Supervision Method, Device, Storage Medium and Electronic Device for Preventing Cheating in Examinations

Abstract

The present invention provides a supervision method, device, storage medium and electronic device for preventing cheating in examinations. The supervision method for preventing cheating in examinations includes: pre-acquiring reference photos of each candidate assigned seats in a target examination room, constructing a first mapping relationship between the reference photos of the candidates and the candidate position information of the candidates, and constructing a second mapping relationship between the acquisition parameters of a camera and the position information; collecting candidate photos in the target examination room, querying the second mapping relationship according to the current acquisition parameters for the current acquisition, and obtaining the acquisition position information mapped by the current acquisition parameters; querying the first mapping relationship and obtaining the candidate reference photos corresponding to the candidate position information mapped by the acquisition position information; and supervising the target examination room based on the candidate photos and the candidate reference photos. The supervision intensity of online examinations can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of face recognition, and in particular to a supervision method, device, storage medium and electronic device for preventing cheating in examinations. Background Art

[0002] With the development of the network, online examinations have been widely used in the industry due to their convenience, time and cost savings. To ensure the fairness of the examination, online examinations are generally centrally arranged in a fixed examination room, and some candidates can also take remote computer-based online examinations through the network. However, due to the remote nature of online examinations, there is a lack of supervision, and candidates are prone to cheating. Therefore, in online examinations, how to prevent candidates from cheating is an urgent problem to be solved.

[0003] Currently, using face recognition technology for examination supervision has become an important means. In examinations, face recognition technology is mainly used for user identity authentication when entering the examination. When candidates log in to the examination system, through face detection and recognition algorithms, the system can quickly and accurately verify the candidate's identity information. By matching with the pre-entered data, the candidate's identity is confirmed, preventing violations such as proxy examinations. By using face recognition technology for examination supervision, the fairness and standardization of the examination can be guaranteed, and the supervision efficiency can be improved.

[0004] However, this method can only identify and authenticate candidates when entering the examination, and cannot solve the situation of someone taking the examination on behalf of others or multiple people answering questions together during the examination. Therefore, the supervision intensity is relatively low. Summary of the Invention

[0005] In view of this, the present invention provides a supervision method, device, storage medium and electronic device for preventing cheating in examinations.

[0006] Specifically, the present invention is implemented through the following technical solutions:

[0007] According to a first aspect of the present invention, there is provided a supervision method for preventing cheating in examinations, the method comprising:

[0008] Pre-acquire reference photos of each candidate assigned seats in the target examination room, construct a first mapping relationship between the reference photos of the candidates and the candidate position information of the candidates, and construct a second mapping relationship between the acquisition parameters of the camera and the position information;

[0009] Collect candidate photos in the target examination room, query the second mapping relationship according to the current acquisition parameters for the current acquisition, and obtain the acquisition position information mapped by the current acquisition parameters;

[0010] Query the first mapping relationship, and obtain the candidate reference photo corresponding to the candidate position information mapped by the acquisition position information;

[0011] Based on the candidate photo and the candidate's reference photo, monitor the target examination room.

[0012] Preferably, the pre-acquisition of the reference photos of each candidate assigned seats in the target examination room includes:

[0013] Verify the identity card information of the candidate to confirm that the candidate is a candidate in the target examination room;

[0014] Collect the face of the candidate to obtain the reference photo of the candidate.

[0015] Preferably, the construction of the second mapping relationship between the acquisition parameters of the camera and the position information includes:

[0016] Obtain the positioning information of each camera deployed in the target examination room;

[0017] For each camera, set the shooting area of the camera;

[0018] Shoot at the target candidate position within the shooting area to obtain the camera parameters of this shooting;

[0019] Construct the second mapping relationship between the positioning information, the camera parameters and the target candidate position;

[0020] For each target candidate position within the shot shooting area, set the variation range of the camera parameters of the camera.

[0021] Preferably, the collection of the candidate photos in the target examination room includes:

[0022] According to the pre-set examination configuration information, make the camera parameters of the target camera vary within the variation range of the target camera, and collect candidate photos according to the changed camera parameters.

