the same time, student A12 is also assigned to the historical companion group X1, and the priority of the historical companion group X1 is updated to be higher than the priority of the historical companion group X2.

[0111] In this state, the historical companion group X1 includes both student A11 and student A12, and the historical companion group X2 includes student A21. That is, each historical companion group includes at least one person entering or leaving the historical campus.

[0112] In some embodiments, when adjusting the historical companion group, this step determines the group corresponding to the new target historical companion group based on the possible companion group of the individual and the group corresponding to the target historical companion group. Specifically, this may include: determining the possible companion group of each historical campus entry / exit individual to obtain each historical companion group; determining the intersection of the individual's possible companion group with each historical companion group to obtain each independent intersection; determining the common intersection of the individual with all historical campus entry / exit individuals; assigning the priority of the common intersection as the highest priority, and determining the priority of each independent intersection to obtain the group corresponding to the new target historical companion group.

[0113] Specifically, continuing with the example above, the person currently entering and leaving the campus is A12. The identity information of student A12 is determined from the historical companion group X1. Therefore, the historical companion group X1 is the target historical companion group, which is also the historical companion group that needs to be adjusted.

[0114] When determining the set of people Y1 corresponding to the historical group of people X1, it is determined based on the set of possible people B12 corresponding to student A12, and the set of possible people B11 corresponding to student A11 that was originally stored in the set of people Y1.

[0115] To further improve the speed of identity verification, in this embodiment, the personnel set corresponding to each historical companion group is divided into at least one personnel subset (that is, the personnel set is composed of at least one personnel subset), and a search priority is set for each personnel subset in the personnel set, so that each personnel subset corresponds to a preset search priority.

[0116] The higher the preset search priority of the personnel subset, the more likely the search will be performed in subsequent comparisons.

[0117] Therefore, in this embodiment, when determining the set of people corresponding to the target historical group of people, the possible sets of people who may be traveling with the person are first determined, and the intersections with each historical set of people who travel with the person are obtained to obtain each independent intersection. Then, the common intersection between the person and all historical people who have entered and exited the campus is determined. After that, based on the independent intersections and the common intersections, each subset of people is obtained, and then a corresponding preset search priority is set for each subset.

[0118] Among them, the preset search priority of the common intersection is the highest. When determining the preset search priority of each independent intersection, it can specifically include: determining the preset search priority of each independent intersection in turn according to the order of entry and exit of historical campus personnel corresponding to each independent intersection.

[0119] Among them, the later the order in which people entered and exited the campus, the higher the preset search priority of the corresponding independent intersection.

[0120] For example, taking the target historical peer group as historical peer group X1 as an example, we find the intersection of the possible peer group B12 of student A12 and the possible peer group B11 of student A11 as an independent intersection, and at the same time, this independent intersection is also a common intersection.

[0121] Therefore, the possible traveler set B12 and the possible traveler set B11 are merged (and deduplicated) to obtain a complete set of people. Then, the complete set of people is divided into three subsets: the common intersection, the remaining set of people corresponding to the possible traveler set B12, and the remaining set of people corresponding to the possible traveler set B11.

[0122] For another example, if the historical group of people traveling together X1 includes student A11 (who entered the campus first) and student A12 (who entered the campus later), and now student A13 (who traveled with students A11 and A12) enters the campus, when adjusting the historical group of people traveling together X1 after student A13 (corresponding to the possible group of people traveling together B13) enters the campus, the intersection of the possible group of people traveling together B13 and the possible group of people traveling together B12 is calculated to obtain an independent intersection M23; the intersection of the possible group of people traveling together B13 and the possible group of people traveling together B11 is calculated to obtain an independent intersection M13; the intersection of the possible group of people traveling together B11 and the possible group of people traveling together B12 is calculated to obtain an independent intersection M12; the intersection of the three possible groups of people traveling together B11, B12 and B13 is calculated to obtain a common intersection.

