User account login method and device, vehicle and storage medium
Automatic login and binding personalized settings through facial feature recognition, the problems of low efficiency and insufficient security of user account login are solved, and automatic synchronization of uninfluenced login and personalized settings are achieved, improving user experience and security.
Patent Information
- Application Number
- CN202510762707.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-09
- Publication Date
- 2025-07-18
AI Technical Summary
In the prior art, the user account login method is inefficient and insufficiently secure, and the personalized settings are not bound to the account, resulting in users having to repeat operations and reducing the driving experience.
By obtaining user facial images, identifying facial feature values and matching them with pre-stored feature values, personalized settings are automatically imported when conditions are met, and warnings are generated when verification fails and manual login is prompted, combining facial and manual dual-path binding logic.
Improve login efficiency, optimize user experience, personalized settings are dynamically bound to account, enhance security and privacy protection, and compatible with identification under different lighting conditions.
Smart Images
Figure CN120342774A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of vehicles, and particularly to a method and device for logging in a user account, a vehicle, and a storage medium. Background Art
[0002] With the popularization and promotion of intelligent cockpits in the fields of passenger vehicles and commercial vehicles, users' demands for vehicle intelligence and personalization are increasing. Among them, the user account is a key function in the intelligent cockpit. By logging in with the user account, user identity recognition can be performed, which is generally used for fleet management, payment function binding, corresponding service permissions, etc.
[0003] In the related art, the user's account login method mainly logs in by entering an account number, password, or swiping a card.
[0004] However, logging in by entering an account number and password has a cumbersome process and a risk of password leakage. Swiping card login depends on hardware support (card reader), and the function is likely to fail due to device damage or card loss during swiping. In addition, in the related art, the user account is not bound to personalized settings (such as seat position, air conditioning parameters, screen brightness, etc.), resulting in users having to repeat adjustments, reducing the driving and riding experience of users, which urgently needs to be solved. Summary of the Invention
[0005] The present application provides a method and device for logging in a user account, a vehicle, and a storage medium to solve the problems in the related art such as low efficiency and insufficient security of the login method, and at the same time, the personalized settings are not bound to the account, and users need to repeat operations.
[0006] The first aspect of the present application provides a method for logging in a user account, including the following steps:
[0007] Obtain the current facial image of the user and identify the facial feature value of the current facial image;
[0008] Determine whether the matching degree between the facial feature value and the pre-stored facial feature value to be matched meets a preset matching condition. If the matching degree between the facial feature value and the pre-stored facial feature value to be matched meets the preset matching condition, it is determined that the current user account verification is successful, and the vehicle personalized settings corresponding to the current user account are automatically imported. Otherwise, it is determined that the current user account verification fails, and at the same time, the verification failure times of the current user account are collected;
[0009] Determine whether the verification failure times exceed a preset verification times. If the verification failure times exceed the preset verification times, a warning reminder is generated and a manual login prompt is given to remind the user to perform a manual login.
[0010] Preferably, before obtaining the current facial image of the user, it further includes:
[0011] Receiving a facial image acquisition instruction of the user;
[0012] Collecting the facial feature values to be matched of the user based on the facial image acquisition instruction, storing the facial feature values to be matched, and at the same time, associating and binding the facial feature values to be matched with the user account.
[0013] Preferably, after determining that the current user account verification is successful, it further includes:
[0014] Judging whether the current user account and the previous user account are the same user account;
[0015] If the current user account and the previous user account are the same user account, maintaining the login state of the current user account, otherwise, logging out the previous user account and automatically logging in based on the account password corresponding to the facial feature values of the current user account.
[0016] Preferably, after determining that the current user account verification is successful, it further includes:
[0017] Judging whether a personalized modification instruction of the user is received;
[0018] If the personalized modification instruction is received, updating the personalized modification settings of the user and storing the updated personalized modification settings to the current user account.
[0019] Preferably, after generating a warning reminder when the number of verification failures exceeds the preset number of verifications, it further includes:
[0020] Judging whether there is an account login currently;
[0021] If there is an account login currently, logging out the account login and generating a manual login prompt for the user based on a preset window, otherwise, directly generating a manual login prompt for the user based on the preset window.
[0022] An embodiment of the second aspect of the present application provides a login device for a user account, including:
[0023] An acquisition module, configured to acquire the current facial image of the user and identify the facial feature values of the current facial image;
[0024] A judgment module, configured to judge whether the matching degree between the facial feature value and the pre-stored facial feature value to be matched meets a preset matching condition. If the matching degree between the facial feature value and the pre-stored facial feature value to be matched meets the preset matching condition, it is determined that the current user account verification is successful, and the vehicle personalized settings corresponding to the current user account are automatically imported. Otherwise, it is determined that the current user account verification fails, and meanwhile, the number of verification failures of the current user account is collected.