[0023] Preferably, the examination configuration information includes: the start time of the examination, the end time of the examination and the number of acquisitions of the target camera;

[0024] The step of making the camera parameters of the target camera vary within the variation range of the target camera according to the pre-set examination configuration information and collecting candidate photos according to the changed camera parameters includes:

[0025] During the examination time between the start time and the end time of the examination, set random acquisition time points according to the number of acquisitions, and the interval between each acquisition time point is greater than the pre-set time threshold;

[0026] Vary within the variation range of the target camera, randomly determine camera monitoring parameters, and adjust the acquisition parameters of the target camera to the camera monitoring parameters;

[0027] At the acquisition time point, acquire a photo according to the camera monitoring parameters.

[0028] Preferably, the supervision of the target examination room based on the candidate photo and the candidate reference photo includes:

[0029] Obtain the number of faces in the candidate photo. When the number of faces is greater than or less than 1, it is determined that the candidate has cheated;

[0030] When the number of faces is equal to 1, perform face comparison on the candidate photo and the candidate reference photo to obtain a similarity. When the similarity is less than a preset similarity threshold, it is determined that the candidate has cheated.

[0031] Preferably, the method further includes:

[0032] Perform live detection on the candidate photo. If the live detection result is not a live body, it is determined that the candidate has cheated.

[0033] The supervision method for preventing cheating in this embodiment uses live detection technology and face detection technology to identify the identity of candidates. By acquiring candidate photos at random time points during the examination, performing face detection and face comparison on the candidate photos and the pre-acquired reference photos, the supervision of candidates during the examination is realized, which has better examination supervision intensity and fairness.

[0034] According to the second aspect of the present invention, there is provided a supervision device for preventing cheating in an examination. The supervision device for preventing cheating in an examination includes:

[0035] A reference photo acquisition module, configured to pre-acquire reference photos of each candidate assigned seats in a target examination room, construct a first mapping relationship between the reference photo of the candidate and the candidate's position information, and construct a second mapping relationship between the acquisition parameters of the camera and the position information;

[0036] A candidate photo acquisition module, configured to acquire candidate photos in the target examination room, query the second mapping relationship according to the current acquisition parameters for the current acquisition, and obtain the acquisition position information mapped by the current acquisition parameters;

[0037] A reference photo mapping module, configured to query the first mapping relationship and obtain the candidate reference photo corresponding to the candidate position information mapped by the acquisition position information;

[0038] A photo verification module for supervising the target examination room based on the candidate's photo and the candidate's reference photo.

[0039] According to a third aspect of the present invention, there is provided a storage medium having stored thereon a computer program, which when executed by a processor, implements the steps of the examination anti-cheating supervision method in any possible implementation manner of the first aspect.

[0040] According to a fourth aspect of the present invention, there is provided an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein when the processor executes the program, it implements the steps of the examination anti-cheating supervision method in any possible implementation manner of the first aspect. Description of the Drawings

[0041] The drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present invention and used together with the specification to explain the principles of the present invention.

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or related technologies. Obviously, for those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0043] Figure 1 It is a schematic flowchart of an examination anti-cheating supervision method provided by an embodiment of the present invention;

[0044] Figure 2 It is a schematic diagram of an examination anti-cheating supervision device provided by an embodiment of the present invention;

[0045] Figure 3 It is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. Detailed Embodiments

[0046] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0047] See Figure 1 , an embodiment of the present invention provides an examination anti-cheating supervision method, which can be applied to the supervision of online examinations, and the method may include the following steps:

[0048] S101. Pre-acquire the reference photos of each candidate assigned seats in the target examination room, construct a first mapping relationship between the reference photo of the candidate and the candidate's position information, and construct a second mapping relationship between the acquisition parameters of the camera and the position information;

[0049] In this embodiment, as an alternative embodiment, pre-acquiring the reference photos of each candidate assigned seats in the target examination room includes:

[0050] Verify the identity card information of the candidate to confirm that the candidate is a candidate in the target examination room;

[0051] Collect the face of the candidate to obtain the reference photo of the candidate.

