Video interview method, apparatus, computer device and storage medium

Abstract

This application relates to a video interview method, apparatus, computer device, storage medium, and computer program product. The method includes: when the user requesting the interview terminal is determined to be a job applicant for an interview appointment based on facial recognition results, sending a video interview invitation to the interviewer terminal; after the interviewer terminal accepts the video interview invitation, starting the video interview and forwarding the video interview screen; when video interview screen stuttering is detected, performing detection based on the configurations of the requesting and interviewer terminals to determine the abnormal terminal and the cause of the video stuttering; sending a corresponding debugging solution to the abnormal terminal, which guides the interview participants in troubleshooting the abnormal terminal. This method allows for greater flexibility in the time and location of interviews while effectively avoiding the risk of someone else conducting the interview on your behalf, solving the problem of poor video communication that easily occurs during interviews, and providing users with a better user experience during interviews.

Description

Technical Field

[0001] This application relates to the field of remote communication technology, and in particular to a video interview method, apparatus, computer equipment, storage medium, and computer program product. Background Technology

[0002] Interviews are an important method for companies to select employees. Interviews provide an opportunity for two-way communication between the company and the applicant, allowing both parties to understand each other better and make more accurate decisions regarding hiring or accepting the position.

[0003] Traditional interview methods are mostly conducted in person. After receiving an interview notice, applicants go to the interview location to participate in the interview. This process requires applicants to spend time traveling back and forth, and also requires interviewers to spend time interviewing a large number of applicants, which is a significant drain on human and material resources. Summary of the Invention

[0004] Therefore, it is necessary to provide a video interview method, apparatus, computer equipment, computer-readable storage medium, and computer program product to address the aforementioned technical problems.

[0005] Firstly, this application provides a video interview method. The method includes:

[0006] When the user requesting the interview terminal is identified as the applicant for the interview appointment based on the facial recognition results, a video interview invitation is sent to the interviewer's terminal.

[0007] After accepting the video interview invitation on the interviewer's terminal, the video interview is started and the video interview screen is forwarded.

[0008] When a stutter is detected in the video interview, the configuration of the requesting interview terminal and the interviewer's terminal is checked. If the stutter is determined to be caused by a terminal configuration issue, the terminal with the abnormal configuration is identified as the abnormal terminal.

[0009] A corresponding debugging plan is sent to the abnormal terminal. The corresponding debugging plan includes a debugging plan for the configuration parameters of the abnormal terminal. The debugging plan guides the interview participants to debug the abnormal terminal.

[0010] In one embodiment,

[0011] When it is determined that the video stuttering is not due to terminal configuration issues, the network parameters of the requesting interview terminal and the interviewer terminal are obtained; when it is determined that the video stuttering is due to a network anomaly based on the network parameters of the requesting interview terminal and the interviewer terminal, the terminal with the network anomaly is identified as the abnormal terminal.

[0012] The corresponding debugging solutions include: the debugging solution for network switching of the abnormal terminal.

[0013] In one embodiment, when a stuttering is detected in the video interview, if it is determined that the video stuttering occurs again after the abnormal terminal has executed the configuration parameter adjustment scheme of the abnormal terminal, then a network switching debugging scheme for the abnormal terminal is sent to the abnormal terminal.

[0014] In one embodiment, the method further includes:

[0015] If the abnormal terminal still experiences video stuttering after executing the network switching debugging scheme, the cause of the video stuttering is determined to be poor network quality, and the terminal with poor network quality is identified as the abnormal terminal.

[0016] The corresponding debugging solutions include: the debugging solution for the abnormal terminal interview method.

[0017] In one embodiment, the method further includes:

[0018] When the video feed stutters, a notification indicating that the abnormal terminal is in an abnormal state is sent to a normal terminal whose detection result is normal.

[0019] When the abnormal terminal executes the corresponding debugging plan according to the cause of the video stuttering, a prompt is sent to the normal terminal indicating that the abnormal terminal is being debugged;

[0020] After the abnormal terminal completes the corresponding debugging scheme, a notification indicating that the debugging of the abnormal terminal has ended is sent to the normal terminal.

[0021] In one embodiment, when the user requesting the interview terminal is determined to be the applicant for the interview appointment based on the facial recognition result, a video interview invitation is sent to the interviewer terminal, including:

[0022] When an interview request is received from the interview request terminal, the camera of the interview request terminal is invoked to capture the image of the first applicant;

[0023] The image of the first applicant is compared with the image of the second applicant who has made an interview appointment to determine whether the current applicant is the one who made the interview appointment.

[0024] When the facial recognition results confirm that the current applicant is the applicant for the interview appointment, a video interview invitation is sent to the interviewer's terminal.

[0025] Secondly, this application also provides a video interview device. The device includes:

[0026] The interview invitation module is used to send a video interview invitation to the interviewer's terminal when the user requesting the interview terminal is determined to be the applicant who made the interview appointment based on the facial recognition results.

[0027] The interview initiation module is used to initiate a video interview and forward the video interview screen after the interviewer's terminal accepts the video interview invitation.

[0028] The interview detection module is used to detect when the video interview screen is detected to be lagging, based on the configuration of the requesting interview terminal and the interviewer terminal. When it is determined that the cause of the video lag is a terminal configuration issue, the terminal with the abnormal configuration is identified as the abnormal terminal.

[0029] The debugging guidance module is used to send a corresponding debugging plan to the abnormal terminal. The corresponding debugging plan includes a debugging plan for the configuration parameters of the abnormal terminal. The debugging plan guides the interview participants to debug the abnormal terminal.