[0123] Then, each person's subset is obtained by dividing the data into common intersections, independent intersections (the common intersections need to be removed from the independent intersections, referring to the independent intersections after removal), and the set of possible companions for each person (the remaining part after removing the independent intersections and common intersections).

[0124] Among these, the common intersection has the highest priority. For each independent intersection, when determining the preset search priority for intersections belonging to the same level, it is determined according to the order of occurrence; the closer the occurrence is to the present, the higher the preset search priority. For example, if student A13 is later than student A12, and later than student A11, then the preset search priority of the independent intersection of student A12 and student A13 is higher than the preset search priority of the independent intersection of student A13 and student A11, which is higher than the preset search priority of the independent intersection of student A11 and student A12.

[0125] It's worth noting that when the number of people in a historical travel companion group is too large, such as four or more, assuming the group includes N historical travelers, when dividing the group into subsets, the intersections are obtained sequentially in the following ways: N people share, N-1 people share, N-2 people share, ..., 2 people share. After obtaining the intersections, the group is further divided into subsets in the following ways: subsets shared by N people, subsets shared by N-1 people, subsets shared by N-2 people, subsets shared by 2 people, and the remaining subset (the total number of people remaining excluding the shared subsets, without distinguishing individual individuals).

[0126] Next, the preset search priority of each personnel subset is confirmed. When confirming the preset search priority of each personnel subset, if the historical peer personnel combination includes N personnel (including the personnel currently included), then the preset search priority is determined in the following order: the common subset of N personnel, the common subset of N-1 personnel, the common subset of N-2 personnel, ... the common subset of 2 personnel, and the remaining personnel set. The preset search priorities are set in descending order.

[0127] In addition, for example, the intersection of student A12 and student A11, the intersection of student A11 and student A13, and the intersection of student A12 and student A13 all belong to the common subset of N-1 people. It is also necessary to divide the preset search priority of these three. When determining the preset search priority of such people belonging to the same level, it is also determined according to the passage time sequence. The closer the passage is to the current time, the higher the preset search priority.

[0128] Furthermore, in some embodiments, when the next person passes through and needs to be compared with the set of people corresponding to the historical companions for identity matching, the search can be performed sequentially from each subset of people according to the preset search priority, so as not to traverse in an unordered manner.

[0129] Specifically, in the above steps, the identification information of individuals is retrieved from the personnel sets corresponding to each historical group of peers. This may include:

[0130] The subsets of personnel are sorted according to a preset search priority. Starting with the first subset, the identity information of the personnel is searched within that subset. If no identity information is found, the next subset is selected, and the search for personnel identity information is repeated until the identity information of a personnel is found, or no personnel identity information is found in any subset.

[0131] For example, taking the passage sequence as follows (student A11-student A21-student A12-student A1), and the current person to be identified is student A14 (student A14 is a fellow traveler with students A11, A12, and A13, but has no connection with student A21), the process of finding student A14's identity information is illustrated as follows:

[0132] Before student A14 could pass through, the individuals who had already passed through the access control were students A11, A21, A12, and A13, forming two independent groups of people traveling together.

[0133] Historical peer group X1: includes students A11, A12, and A13; the corresponding subsets of the peer group are ordered in order of preset search priority: Preference subset X1-123 (the common intersection of students A11, A12, and A13), Preference subset X1-23 (the intersection of possible peer groups of students A12 and A13), Preference subset X1-13 (the intersection of possible peer groups of students A12 and A13), Preference subset X1-12 (the intersection of possible peer groups of students A12 and A13), Preference subset X1-Remaining (the remaining peers in the possible peer groups of students A11, A12, and A13).

[0134] History peer group X2: includes student A21.

[0135] First, the priority of the two historical companion groups is determined according to their passage time. Since student A21's passage time is earlier than student A13, the overall passage time of historical companion group X1 is closer to the current person to be identified, A14. The priority order of historical companion groups is: historical companion group X1 > historical companion group X2.