[0052] In this embodiment, as an alternative embodiment, constructing the second mapping relationship between the acquisition parameters of the camera and the position information includes:

[0053] Obtain the positioning information of each camera deployed in the target examination room;

[0054] For each camera, set the shooting area of the camera;

[0055] Take a photo of the target candidate position in the shooting area to obtain the camera parameters of this shooting;

[0056] Construct the second mapping relationship between the positioning information, the camera parameters and the target candidate position;

[0057] For each target candidate position in the captured shooting area, set the variation range of the camera parameters of the camera.

[0058] In this embodiment, it is also possible to use the camera of a mobile phone or a personal computer for taking pictures. As an alternative embodiment, within the shooting area of the camera, there is only one target candidate position. The variation range of the camera parameters can be a pre-set range. As another alternative real-time example, it is also possible to set a camera parameter corresponding to each target candidate position, and the camera parameters of each position form a set of camera parameters as the variation range of the camera parameters. In subsequent photo acquisition, the camera parameter is randomly selected from the set of camera parameters.

[0059] In this embodiment, as an alternative embodiment, perform live body recognition and face detection on the reference photo of the candidate: Ensure that the candidate being collected currently is a real live body rather than a static photo or video through live body recognition technology; Identify the face in the image through face detection technology. When there is exactly one face in the photo, it is saved as the reference photo of the current candidate as a valid photo. By combining live body recognition and face detection, the security and accuracy are improved.

[0060] In this embodiment, as another alternative embodiment, if the photo does not meet the requirements, the step of collecting the face of the candidate is repeated until a reference photo of the candidate is obtained.

[0061] In this embodiment, as an alternative embodiment, when collecting the reference photo of the candidate, a photo P01 is collected under the condition that the candidate meets the requirements of live body recognition. To prevent the photo collected from not meeting the requirements due to the candidate suddenly turning the head, moving the position, etc. during the photo collection, face detection is performed on the photo P01; when the face detection result meets the requirements, the photo P01 is saved as the reference photo P0 of the current candidate; if the face detection result does not meet the requirements, the above steps are repeated until the reference photo P0 is obtained.

[0062] S102. Collect the photos of the candidates in the target examination room, query the second mapping relationship according to the current collection parameters for the current collection, and obtain the collection position information mapped by the current collection parameters.

[0063] In this embodiment, as an alternative embodiment, the collecting the photos of the candidates in the target examination room includes:

[0064] According to the pre-set examination configuration information, the camera parameters of the target camera are changed within the change range of the target camera, and the candidate photos are collected according to the changed camera parameters.

[0065] In this embodiment, as an alternative embodiment, the examination configuration information includes: the start time of the examination, the end time of the examination, and the number of times of collection of the target camera.

[0066] The changing the camera parameters of the target camera within the change range of the target camera and collecting the candidate photos according to the changed camera parameters includes:

[0067] During the examination time between the start time of the examination and the end time of the examination, random collection time points are set according to the number of collections, and the interval between each collection time point is greater than the pre-set time threshold.

[0068] The camera monitoring parameters are randomly determined within the change range of the target camera, and the collection parameters of the target camera are adjusted to the camera monitoring parameters.

[0069] At the collection time point, photos are collected according to the camera monitoring parameters.

[0070] In this embodiment, as an alternative embodiment, a random algorithm can be used to obtain random collection time points. As an alternative embodiment, the pre-set time threshold can be 10 seconds.

[0071] In this embodiment, as an alternative embodiment, the target camera collects the photos of the examinees in the target examination room according to the examination configuration information and the changed camera parameters, and queries the second mapping relationship according to the current acquisition parameters to obtain the mapped acquisition location information.

[0072] In this embodiment, as an alternative embodiment, it is assumed that the examination configuration information is preset as follows: the examination time is 1 hour, and the number of acquisitions of the target camera is 5 times. In this embodiment, the examinees enter the examination at time t0, and the examination time is 1 hour, that is, 3600 seconds. Five random numbers between 0 and 3600 are obtained by using a random algorithm as the random acquisition time points to determine the camera monitoring parameters. There is at least a 10-second interval between each number to ensure that the camera is reserved for photo-taking processing time. At each acquisition time point, photos are collected according to the camera monitoring parameters to obtain the photos P1 of the examinees during the examination.