[0030] In one embodiment, the interview detection module is further configured to: when it is determined that the video stuttering is not due to a terminal configuration issue, obtain the network parameters of the requesting interview terminal and the interviewer terminal; and when it is determined that the video stuttering is due to a network anomaly based on the network parameters of the requesting interview terminal and the interviewer terminal, identify the terminal with the network anomaly as the abnormal terminal.

[0031] The corresponding debugging solutions include: the debugging solution for network switching of the abnormal terminal.

[0032] In one embodiment, the interview detection module is further configured to: when a stuttering is detected in the video interview, if it is determined that the video stuttering occurs again after the abnormal terminal has executed the adjustment scheme of the abnormal terminal's configuration parameters, then send a network switching debugging scheme for the abnormal terminal to the abnormal terminal.

[0033] In one embodiment, the interview detection module is further configured to: when the abnormal terminal still experiences video stuttering after executing the debugging scheme for abnormal terminal network switching, determine that the cause of the video stuttering is poor network quality, and identify the terminal with poor network quality as the abnormal terminal; the corresponding debugging scheme includes: the debugging scheme for the abnormal terminal interview method.

[0034] In one embodiment, the device further includes: a status indication module;

[0035] The status prompt module is used to send a prompt indicating that the abnormal terminal is in an abnormal state to a normal terminal with a normal detection result when the video frame stutters; to send a prompt indicating that the abnormal terminal is being debugged to a normal terminal when the abnormal terminal executes the corresponding debugging plan according to the cause of the video stuttering; and to send a prompt indicating that the abnormal terminal has finished debugging to a normal terminal after the abnormal terminal has completed the corresponding debugging plan.

[0036] In one embodiment, when the interview invitation module determines, based on the facial recognition result, that the user requesting the interview terminal is the applicant who has made an interview appointment, and sends a video interview invitation to the interviewer terminal, it includes:

[0037] When an interview request is received from the interview requesting terminal, the camera of the interview requesting terminal is invoked to capture the image of the first applicant; the image of the first applicant is compared with the image of the second applicant who has made an interview appointment to perform facial recognition to determine whether the current applicant is the applicant who made the interview appointment; when the facial recognition result determines that the current applicant is the applicant who made the interview appointment, a video interview invitation is sent to the interviewer terminal.

[0038] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the above-described method.

[0039] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of the above-described method.

[0040] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the steps of the above-described method.

[0041] The aforementioned video interview methods, devices, computer equipment, storage media, and computer program products, when conducting remote video interviews, first perform facial recognition on the user requesting the interview terminal to confirm that the user is the client who made the interview appointment. Then, a video interview invitation is sent to the interview terminal, initiating the video interview and forwarding the video interview screen. By performing facial recognition on the user requesting the interview terminal beforehand, the risk of someone else conducting the interview on their behalf is effectively avoided. Secondly, during the interview, the video screen is monitored. When video interruptions occur, the terminal configurations of both interviewers are checked to determine the abnormal terminal and the cause of the video interruption. The corresponding troubleshooting plan is then used to guide the abnormal terminal in troubleshooting. This ensures that the interview process proceeds smoothly, making the time and location of the interview more flexible and resolving the common problem of video communication difficulties during interviews, thus providing users with a better user experience. Attached Figure Description

[0042] Figure 1 This is a diagram illustrating the application environment of a video interview method in one embodiment;

[0043] Figure 2 This is a flowchart illustrating a video interview method in one embodiment;

[0044] Figure 3 This is a flowchart illustrating the detection steps based on the configurations of the requesting interview terminal and the interviewer terminal when a stuttering is detected in a video interview, as shown in one embodiment.

[0045] Figure 4 This is a flowchart illustrating the process of sending a corresponding debugging plan to an abnormal terminal in one embodiment, and the debugging plan guiding the interview participants to perform debugging steps on the abnormal terminal.

[0046] Figure 5 This is a flowchart illustrating a video interview method in another embodiment;

[0047] Figure 6 This is a structural block diagram of a video interview device in one embodiment;

[0048] Figure 7 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0049] To make the objectives, technical solutions, 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.

[0050] The video interview method provided in this application embodiment can be applied to, for example, Figure 1In the application environment shown, the requesting interview terminal 102 communicates with the remote interview backend 104 via a network. The remote interview backend 104 also communicates with the interviewer terminal 106 via a network. When the remote interview backend 104 determines, based on facial recognition results, that the user of the requesting interview terminal 102 is the applicant who has scheduled an interview, it sends a video interview invitation to the interviewer terminal 106. After the video interview invitation is received, the remote interview backend 104 starts the video interview and forwards the video interview screen. Simultaneously, the remote interview backend 104 monitors the video interview screen during the process. When it detects stuttering, it checks the configurations of both the requesting interview terminal 102 and the interviewer terminal 104 to determine the abnormal terminal and the cause of the stuttering. Based on the cause of the stuttering, it sends a corresponding debugging solution to the abnormal terminal, guiding the interview participants to debug the abnormal terminal so that the interview process can continue. The requesting interview terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, and tablets. The remote interview backend 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0051] In one embodiment, such as Figure 2 As shown, a video interview method is provided, which can be applied to... Figure 1 Taking the remote interview backend 104 in the example, the following steps are included:

[0052] Step 202: When the user requesting the interview terminal is determined to be the applicant who made the interview appointment based on the facial recognition result, a video interview invitation is sent to the interviewer terminal.

[0053] Facial recognition is a biometric technology, also known as portrait recognition or face recognition. It is a biometric technology that identifies individuals based on their facial features. It mainly uses cameras or webcams to capture images or video streams containing faces, automatically detects and tracks faces in the images, and then performs facial recognition on the detected faces.

[0054] In this context, the requesting interview terminal is the terminal device used by the applicant during the interview process. The interviewer terminal is the terminal device used by the interviewer during the interview process. It is understood that in this embodiment, both the requesting interview terminal and the interviewer terminal can be personal computers, laptops, smartphones, tablets, etc., and this invention does not impose any limitations.