[0136] Subsequently, when searching for the identity information of student A13 from the personnel set corresponding to the historical peer group X1, the personnel subsets are sorted in order from first to last according to the preset search priority, namely: personnel subset X1-123, personnel subset X1-23, personnel subset X1-13, personnel subset X1-12, personnel subset X1-remaining.

[0137] Next, the system first searches for the identity information of the current student A14 in the subset X1-123. If it is not found, it searches for the identity information of the current student A14 in the next subset X1-23. If it is still not found, it searches for the identity information of the current student A14 in the next subset X1-13, and so on. If the identity information of the current student A14 is found, the loop ends and step S140 is executed to open the campus access control gate, so that student A14 can enter and exit the campus.

[0138] If student A14's identity information is not found in the personnel set Y1 corresponding to the historical companion group X1, then the search continues in the personnel set Y2 corresponding to the historical companion group X2. If student A14's identity information is also not found in the personnel set Y2 corresponding to the historical companion group X2, then step S130 is executed to search the entire campus personnel set. If student A14's identity information is also not found in the entire campus personnel set, it means that student A14's identity verification has failed and passage is denied.

[0139] Therefore, by splitting the set of people corresponding to historical companion groups into subsets of people with different priorities, and searching them step by step in descending order of preset search priority, prioritizing the subset of people with the highest probability of being companions, this avoids unordered traversal of all people and the need to directly call the entire campus personnel set for comparison. Instead, it sequentially traverses the set of people with the highest probability of being companions, thus enabling companions to quickly complete identity verification, reducing the time spent searching facial images, and effectively alleviating the problem of queuing congestion at the campus access control points during peak hours of school arrival and departure.

[0140] It is worth noting that, regarding the campus security monitoring method of this embodiment, based on the above exemplary implementations, in specific implementation, as a preferred embodiment, it is still based on... Figure 1 As shown, this could include, for example, the following steps: When personnel enter or exit the campus through a campus access control gate, first, a facial image of the personnel is captured, and historical combinations of companions identified when the personnel passed through the same access control gate are obtained, along with the corresponding sets of personnel for each historical companion combination. Then, based on the facial image, the personnel's identity information is searched sequentially according to the order of each historical companion combination. If the personnel's identity information cannot be found within the set of personnel corresponding to a historical companion combination, then the personnel's identity information is searched based on the entire set of campus personnel. If the personnel's identity information is found, the campus access control gate is opened, allowing personnel to pass through, thus achieving the purpose of monitoring personnel entering and exiting the campus. Furthermore, even after a personnel's identity information is found, the historical companion combinations are adjusted to facilitate identity lookup for the next person.

[0141] It is worth noting that if the identity information of a person cannot be found even if all the campus personnel are gathered, that person will be prohibited from passing.

[0142] In the preferred embodiment of the above campus security monitoring method, the specific implementation of each step can still be found in the descriptions of the above exemplary embodiments, and the beneficial effects brought about by the design of each step in this preferred embodiment can also be found in the descriptions of the above exemplary embodiments.

[0143] The campus security monitoring method in this embodiment adopts the above design. When people enter or leave the campus, instead of directly searching for the person's identity information from the entire set of campus personnel, it analyzes from the perspective of group behavior and first searches for the corresponding identity information from the set of personnel corresponding to historical group members. In this way, when the person is in the same group as the person in front, the person's identity information can be directly and quickly found from the set of personnel corresponding to historical group members without having to traverse the entire set. This can improve the efficiency of identity recognition when people enter or leave the campus and reduce congestion.

[0144] An embodiment of the second aspect of this application provides an electronic device, with reference to... Figure 2 , Figure 2 The illustrated electronic device includes a processor 210 and a memory 220. The processor 210 and the memory 220 are connected, for example, via a bus. Optionally, the electronic device may also include a transceiver. It should be noted that in practical applications, the transceiver is not limited to one unit, and the structure of this electronic device does not constitute a limitation on the embodiments of this application.