[0073] S103. Query the first mapping relationship to obtain the reference photos of the examinees corresponding to the examinee location information mapped by the acquisition location information;

[0074] In this embodiment, as an alternative embodiment, by querying the first mapping relationship, the reference photos of the examinees corresponding to the examinee location information mapped by the acquisition location information are obtained, and the examinee photos are associated with the reference photos of the examinees through the acquisition location for subsequent comparison with the examinee photos to verify the identities of the examinees.

[0075] S104. Supervise the target examination room based on the examinee photos and the reference photos of the examinees.

[0076] In this embodiment, as an alternative embodiment, the supervision of the target examination room based on the examinee photos and the reference photos of the examinees includes:

[0077] Verifying the number and identity of the examinees in the examinee photos based on the reference photos of the examinees, including:

[0078] Obtain the number of faces in the examinee photo. When the number of faces is greater than or less than 1, it is determined that the examinee has cheated;

[0079] When the number of faces is equal to 1, the faces of the examinee photo and the reference photo of the examinee are compared to obtain the similarity. When the similarity is less than the preset similarity threshold, it is determined that the examinee has cheated.

[0080] In this embodiment, as another alternative embodiment, when the similarity is greater than or equal to the preset similarity threshold, an anti-cheating record is recorded.

[0081] In this embodiment, as an alternative embodiment, the number of faces in the candidate photo can be verified through an AI face detection model, and the faces in the reference photo and the candidate photo can be compared through an AI face comparison model to obtain the similarity.

[0082] In this embodiment, as an alternative embodiment, the real-time photo P1 is input into the AI face detection model to obtain the number of faces F1 in the face detection result. When F1 < 1 or F1 > 1, it is determined that the current candidate has cheated; when F1 = 1, the face comparison continues.

[0083] The reference photo P0 and the real-time photo P1 are input into the AI face comparison model to obtain the similarity C1 in the face comparison result. C1 is compared with a pre-set threshold C0: when C1 < C0, it is determined that the current candidate is not the account user himself / herself and has cheated; when C1 >= C0, it is determined that the current candidate is the account user himself / herself, and an anti-cheating record is recorded.

[0084] In this embodiment, as an alternative embodiment, liveness detection is performed on the candidate photo. If the liveness detection result is not liveness, it is determined that the candidate has cheated.

[0085] In this embodiment, as an alternative embodiment, the exam configuration further includes: when it is determined that there is cheating behavior, a pre-set cheating intervention strategy is executed. The cheating intervention strategy includes but is not limited to: automatically and forcibly collecting the papers to end the exam, or marking the cheating suspicion for manual review, etc. This embodiment does not make a limitation on this.

[0086] In this embodiment, by pre-acquiring the reference photos of each candidate assigned seats in the target examination room, a first mapping relationship between the reference photo of the candidate and the candidate's position information in the examination room is constructed, and a second mapping relationship between the acquisition parameters of the camera and the position information is constructed; the candidate photos in the target examination room are collected, and according to the current acquisition parameters for the current collection, the second mapping relationship is queried to obtain the acquisition position information mapped by the current acquisition parameters; the first mapping relationship is queried to obtain the candidate reference photo corresponding to the candidate position information mapped by the acquisition position information; based on the candidate photo and the candidate reference photo, the target examination room is supervised. In this way, by using liveness detection technology and face detection technology, the identity of the person being identified and whether it is a real live body are judged, improving the accuracy of identification. By collecting candidate photos at random time points during the exam time, the number of faces in the candidate photos is verified and the similarity with the reference photos is compared to prevent cheating behaviors such as others taking the exam on behalf of candidates or multiple people answering questions simultaneously during the exam, realizing the supervision of candidates during the exam, and having better exam supervision intensity and fairness.

[0087] Based on the same inventive concept, as Figure 2As shown in the figure, an embodiment of the present invention further provides a supervision device for preventing cheating in examinations. The device includes:

[0088] A reference photo acquisition module 201, configured to pre-acquire reference photos of each candidate assigned seats in a target examination room, construct a first mapping relationship between the reference photo of the candidate and the candidate's position information, and construct a second mapping relationship between the acquisition parameters of the camera and the position information;

[0089] In this embodiment, as an optional embodiment, verify the identity card information of the candidate, collect the face of the target candidate to obtain the reference photo of the candidate; obtain the positioning information of each camera arranged in the target examination room, for each camera, set the shooting area of the camera, shoot the target candidate position in the shooting area, obtain the camera parameters of this shooting, construct the second mapping relationship between the positioning information, the camera parameters and the target candidate position, and set the change range of the camera parameters of the camera for each target candidate position in the photographed shooting area.