[0055] Interview appointment refers to the process by which job seekers submit their resumes or personal information online or offline in advance to schedule a job interview with an interviewer.

[0056] Specifically, when the remote interview backend determines, based on facial recognition results, that the user requesting the interview terminal is the applicant who has scheduled an interview, it sends a video interview invitation from the requesting terminal to the interviewer's terminal. The interviewee then negotiates the interview platform and time with HR, and the HR establishes the job interview appointment with the interviewer.

[0057] Step 204: After accepting the video interview invitation on the interviewer's terminal, start the video interview and forward the video interview screen.

[0058] The video interview footage is a continuous video stream transmitted through the remote interview backend after the requesting interview terminal and the interviewer terminal establish an interview channel. This video stream is captured by the cameras carried by the requesting interview terminal and the interviewer terminal respectively.

[0059] Specifically, after the remote interview backend receives the video interview invitation on the interviewer's terminal, it starts the video interview, establishes an interview channel between the requesting interview terminal and the interviewer's terminal, and forwards the video streams captured by the cameras on the requesting interview terminal and the interviewer's terminal to the other interview terminal.

[0060] Step 206: When a stuttering is detected in the video interview, the configuration of the requesting interview terminal and the interviewer's terminal is checked. If the stuttering is determined to be due to a terminal configuration issue, the terminal with the abnormal configuration is identified as an abnormal terminal.

[0061] Whether the video interview footage is choppy is determined by the remote interview backend by monitoring the video data stream of the video interview footage.

[0062] Among them, the abnormal terminal is the terminal that the remote interview backend identifies as causing video stuttering after detecting the configuration of the terminal requesting the interview and the interviewer's terminal.

[0063] In one embodiment, the terminal is configured with parameters for the browser that requests a remote video interview between the interview terminal and the interviewer's terminal. The corresponding debugging scheme includes a debugging scheme for the browser configuration parameters used by the abnormal terminal for the remote video interview.

[0064] In one embodiment, the terminal is configured to request the configuration of terminal system parameters for both the interview terminal and the interviewer's terminal. The corresponding debugging scheme includes: a debugging scheme for the abnormal terminal's own terminal system configuration parameters.

[0065] Specifically, during a remote video interview, the remote interview backend monitors the video data stream to detect any stuttering or buffering. When stuttering is detected, the backend retrieves the configuration parameters of both the requesting and interviewer terminals. If the stuttering is determined to be due to terminal configuration issues, the terminal with the abnormal configuration is identified as an abnormal terminal.

[0066] Step 208: Send the corresponding debugging plan to the abnormal terminal. The corresponding debugging plan includes: a debugging plan for the configuration parameters of the abnormal terminal. The debugging plan guides the interview participants to debug the abnormal terminal.

[0067] The debugging plan is a corresponding debugging solution generated based on the cause of video stuttering, in order to solve the stuttering problem.

[0068] Specifically, the remote interview backend generates a corresponding debugging plan based on the cause of the video buffering. This plan is a debugging scheme for the configuration parameters of the abnormal terminal. The debugging plan is then sent to the abnormal terminal, guiding the interview participants to debug the abnormal terminal so that the interview can continue.

[0069] The aforementioned video interview method, when a remote video interview is required, first performs facial recognition on the user requesting the interview terminal to confirm that the user is the client who made the interview appointment. Then, a video interview invitation is sent to the terminal requesting the interview, initiating the video interview and forwarding the video interview screen. By performing facial recognition on the user requesting the interview terminal beforehand, the risk of someone else conducting the interview on their behalf is effectively avoided. Secondly, during the interview, the video screen is monitored. When the video interview becomes choppy, the terminal configurations of both parties are checked to determine the abnormal terminal and the cause of the video lag. Corresponding troubleshooting solutions are then provided to guide the abnormal terminal in troubleshooting, ensuring the interview proceeds smoothly. The interview time and location are more flexible, resolving the common problem of video communication breakdowns during interviews and providing users with a better user experience.

[0070] In one embodiment, such as Figure 3 As shown, when video interview stuttering is detected, the detection process, based on the configurations of the requesting interview terminal and the interviewer's terminal, also includes the following steps:

[0071] When the cause of video stuttering is determined to be non-terminal configuration-related, or when video stuttering still occurs after adjusting the configuration parameters of the abnormal terminal, obtain the network parameters of the requesting interview terminal and the interviewer's terminal.

[0072] Among these, non-terminal configuration reasons refer to any cause other than abnormal terminal configuration that leads to stuttering in the video interview. Preferably, in this embodiment, the non-terminal configuration reason is a network abnormality.

[0073] Specifically, if the remote interview backend determines that the video stuttering is unrelated to the terminal configuration after checking the configurations of the requesting interview terminal and the interviewer's terminal, or if the video stuttering persists even after the remote interview backend guides the interviewees to adjust the configuration parameters of the abnormal terminal according to the corresponding configuration parameter adjustment plan, then the cause of the video stuttering is determined to be non-terminal configuration-related. The remote interview backend will obtain the network parameters of the requesting interview terminal and the interviewer's terminal. If the video stuttering does not reappear after implementing the configuration parameter adjustment plan for the abnormal terminal, then the cause of the video stuttering is indeed a terminal configuration issue.

[0074] If the video stuttering is determined to be caused by a network anomaly based on the network parameters of the requesting interview terminal and the interviewer's terminal, then the terminal with the network anomaly is identified as the abnormal terminal. The corresponding debugging solutions include: a debugging solution for network switching of the abnormal terminal.