[0145] The memory 220 is used to store application code that executes the solution of this application, and its execution is controlled by the processor 210. The processor 210 is used to execute the application code stored in the memory 220 to implement the content shown in the foregoing method embodiments.

[0146] Among them, electronic devices include, but are not limited to: mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (such as in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers, and can also be servers, etc. Figure 2 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0147] The electronic device in this embodiment, by executing the campus security monitoring method in the above method embodiment, can, when people enter or leave the campus, not directly search for the identity information of the person from the entire campus population, but analyze from the perspective of group behavior, first search for the corresponding identity information from the population corresponding to the historical group of people traveling together. In this way, when the person is traveling with the person in front of him, the person's identity information can be directly and quickly found from the population corresponding to the historical group of people traveling together, without having to traverse the entire population. This can improve the efficiency of identity recognition when people enter or leave the campus and reduce congestion.

[0148] An embodiment of the third aspect of this application provides a campus security monitoring device, referring to... Figure 3 The campus security monitoring device includes a data acquisition module 310, a first identity lookup module 320, a second identity lookup module 330, and a control module 340.

[0149] The aforementioned data acquisition module 310 is used to acquire facial images of personnel when they enter or exit the campus through the campus access control gate, and to obtain historical combinations of companions identified when personnel have passed through the campus access control gate, as well as the corresponding personnel sets for these historical companion combinations. The aforementioned first identity lookup module 320 is used to look up the identity information of personnel from the personnel sets corresponding to historical companion combinations based on the facial images. The aforementioned second identity lookup module 330 is used to look up the identity information of personnel based on the entire campus personnel set when the identity information of personnel cannot be found from the personnel sets corresponding to historical companion combinations. The aforementioned control module 340 is used to control the campus access control gate to switch to a preset open state and adjust the historical companion combinations when the identity information of personnel is found, in order to monitor personnel entering and exiting the campus.

[0150] Specifically, in the implementation of the campus security monitoring device of this embodiment, the above-mentioned modules can be existing module products with data transmission, storage or computing functions.

[0151] In practical applications, the specific implementation process of the functions of each module in the campus security monitoring device of this embodiment can be found in the relevant descriptions in the above method embodiments, and will not be repeated here.

[0152] In this embodiment, the campus security monitoring device does not directly search for the identity information of a person entering or leaving the campus from the entire pool of campus personnel. Instead, it analyzes from the perspective of group behavior and first searches for the corresponding identity information from the pool of personnel corresponding to previous group members. In this way, when a person is traveling with the person in front of them, the person's identity information can be directly and quickly found from the pool of personnel corresponding to previous group members without having to traverse the entire pool. This improves the efficiency of identity recognition when people enter or leave the campus and reduces congestion.

[0153] An embodiment of the fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when run on a computer, enables the computer to execute the corresponding content in the foregoing method embodiments. The storage medium may be a read-only memory, a magnetic disk, or an optical disk, etc.

[0154] The above are merely some embodiments of this application and are not intended to limit this application. The technical features or structures in the foregoing different embodiments can be arbitrarily combined to form other specific technical solutions as needed. For those skilled in the art, this application can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of this application should be included within the protection scope of the claims of this application.

Claims

1. A campus security monitoring method, characterized in that, include: When personnel enter or exit the campus through the campus access control checkpoint, the system collects the personnel's facial images and obtains the historical companion groups identified when the personnel passed through the campus access control checkpoint, as well as the personnel sets corresponding to the historical companion groups. Based on the facial image, the identity information of the person is retrieved from the group of people corresponding to the historical group of people traveling together; When the identity information of the person cannot be found in the personnel set corresponding to the historical peer group, the identity information of the person is searched based on the full campus personnel set; Once the identity information of the person is found, the campus access control gate is switched to a preset open state, and the historical group of people traveling together is adjusted to monitor the people entering and leaving the campus.