[0090] In this embodiment, as an optional embodiment, perform live body recognition and face detection on the reference photo of the candidate to ensure that the candidate being collected currently is a real live body, and when there is only one face in the photo, it is saved as the reference photo of the current candidate as a valid photo. As another optional embodiment, if the photo does not meet the requirements, repeat the step of collecting the face of the candidate until the reference photo of the candidate is obtained.

[0091] A candidate photo acquisition module 202, configured to collect candidate photos in the target examination room, query the second mapping relationship according to the current acquisition parameters during the current acquisition, and obtain the acquisition position information mapped by the current acquisition parameters;

[0092] In this embodiment, as an optional embodiment, according to the pre-set examination configuration information, make the camera parameters of the target camera change within the change range of the target camera, and collect candidate photos according to the changed camera parameters.

[0093] In this embodiment, as an optional embodiment, the examination configuration information includes: the start time of the examination, the end time of the examination, and the number of acquisitions of the target camera. During the examination time, set random acquisition time points according to the number of acquisitions, and the interval between each acquisition time point is greater than the pre-set time threshold to ensure that the camera is reserved for photo-taking processing time.

[0094] In this embodiment, as an optional embodiment, the target camera collects candidate photos in the target examination room according to the examination configuration information and the changed camera parameters, queries the second mapping relationship according to the acquisition parameters during the current acquisition, and obtains the mapped acquisition position information.

[0095] A reference photo mapping module 203 is configured to query the first mapping relationship and obtain the candidate reference photo corresponding to the candidate location information mapped by the collection location information.

[0096] In this embodiment, as an alternative embodiment, by querying the first mapping relationship, the candidate reference photo corresponding to the candidate location information mapped by the collection location information is obtained, and the candidate photo is associated with the candidate reference photo through the collection location for subsequent comparison with the candidate photo to verify the candidate's identity.

[0097] A photo verification module 204 is configured to monitor the target examination room based on the candidate photo and the candidate reference photo.

[0098] In this embodiment, as an alternative embodiment, verifying the number and identity of the candidates in the candidate photo based on the candidate reference photo includes:

[0099] Obtain the number of human faces in the candidate photo. When the number of human faces in the photo is greater than or less than 1, it is determined that the candidate has cheated. When the number of human faces in the photo is equal to 1, the human faces in the candidate photo and the candidate reference photo are compared to obtain a similarity. When the similarity is less than a preset similarity threshold, it is determined that the candidate has cheated. When the similarity is greater than or equal to the preset similarity threshold, an anti-cheating record is recorded.

[0100] In this embodiment, as an alternative embodiment, the number of human faces in the candidate photo can be verified through an AI face detection model, and the human faces in the reference photo and the candidate photo are compared through an AI face comparison model to obtain a similarity.

[0101] Based on the same inventive concept, an embodiment of the present invention further provides a storage medium, on which a computer program is stored. When the program is executed by a processor, the steps of the examination anti-cheating supervision method in any possible implementation manner described above are implemented.

[0102] Optionally, the storage medium may be a non-transitory computer-readable storage medium. For example, the non-transitory computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0103] Based on the same inventive concept, see Figure 3, an embodiment of the present invention further provides an electronic device, including a memory 101 (such as a non-volatile memory), a processor 102, and a computer program stored on the memory 101 and executable on the processor 102. When the processor 102 executes the program, it implements the steps of the supervision method for exam anti-cheating in any of the above possible implementation manners, which is equivalent to the supervision device for exam anti-cheating as described above. Of course, this processor can also be used to process other data or perform operations. The electronic device can be a device such as a PC, a server, or a terminal.

[0104] As Figure 3 shown, the electronic device generally may further include: a memory 103, a network interface 104, and an internal bus 105. In addition to these components, other hardware may also be included, which will not be elaborated here.