[0075] Specifically, when the remote interview backend determines that the video stuttering is caused by a network anomaly based on the obtained network parameters, the terminal experiencing the network anomaly is identified as an abnormal terminal; a corresponding debugging plan is generated based on the network parameters of the abnormal terminal, which is a debugging plan to switch the network of the abnormal terminal.

[0076] In one embodiment, the troubleshooting solution for abnormal terminal network switching is to guide the interview participants to switch the abnormal terminal's network configuration from a mobile network to a wireless network, or to convert it to a mobile network that is one level higher than the current mobile network.

[0077] In one embodiment, the debugging scheme for abnormal terminal network switching is to guide the interview participants to change the network configuration of the abnormal terminal from wireless network to mobile network.

[0078] If video stuttering still occurs after the abnormal terminal has implemented the abnormal terminal network switching debugging plan, the cause of the video stuttering is determined to be poor network quality, and the terminal with poor network quality is identified as an abnormal terminal; the corresponding debugging plan includes: the abnormal terminal interview method debugging plan.

[0079] Specifically, if the video still stutters after the remote interview backend guides the interviewee to switch the network of the abnormal terminal according to the corresponding debugging plan for abnormal terminal network switching, the cause of the video stuttering is determined to be poor network quality. The terminal with poor network quality is then identified as the abnormal terminal. The remote interview backend generates a corresponding debugging plan based on the cause of the video stuttering. This debugging plan is for the abnormal terminal interview method. If the abnormal terminal does not experience video stuttering after executing the abnormal terminal network switching debugging plan, it indicates that the cause of the video stuttering is indeed a network abnormality. At this point, the network configuration parameters have been adjusted to normal, and the testing ends.

[0080] In one embodiment, the debugging solution for abnormal terminal interview mode is to send a voice switching prompt to the interviewer's terminal, instructing the interviewer to switch from video interview to voice interview.

[0081] In one embodiment, when the abnormal terminal still experiences video stuttering after executing the abnormal terminal network switching debugging scheme, the cause of the video stuttering is determined to be poor network quality. After identifying the terminal with poor network quality as the abnormal terminal, the method further includes: when conducting a remote interview using voice, periodically calling the camera of the requesting interview terminal to capture a single-frame image of the requesting interview terminal user. The single-frame image contains the facial information of the requesting interview terminal user. Face recognition is performed on the single-frame image to determine whether the user of the requesting interview terminal is the applicant.

[0082] Specifically, during a remote interview conducted via voice call, the remote interview backend will capture single-frame images of the user through the camera of the requesting interview terminal. Facial recognition will then be performed by comparing these single-frame images with pre-stored images of the applicant's face in the remote interview backend. Based on the recognition results, it will be determined whether the user requesting the interview terminal is indeed the applicant. This method effectively prevents users from cheating during the voice interview process and avoids having someone else conduct the interview on their behalf.

[0083] In the above embodiments, when abnormal stuttering occurs during a remote video interview, the remote interview backend determines the cause of the stuttering by retrieving various parameters from both the requesting interview terminal and the interviewer's terminal, and generates a corresponding troubleshooting solution based on the cause. Using the video interview method described above, when abnormal stuttering occurs during a remote interview, the remote interview backend can quickly identify the cause of the problem and the corresponding solution, greatly accelerating the resolution of video stuttering issues during the interview.

[0084] In one embodiment, a video interview method is provided, comprising the following steps:

[0085] Step 1: When the user requesting the interview terminal is determined to be the applicant who made the interview appointment based on the facial recognition result, a video interview invitation is sent to the interviewer's terminal.

[0086] Step 2: After accepting the video interview invitation on the interviewer's terminal, start the video interview and forward the video interview screen.

[0087] Step 3: When video interview stuttering is detected, the abnormal terminal and the cause of video stuttering are determined based on the configuration of the requesting interview terminal and the interviewer's terminal.

[0088] Step 4: When the video stutters, send a notification that the abnormal terminal status is abnormal to the normal terminal whose test result is normal.

[0089] Specifically, the remote interview backend performs detection based on the configuration of the requesting interview terminal and the interviewer's terminal. After determining the abnormal terminal and the cause of video lag, it sends an abnormal terminal status prompt to the normal terminals whose detection results are normal.

[0090] Step 5: When the abnormal terminal executes the corresponding debugging solution based on the cause of video stuttering, send a prompt to the normal terminal indicating that the abnormal terminal is being debugged.

[0091] Specifically, while the remote interview backend guides the interview participants to debug the abnormal terminal according to the corresponding debugging plan, it also sends a prompt that the abnormal terminal is being debugged to the normal terminals whose detection results are normal.

[0092] Step 6: Send the corresponding debugging plan to the abnormal terminal. The debugging plan will guide the interview participants to debug the abnormal terminal.

[0093] Step 7: After the abnormal terminal has completed the corresponding debugging scheme, send a notification to the normal terminal indicating that the debugging of the abnormal terminal has ended.

[0094] Specifically, after the remote interview backend guides the interview participants to perform debugging operations on the abnormal terminal according to the corresponding debugging plan, the remote interview backend sends a prompt that the abnormal terminal debugging is complete to the normal terminal whose detection result is normal.

[0095] In this embodiment, the remote interview backend generates a prompt message based on the real-time status of the abnormal terminal and sends the prompt message to the normal terminal whose detection result is normal. Using the method in this embodiment, when an abnormal pause occurs during the remote interview process, the normal terminal can clearly know the status of the other party's terminal based on the prompt message sent by the remote interview backend, and can have a better understanding and control of the entire interview process.

[0096] In one embodiment, such as Figure 4As shown, when the user requesting the interview terminal is determined to be the applicant for the interview appointment based on the facial recognition result, a video interview invitation is sent to the interviewer's terminal, which also includes the following steps:

[0097] Step 401: When an interview request is received from the interview request terminal, the camera of the interview request terminal is invoked to capture the image of the first applicant.