2. The campus security monitoring method according to claim 1, characterized in that, When multiple historical peer-to-peer (PBP) combinations are obtained, the step of searching for the identity information of the individuals from the set of individuals corresponding to the PBP combinations includes: Determine the priority of each of the aforementioned historical peer groups; Based on the priority of each of the historical peer groups, the identity information of the person is searched sequentially from the personnel set corresponding to each of the historical peer groups until the identity information of the person is found or the personnel set corresponding to each of the historical peer groups does not contain the person.

3. The campus security monitoring method according to claim 2, characterized in that, The set of people corresponding to the historical peer group includes at least one subset of people, and each subset of people corresponds to a preset search priority; The step of searching for the identity information of the person from the person set corresponding to each of the aforementioned historical peer groups includes: The subsets of personnel are sorted according to the preset search priority. Starting from the first subset of personnel, search for the identity information of the personnel within the subset of personnel; If the identity information of the person is not found, determine the next subset of people and search for the identity information of the person again until the identity information of the person is found, or the identity information of the person is not found in any of the subsets of people.

4. The campus security monitoring method according to claim 1, characterized in that, If the identity information of the person is found, adjusting the historical group of people traveling together includes: If the identity information of the person is found in the set of people corresponding to the target historical peer group, the possible peer group of the person is determined based on the identity information of the person. The personnel are assigned to the target historical peer group, and a new personnel group corresponding to the target historical peer group is determined based on the possible peer group of the personnel and the personnel group corresponding to the target historical peer group.

5. The campus security monitoring method according to claim 4, characterized in that, The target historical group of people includes at least one person who has entered or exited the campus in the past. The step of determining the new set of people corresponding to the target historical combination of people based on the possible set of people traveling with the person and the set of people corresponding to the target historical combination of people traveling with the person includes: Determine the possible sets of companions for each person entering and exiting the historical campus, and obtain the sets of companions for each historical campus. Determine the possible sets of companions of the stated personnel, and the intersections of these sets with each of the stated historical sets of companions, to obtain each independent intersection; Determine the common intersection between the stated personnel and all historical personnel who entered and exited the campus; The preset search priority of the common intersection is determined as the highest priority, and the preset search priority corresponding to each of the independent intersections is determined respectively, so as to obtain the personnel set corresponding to the new target historical peer personnel combination.

6. The campus security monitoring method according to claim 5, characterized in that, The step of determining the priority of each of the independent intersections includes: Based on the order of entry and exit of historical campus personnel corresponding to each independent intersection, the priority of each independent intersection is determined sequentially. The later the order in which people entered and exited the campus in the past, the higher the priority of the corresponding independent intersection.

7. The campus security monitoring method according to claim 4, characterized in that, The step of determining the set of possible companions of the person based on the person's identity information includes: Based on the identity information of the person, determine the preset group characteristic data corresponding to the person; Based on the preset group characteristic data, determine the behavioral characteristics that the person may be involved in; Based on the preset group characteristic data and the behavioral characteristics, the possible group of people traveling with each person is determined from the total number of campus personnel.

8. An electronic device, characterized in that, include: Memory, which stores computer programs; A processor is configured to execute the computer program stored in the memory to implement the campus security monitoring method according to any one of claims 1-7.

9. A campus security monitoring device, characterized in that, include: The data acquisition module is used to acquire facial images of personnel when they enter or exit the campus through the campus access control gate, and to obtain historical pairs of people identified when personnel pass through the campus access control gate, as well as the set of people corresponding to the historical pairs of people. The first identity lookup module is used to look up the identity information of a person from the set of people corresponding to the historical group of people based on the facial image; The second identity lookup module is used to look up the identity information of a person based on the full set of campus personnel when the identity information of the person cannot be found in the personnel set corresponding to the historical peer group. The control module is used to control the campus access control gate to switch to a preset open state when the identity information of the person is found, and to adjust the historical group of people traveling together, so as to monitor the people entering and leaving the campus.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it can implement the campus security monitoring method according to any one of claims 1-7.

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