[0105] It should be noted that the above-mentioned supervision device for exam anti-cheating can be implemented by software. As a logically meaningful device, it is formed by the processor 102 of the electronic device where it is located reading the computer program instructions stored in the non-volatile memory into the memory 103 for running.

[0106] Embodiments of the subject matter and functional operations described in this specification can be implemented in the following: digital electronic circuits, tangible computer software or firmware, computer hardware including the structures disclosed in this specification and their structural equivalents, or a combination of one or more of them. Embodiments of the subject matter described in this specification can be implemented as one or more computer programs, that is, one or more modules in computer program instructions encoded on a tangible non-transitory program carrier to be executed by a data processing device or to control the operation of a data processing device. Alternatively or additionally, the program instructions can be encoded on an artificially generated propagated signal, such as a machine-generated electrical, optical, or electromagnetic signal, which is generated to encode and transmit information to a suitable receiver device for execution by a data processing device. A computer storage medium can be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of one or more of them.

[0107] The processes and logical flows described in this specification can be executed by one or more programmable computers executing one or more computer programs to perform corresponding functions by operating on input data and generating outputs. The processes and logical flows can also be executed by dedicated logic circuits - such as FPGAs (Field Programmable Gate Arrays) or ASICs (Application Specific Integrated Circuits), and the device can also be implemented as dedicated logic circuits.

[0108] Computers suitable for executing computer programs include, for example, general and / or special-purpose microprocessors, or any other type of central processing unit. Generally, the central processing unit will receive instructions and data from read-only memory and / or random access memory. The basic components of a computer include a central processing unit for implementing or executing instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include one or more mass storage devices for storing data, such as magnetic disks, magneto-optical disks, or optical disks, etc., or the computer will be operably coupled to such mass storage devices to receive data therefrom or transfer data thereto, or both. However, a computer is not necessarily required to have such devices. In addition, a computer may be embedded in another device, such as a mobile phone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable storage device such as a universal serial bus (USB) flash drive, to name just a few.

[0109] Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media, and memory devices, such as including semiconductor memory devices (e.g., EPROM, EEPROM, and flash memory devices), magnetic disks (e.g., internal hard disks or removable disks), magneto-optical disks, and CD-ROM and DVD-ROM disks. The processor and the memory may be supplemented by, or incorporated in, special logic circuitry.

[0110] Although this specification contains many specific implementation details, these should not be construed as limiting the scope of any invention or the scope of what is claimed, but rather as mainly describing the features of specific embodiments of a particular invention. Certain features that are described in multiple embodiments in this specification may also be implemented in combination in a single embodiment. On the other hand, the various features described in a single embodiment may also be implemented separately in multiple embodiments or in any suitable sub-combination. In addition, although features may operate in certain combinations as described above and even be initially claimed as such, one or more features from the claimed combination may in some cases be removed from that combination, and the claimed combination may be directed to a sub-combination or a variation of a sub-combination.

[0111] Similarly, although operations are depicted in the drawings in a particular order, this should not be understood as requiring that the operations be performed in the particular order shown or sequentially, or that all illustrated operations be performed, to achieve the desired result. In some cases, multitasking and parallel processing may be advantageous.

[0112] Thus, specific embodiments of the subject matter have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the particular order shown or sequential order to achieve the desired results.