[0098] Specifically, the user requesting the interview terminal triggers the interview request. The remote interview backend, based on the interview request, calls the camera of the requesting interview terminal, captures the user's facial image through the camera, and uses this facial image as the first candidate's image.

[0099] Step 402: Perform facial recognition on the image of the first applicant and the image of the second applicant who has made an interview appointment to determine whether the current applicant is the applicant who made the interview appointment.

[0100] The second applicant's image can be an image from the online or offline resume or materials provided by the applicant when scheduling an interview, which can be pre-stored in the remote interview backend.

[0101] Specifically, the remote interview backend extracts first and second facial feature information from the images of the first and second applicants. The first facial feature information is the facial feature information of the first applicant's image; the second facial feature information is the facial feature information of the second applicant's image. A face recognition operation is performed based on the first and second facial feature information. Based on the face recognition result, it is determined whether the current applicant is the one scheduled for the interview. It is understood that the face recognition operation in this embodiment can be performed using face recognition algorithms such as Eigenfaces and Fisherfaces, and this application does not limit it to these algorithms.

[0102] Step 403: When the facial recognition results confirm that the current applicant is the applicant who has made an interview appointment, a video interview invitation is sent to the interviewer's terminal.

[0103] Specifically, when the remote interview backend determines, based on facial recognition results, that the user requesting the interview terminal is the applicant who has made an interview appointment, it sends a video interview invitation from the requesting terminal to the interviewer's terminal. The interview appointment is a pre-arranged job interview appointment established between the applicant and the interviewer by submitting their resume or personal information online or offline.

[0104] In this embodiment, the remote interview backend periodically captures single-frame images containing the facial information of the user requesting the interview, and performs facial recognition operations against pre-stored images of the applicant's facial information to determine if the interviewee is indeed the applicant. Using the method in this embodiment for remote video interviews can prevent issues during the interview process.

[0105] In one embodiment, such as Figure 5 As shown, a video interview method is provided, including the following steps:

[0106] This embodiment involves a request-for-interview terminal, an interviewer terminal, and a remote interview backend. The request-for-interview terminal and the interviewer terminal communicate with the remote interview backend via a network. The request-for-interview terminal runs a candidate interface and an AI assistant, allowing candidates to participate in the interview. The interviewer terminal runs an interviewer interface and an AI assistant, allowing interviewers to conduct interviews with candidates. The remote interview backend provides a data communication bridge between the request-for-interview terminal and the interviewer terminal, and the AI ​​assistant provides relevant AI services to both candidates and interviewers.

[0107] After entering the interview room, the user can click the check-in button on the applicant interface to trigger facial recognition. Specifically, the camera on the requesting interview terminal can identify the applicant and obtain facial recognition data. Facial recognition data refers to a video stream containing the facial image information of the user on the requesting interview terminal. The facial recognition data is then output to the remote interview backend, which analyzes the facial recognition data to determine the facial recognition result. Specifically, the remote interview backend's database can pre-store the facial image information of the scheduled applicants. By matching the currently obtained facial recognition data with the pre-stored facial image information of the scheduled applicants in the database, it is determined whether the user is an applicant, and the facial recognition result is returned.

[0108] When the facial recognition result indicates that the user is the applicant, the remote interview backend control activates the camera on the requesting interview terminal, and the applicant waits for the interviewer. When the facial recognition result indicates that the user is not the applicant, the system prompts that the applicant must attend the interview in person and exits the interview room.

[0109] Interviewers can enter the interview room through their interviewer terminal. Once inside, they can turn on their camera and establish a real-time video communication with the candidate.

[0110] During the video communication between the applicant and the interviewer, the remote interview backend can monitor the data interaction in real time, such as the data transmission rate. If a video stuttering is detected based on the data transmission rate, a corresponding debugging solution is generated, and an AI assistant is activated. The AI ​​assistant guides the interviewer and applicant to resolve the video stuttering problem through the corresponding debugging solution until the interview ends and the interviewer and applicant leave the interview room.

[0111] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0112] Based on the same inventive concept, this application also provides a video interview device for implementing the video interview method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more video interview device embodiments provided below can be found in the limitations of the video interview method described above, and will not be repeated here.

[0113] In one embodiment, such as Figure 6 As shown, a video interview device is provided, including: an interview invitation module 501, an interview initiation module 502, an interview detection module 503, and a debugging guidance module 504, wherein:

[0114] The interview invitation module 501 is used to send a video interview invitation to the interviewer's terminal when the user requesting the interview terminal is determined to be the applicant who made the interview appointment based on the facial recognition result.

[0115] The interview initiation module 502 is used to initiate a video interview and forward the video interview screen after the interviewer receives the video interview invitation on the interviewer's terminal.

[0116] The interview detection module 503 is used to detect when the video interview screen is detected to be choppy. It performs detection based on the configuration of the requesting interview terminal and the interviewer terminal. When it is determined that the cause of the video choppy is a terminal configuration problem, the terminal with abnormal configuration is identified as an abnormal terminal.

[0117] The debugging guidance module 504 is used to send the corresponding debugging plan to the abnormal terminal. The corresponding debugging plan includes: the debugging plan for the configuration parameters of the abnormal terminal. The debugging plan guides the interview participants to debug the abnormal terminal.

[0118] In one embodiment, the interview detection module 503 is further configured to: when it is determined that the video stuttering is not due to a terminal configuration issue, obtain the network parameters of the requesting interview terminal and the interviewer terminal; and when it is determined that the video stuttering is due to a network anomaly based on the network parameters of the requesting interview terminal and the interviewer terminal, identify the terminal with the network anomaly as an abnormal terminal.