[0113] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0114] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for preventing cheating in an examination, characterized in that: Applicable to multiple candidates in the same test center, including: Pre-acquire reference photos of each examinee assigned a seat in the target examination room, construct a first mapping relationship between the examinee's reference photo and the examinee's position information, and construct a second mapping relationship between the camera's acquisition parameters and the position information; Collecting a photo of the examinee in the target examination room, querying the second mapping relationship according to the current acquisition parameters currently being collected, and obtaining acquisition position information mapped by the current acquisition parameters, wherein a plurality of cameras are arranged in the target examination room, and the shooting area of ​​each camera only includes one target examinee position; Query the first mapping relationship to obtain a candidate reference photo corresponding to the candidate location information mapped by the collection location information; Based on the examinee's photo and the examinee's reference photo, supervising the target examination room; The collecting of the photos of the examinees in the target examination room includes: According to the preset test configuration information, the camera parameters of the target camera are changed within the change range of the target camera, and the test taker's photo is collected according to the changed camera parameters; The test configuration information includes: the test start time, the test end time and the number of acquisition times of the target camera; The step of changing the camera parameters of the target camera within the change range of the target camera according to the preset test configuration information and collecting the examinee's photo according to the changed camera parameters includes: During the examination time between the start time and the end time of the examination, a random collection time point is set according to the number of collection times, and the interval between each of the collection time points is greater than a preset time threshold; When the target camera changes within a range of change, randomly determine camera monitoring parameters, and adjust acquisition parameters of the target camera to the camera monitoring parameters; At the acquisition time point, photos are acquired according to the camera monitoring parameters.

2. The method according to claim 1, characterized in that The step of obtaining reference photos of each examinee with assigned seats in the target examination room in advance includes: Verify the candidate's ID card information and confirm that the candidate is a candidate in the target examination room; The face of the examinee is collected to obtain a reference photo of the examinee.

3. The method according to claim 2, characterized in that The constructing a second mapping relationship between the camera's acquisition parameters and the position information includes: Obtaining positioning information of each camera deployed in the target examination room; For each camera, set the shooting area of ​​the camera; Shoot the target examinee's position within the shooting area and obtain the camera parameters of the shooting; Constructing a second mapping relationship between the positioning information, the camera parameters and the target examinee's position; The variation range of the camera parameters of the camera is set according to the position of each target examinee within the shooting area.

4. The method according to claim 1, characterized in that The monitoring of the target examination room based on the examinee's photo and the examinee's reference photo includes: Obtaining the number of faces in the candidate's photo, and when the number of faces is greater than or less than 1, determining that the candidate has cheated; When the number of faces is equal to 1, a face comparison is performed on the candidate's photo and the candidate's reference photo to obtain a similarity. When the similarity is less than a preset similarity threshold, it is determined that the candidate has cheated.

5. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: Perform liveness recognition on the candidate's photo, and if the liveness recognition result is not liveness, it is determined that the candidate has cheated.

6. A monitoring device for preventing cheating in an examination, characterized in that: Applied to multiple examinees in the same target examination room, the examination anti-cheating supervision device includes: A reference photo acquisition module is used to pre-acquire reference photos of each candidate assigned a seat in the target examination room, construct a first mapping relationship between the candidate's reference photo and the candidate's position information, and construct a second mapping relationship between the camera's acquisition parameters and the position information, wherein a plurality of cameras are arranged in the target examination room, and the shooting area of ​​each camera only includes one target candidate position; The candidate photo collection module is used to collect the candidate photos in the target examination room, query the second mapping relationship according to the current collection parameters currently being collected, and obtain the collection position information mapped by the current collection parameters; The collecting of the photos of the examinees in the target examination room includes: According to the preset test configuration information, the camera parameters of the target camera are changed within the change range of the target camera, and the test taker's photo is collected according to the changed camera parameters; The test configuration information includes: the test start time, the test end time and the number of acquisition times of the target camera; The step of changing the camera parameters of the target camera within the change range of the target camera according to the preset test configuration information and collecting the examinee's photo according to the changed camera parameters includes: During the examination time between the start time and the end time of the examination, a random collection time point is set according to the number of collection times, and the interval between each of the collection time points is greater than a preset time threshold; When the target camera changes within a range of change, randomly determine camera monitoring parameters, and adjust acquisition parameters of the target camera to the camera monitoring parameters; At the collection time point, collecting photos according to the camera monitoring parameters; A reference photo mapping module, used to query the first mapping relationship and obtain a candidate reference photo corresponding to the candidate location information mapped by the collection location information; The photo verification module is used to supervise the target examination room based on the candidate's photo and the candidate's reference photo.

7. A storage medium, characterized in that: The storage medium stores programs or instructions, and when the programs or instructions are executed by the processor, the steps of the method for supervising and controlling examination cheating prevention as described in any one of claims 1 to 5 are implemented.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method for supervising examination cheating prevention as claimed in any one of claims 1 to 5 are implemented.

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