[0119] The corresponding debugging solutions include: debugging solutions for abnormal terminal network switching.

[0120] In one embodiment, the interview detection module 503 is further configured to: when a video interview is detected to be stuttering, if it is determined that the video stuttering occurs again after the abnormal terminal has executed the abnormal terminal's configuration parameter adjustment scheme, then send an abnormal terminal network switching debugging scheme to the abnormal terminal.

[0121] In one embodiment, the interview detection module 503 is further configured to: when the abnormal terminal still experiences video stuttering after executing the abnormal terminal network switching debugging scheme, determine that the cause of the video stuttering is poor network quality, and identify the terminal with poor network quality as an abnormal terminal; the corresponding debugging scheme includes: a debugging scheme for the abnormal terminal interview method.

[0122] In one embodiment, the device further includes: a status prompt module; the status prompt module is used to send a prompt indicating that the abnormal terminal is in an abnormal state to a normal terminal whose detection result is normal when the video screen stutters; to send a prompt indicating that the abnormal terminal is being debugged to a normal terminal when the abnormal terminal executes the corresponding debugging plan according to the cause of the video stuttering; and to send a prompt indicating that the abnormal terminal has finished debugging to a normal terminal after the abnormal terminal has completed the corresponding debugging plan.

[0123] In one embodiment, when the interview invitation module 501 determines, based on the facial recognition result, that the user requesting the interview terminal is an applicant who has made an interview appointment, and sends a video interview invitation to the interviewer terminal, the process includes: when receiving an interview request triggered on the requesting interview terminal, calling the camera of the requesting interview terminal to capture an image of the first applicant; performing facial recognition on the first applicant image and the image of the second applicant who made the interview appointment to determine whether the current applicant is the applicant who made the interview appointment; and when the facial recognition result determines that the current applicant is the applicant who made the interview appointment, sending a video interview invitation to the interviewer terminal.

[0124] The aforementioned video interview device, when a remote video interview is required, first performs facial recognition on the user requesting the interview terminal. After confirming that the user is the client who made the interview appointment, it sends a video interview invitation to the interview terminal, starts the video interview, and forwards the video interview screen. By performing facial recognition on the user requesting the interview terminal beforehand, the risk of someone else conducting the interview on their behalf is effectively avoided. Secondly, during the interview, the device monitors the video screen. When the video interview screen freezes, it checks the terminal configurations of both parties to determine the abnormal terminal and the cause of the video freeze. It then guides the abnormal terminal to be debugged according to the corresponding troubleshooting solution, ensuring that the interview process proceeds normally. The time and location of the interview are more flexible, solving the problem of poor video communication that often occurs during interviews, and providing users with a better user experience during the interview process.

[0125] The modules in the aforementioned video interview device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0126] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 6 As shown, the computer device includes a processor, memory, and a communication interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When executed by the processor, the computer program implements a video interview method.

[0127] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0128] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0129] When the user requesting the interview terminal is identified as the applicant for the interview appointment based on the facial recognition results, a video interview invitation is sent to the interviewer's terminal.

[0130] After accepting the video interview invitation on the interviewer's terminal, start the video interview and forward the video interview screen;

[0131] When video interview stuttering is detected, the configuration of the requesting interview terminal and the interviewer's terminal is checked. If the video stuttering is determined to be caused by terminal configuration issues, the terminal with abnormal configuration is identified as an abnormal terminal.

[0132] Send the corresponding debugging plan to the abnormal terminal. The corresponding debugging plan includes: a debugging plan for the configuration parameters of the abnormal terminal. The debugging plan guides the interview participants to debug the abnormal terminal.

[0133] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0134] When the video stuttering is determined to be caused by something other than terminal configuration, obtain the network parameters of the requesting interview terminal and the interviewer's terminal; if the video stuttering is determined to be caused by a network error based on the network parameters of the requesting interview terminal and the interviewer's terminal, then identify the terminal with the network error as the abnormal terminal.

[0135] The corresponding debugging solutions include: debugging solutions for abnormal terminal network switching.

[0136] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0137] When video interview stuttering is detected, if the video stuttering occurs again after the abnormal terminal's configuration parameters are adjusted, a network switching debugging plan for the abnormal terminal is sent to the abnormal terminal.

[0138] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0139] If video stuttering still occurs after the abnormal terminal has implemented the abnormal terminal network switching debugging plan, the cause of the video stuttering is determined to be poor network quality, and the terminal with poor network quality is identified as an abnormal terminal; the corresponding debugging plan includes: the abnormal terminal interview method debugging plan.

[0140] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0141] When video playback stutters, a notification indicating an abnormal terminal status is sent to a normal terminal whose detection result is normal.

[0142] When the abnormal terminal executes the corresponding debugging solution based on the cause of video stuttering, a prompt that the abnormal terminal is being debugged is sent to the normal terminal;

[0143] After the abnormal terminal completes the corresponding debugging scheme, a message indicating that the abnormal terminal debugging has ended is sent to the normal terminal.

[0144] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0145] When an interview request is received from the interview request terminal, the camera of the interview request terminal is invoked to capture the image of the first applicant.

[0146] The image of the first applicant is compared with the image of the second applicant who has made an interview appointment to determine whether the current applicant is the one who made the interview appointment.

[0147] When the facial recognition results confirm that the current applicant is the one who has scheduled an interview, a video interview invitation is sent to the interviewer's terminal.

[0148] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0149] When the user requesting the interview terminal is identified as the applicant for the interview appointment based on the facial recognition results, a video interview invitation is sent to the interviewer's terminal.

[0150] After accepting the video interview invitation on the interviewer's terminal, start the video interview and forward the video interview screen;

[0151] When video interview stuttering is detected, the configuration of the requesting interview terminal and the interviewer's terminal is checked. If the video stuttering is determined to be caused by terminal configuration issues, the terminal with abnormal configuration is identified as an abnormal terminal.

[0152] Send the corresponding debugging plan to the abnormal terminal. The corresponding debugging plan includes: a debugging plan for the configuration parameters of the abnormal terminal. The debugging plan guides the interview participants to debug the abnormal terminal.

[0153] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0154] When the video stuttering is determined to be caused by something other than terminal configuration, obtain the network parameters of the requesting interview terminal and the interviewer's terminal; if the video stuttering is determined to be caused by a network error based on the network parameters of the requesting interview terminal and the interviewer's terminal, then identify the terminal with the network error as the abnormal terminal.

[0155] The corresponding debugging solutions include: debugging solutions for abnormal terminal network switching.

[0156] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0157] When video interview stuttering is detected, if the video stuttering occurs again after the abnormal terminal's configuration parameters are adjusted, a network switching debugging plan for the abnormal terminal is sent to the abnormal terminal.

[0158] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0159] If video stuttering still occurs after the abnormal terminal has implemented the abnormal terminal network switching debugging plan, the cause of the video stuttering is determined to be poor network quality, and the terminal with poor network quality is identified as an abnormal terminal; the corresponding debugging plan includes: the abnormal terminal interview method debugging plan.

[0160] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0161] When video playback stutters, a notification indicating an abnormal terminal status is sent to a normal terminal whose detection result is normal.

[0162] When the abnormal terminal executes the corresponding debugging solution based on the cause of video stuttering, a prompt that the abnormal terminal is being debugged is sent to the normal terminal;

[0163] After the abnormal terminal completes the corresponding debugging scheme, a message indicating that the abnormal terminal debugging has ended is sent to the normal terminal.

[0164] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0165] When an interview request is received from the interview request terminal, the camera of the interview request terminal is invoked to capture the image of the first applicant.

[0166] The image of the first applicant is compared with the image of the second applicant who has made an interview appointment to determine whether the current applicant is the one who made the interview appointment.

[0167] When the facial recognition results confirm that the current applicant is the one who has scheduled an interview, a video interview invitation is sent to the interviewer's terminal.

[0168] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0169] When the user requesting the interview terminal is identified as the applicant for the interview appointment based on the facial recognition results, a video interview invitation is sent to the interviewer's terminal.

[0170] After accepting the video interview invitation on the interviewer's terminal, start the video interview and forward the video interview screen;

[0171] When video interview stuttering is detected, the configuration of the requesting interview terminal and the interviewer's terminal is checked. If the video stuttering is determined to be caused by terminal configuration issues, the terminal with abnormal configuration is identified as an abnormal terminal.

[0172] Send the corresponding debugging plan to the abnormal terminal. The corresponding debugging plan includes: a debugging plan for the configuration parameters of the abnormal terminal. The debugging plan guides the interview participants to debug the abnormal terminal.

[0173] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0174] When the video stuttering is determined to be caused by something other than terminal configuration, obtain the network parameters of the requesting interview terminal and the interviewer's terminal; if the video stuttering is determined to be caused by a network error based on the network parameters of the requesting interview terminal and the interviewer's terminal, then identify the terminal with the network error as the abnormal terminal.

[0175] The corresponding debugging solutions include: debugging solutions for abnormal terminal network switching.

[0176] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0177] When video interview stuttering is detected, if the video stuttering occurs again after the abnormal terminal's configuration parameters are adjusted, a network switching debugging plan for the abnormal terminal is sent to the abnormal terminal.

[0178] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0179] If video stuttering still occurs after the abnormal terminal has implemented the abnormal terminal network switching debugging plan, the cause of the video stuttering is determined to be poor network quality, and the terminal with poor network quality is identified as an abnormal terminal; the corresponding debugging plan includes: the abnormal terminal interview method debugging plan.

[0180] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0181] When video playback stutters, a notification indicating an abnormal terminal status is sent to a normal terminal whose detection result is normal.

[0182] When the abnormal terminal executes the corresponding debugging solution based on the cause of video stuttering, a prompt that the abnormal terminal is being debugged is sent to the normal terminal;

[0183] After the abnormal terminal completes the corresponding debugging scheme, a message indicating that the abnormal terminal debugging has ended is sent to the normal terminal.

[0184] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0185] When an interview request is received from the interview request terminal, the camera of the interview request terminal is invoked to capture the image of the first applicant.

[0186] The image of the first applicant is compared with the image of the second applicant who has made an interview appointment to determine whether the current applicant is the one who made the interview appointment.

[0187] When the facial recognition results confirm that the current applicant is the one who has scheduled an interview, a video interview invitation is sent to the interviewer's terminal.

[0188] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0189] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0190] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0191] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A video interview method, characterized in that, The method includes: When the user requesting the interview terminal is identified as the applicant for the interview appointment based on the facial recognition results, a video interview invitation is sent to the interviewer's terminal. After accepting the video interview invitation on the interviewer's terminal, the video interview is started and the video interview screen is forwarded. When a stutter is detected in the video interview, the configuration of the requesting interview terminal and the interviewer's terminal is checked. If the stutter is determined to be caused by a terminal configuration issue, the terminal with the abnormal configuration is identified as the abnormal terminal. Send a corresponding debugging plan to the abnormal terminal. The corresponding debugging plan includes: a debugging plan for the configuration parameters of the abnormal terminal. The debugging plan guides the interview participants to debug the abnormal terminal. When it is determined that the video stuttering is not due to a terminal configuration issue, the network parameters of the requesting interview terminal and the interviewer's terminal are obtained. When the network parameters determine that the video stuttering is caused by a network anomaly, the terminal with the network anomaly is identified as the abnormal terminal, and a network switching debugging plan for the abnormal terminal is sent to the abnormal terminal. If the abnormal terminal still experiences video stuttering after executing the network switching debugging scheme, the cause of the video stuttering is determined to be poor network quality. The terminal with poor network quality is identified as an abnormal terminal, and the corresponding debugging scheme includes: the debugging scheme for the abnormal terminal interview method; the debugging scheme for the abnormal terminal interview method includes sending a voice switching prompt to the interview terminal, and instructing the interviewer to switch the video interview to a voice interview through the voice switching prompt. When conducting remote interviews using voice, the camera of the requesting interview terminal is periodically invoked to capture single-frame images of the user. Facial recognition is then performed on the single-frame images to determine whether the user is the applicant who has scheduled an interview.

2. The method according to claim 1, characterized in that, The debugging scheme for abnormal terminal network switching includes: Instruct the interview participants to switch the network configuration of the abnormal terminal from a mobile network to a wireless network, or to convert it to a mobile network of a higher level than the current mobile network.

3. The method according to claim 1, characterized in that, When the video interview is detected to be stuttering, if it is determined that the video stuttering occurred again after the abnormal terminal executed the configuration parameter adjustment scheme of the abnormal terminal, then the abnormal terminal network switching debugging scheme is sent to the abnormal terminal.

4. The method according to claim 1, characterized in that, The method further includes: When the video interview screen freezes, a notification indicating that the abnormal terminal is in an abnormal state is sent to a normal terminal whose detection result is normal. When the abnormal terminal executes the corresponding debugging plan according to the cause of the video stuttering, a prompt is sent to the normal terminal indicating that the abnormal terminal is being debugged; After the abnormal terminal completes the corresponding debugging scheme, a notification indicating that the debugging of the abnormal terminal has ended is sent to the normal terminal.

5. The method according to claim 1, characterized in that, When the user requesting the interview at the interview terminal is identified as the applicant for the interview appointment based on facial recognition results, a video interview invitation is sent to the interviewer's terminal, including: When an interview request is received from the interview request terminal, the camera of the interview request terminal is invoked to capture the image of the first applicant; The image of the first applicant is compared with the image of the second applicant who has made an interview appointment to determine whether the current applicant is the one who made the interview appointment. When the facial recognition results confirm that the current applicant is the applicant for the interview appointment, a video interview invitation is sent to the interviewer's terminal.

6. A video interview device, characterized in that, The device includes: The interview invitation module is used to send a video interview invitation to the interviewer's terminal when the user requesting the interview terminal is determined to be the applicant who has made an interview appointment based on the facial recognition results. The interview initiation module is used to initiate a video interview and forward the video interview screen after the interviewer's terminal accepts the video interview invitation. The interview detection module is used to detect when the video interview screen is detected to be lagging, based on the configuration of the requesting interview terminal and the interviewer terminal. When it is determined that the video lag is caused by a terminal configuration problem, the terminal with the abnormal configuration is identified as the abnormal terminal. The debugging guidance module is used to send a corresponding debugging plan to the abnormal terminal. The corresponding debugging plan includes a debugging plan for the configuration parameters of the abnormal terminal. The debugging plan guides the interview participants to debug the abnormal terminal. The interview detection module is further configured to: when the video stuttering is determined to be due to reasons other than terminal configuration, obtain the network parameters of the requesting interview terminal and the interviewer's terminal; when the video stuttering is determined to be due to a network anomaly based on the network parameters, identify the terminal with the network anomaly as the abnormal terminal and send a network switching debugging plan to the abnormal terminal; when the abnormal terminal still experiences video stuttering after executing the network switching debugging plan, determine that the video stuttering is due to poor network quality, identify the terminal with poor network quality as the abnormal terminal, and the corresponding debugging plan includes: a debugging plan for the abnormal terminal interview method; the debugging plan for the abnormal terminal interview method includes sending a voice switching prompt to the interview terminal, instructing the interviewer to switch the video interview to a voice interview through the voice switching prompt; when conducting a remote interview using voice, periodically call the camera of the requesting interview terminal to capture a single frame image of the user, perform face recognition on the single frame image, and determine whether the user is the applicant who made the interview appointment.

7. The apparatus according to claim 6, characterized in that, The interview testing module is also used for: When the video interview is detected to be stuttering, if it is determined that the video stuttering occurred again after the abnormal terminal executed the configuration parameter adjustment scheme of the abnormal terminal, then the abnormal terminal network switching debugging scheme is sent to the abnormal terminal.

8. The apparatus according to claim 6 or 7, characterized in that, The device further includes: a status indication module; The status prompt module is used to send a prompt indicating that the abnormal terminal is in an abnormal state to a normal terminal with a normal detection result when the video interview screen stutters; to send a prompt indicating that the abnormal terminal is debugging when the abnormal terminal executes the corresponding debugging plan according to the cause of the video stuttering to the normal terminal; and to send a prompt indicating that the abnormal terminal has finished debugging to the normal terminal after the abnormal terminal has completed the corresponding debugging plan.

9. The apparatus according to claim 6, characterized in that, When the interview invitation module determines, based on facial recognition results, that the user requesting the interview terminal is the applicant who has made an interview appointment, it sends a video interview invitation to the interviewer's terminal, including: When an interview request is received from the interview requesting terminal, the camera of the interview requesting terminal is invoked to capture the image of the first applicant; the image of the first applicant is compared with the image of the second applicant who has made an interview appointment to perform facial recognition to determine whether the current applicant is the applicant who made the interview appointment; when the facial recognition result determines that the current applicant is the applicant who made the interview appointment, a video interview invitation is sent to the interviewer terminal.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

12. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

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