[0025] A reminder module, configured to judge whether the number of verification failures exceeds a preset verification number. If the number of verification failures exceeds the preset verification number, a warning reminder is generated, and a manual login prompt is given to remind the user to perform a manual login.
[0026] Preferably, before obtaining the current facial image of the user, the obtaining module is further configured to:
[0027] Receive the facial image acquisition instruction of the user;
[0028] Collect the facial feature value to be matched of the user based on the facial image acquisition instruction, store the facial feature value to be matched, and meanwhile, associate and bind the facial feature value to be matched with the user account.
[0029] Preferably, after determining that the current user account verification is successful, the judgment module is further configured to:
[0030] Judge whether the current user account and the previous user account are the same user account;
[0031] If the current user account and the previous user account are the same user account, maintain the login state of the current user account. Otherwise, log out the previous user account and automatically log in based on the account password corresponding to the facial feature value of the current user account.
[0032] Preferably, after determining that the current user account verification is successful, the judgment module is further configured to:
[0033] Judge whether a personalized modification instruction of the user is received;
[0034] If the personalized modification instruction is received, update the personalized modification settings of the user, and store the updated personalized modification settings in the current user account.
[0035] Preferably, after the number of verification failures exceeds the preset verification number and a warning reminder is generated, the reminder module further includes:
[0036] Judge whether there is an account login currently;
[0037] If the account is currently logged in, log out of the account and generate a manual login prompt for the user based on a preset window. Otherwise, directly generate a manual login prompt for the user based on the preset window.
[0038] An embodiment of the third aspect of the present application provides a vehicle, including: a memory, a processor, and a computer program stored on the memory and executable on the processor. The processor executes the program to implement the login method of the user account as described in the above embodiments.
[0039] An embodiment of the fourth aspect of the present application provides a computer-readable storage medium, on which a computer program is stored. The program is executed by a processor to implement the login method of the user account as described in the above embodiments.
[0040] Thus, the present application has at least the following beneficial effects: identifying the facial feature value of the current facial image, determining that the current user account verification is successful when the matching degree between the facial feature value and the pre-stored facial feature value to be matched meets the preset matching condition, and automatically importing the vehicle personalized settings corresponding to the current user account. Otherwise, determining that the current user account verification fails, and at the same time, when the number of verification failures exceeds the preset verification times, generating a warning reminder and a manual login prompt to remind the user to perform a manual login. Thus, the problems in the related art such as low efficiency and insufficient security of the login method, and the lack of binding between the personalized settings and the account, and the need for the user to repeat operations are solved. By collecting the user's facial features, using the dual-path binding logic of face and manual to log in, and dynamically associating the personalized settings with the account, the login efficiency is improved and the user experience is improved.
[0041] The additional aspects and advantages of the present application will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS
[0042] The above and / or additional aspects and advantages of the present application will become obvious and easy to understand from the following description of the embodiments in conjunction with the drawings, where:
[0043] Figure 1 is a flowchart of a method for logging in a user account according to an embodiment of the present application;
[0044] Figure 2 is a flowchart of the overall solution according to an embodiment of the present application;
[0045] Figure 3 is a block diagram example of a device for logging in a user account according to an embodiment of the present application;
[0046] Figure 4 is a schematic structural diagram of a vehicle according to an embodiment of the present application.
[0047] Description of reference numerals: 100 - acquisition module; 200 - determination module; 300 - reminder module. DETAILED DESCRIPTION
[0048] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.
[0049] The following describes the detection method, device, vehicle and storage medium of the labeled data sample of the embodiment of the present application with reference to the accompanying drawings. Specifically, Figure 1 A flowchart of a method for logging into a user account provided in an embodiment of the present application.
[0050] like Figure 1 As shown, the login method of the user account includes the following steps:
[0051] In step S101, a current facial image of a user is acquired, and facial feature values of the current facial image are identified.
[0052] Preferably, before obtaining the user's current facial image, it also includes: receiving the user's facial image acquisition instruction; acquiring the user's facial feature values to be matched based on the facial image acquisition instruction, and storing the facial feature values to be matched, and at the same time, associating and binding the facial feature values to be matched with the user account.
[0053] Specifically, Figure 2 As shown, when the system starts, it first detects the network connection status. It can determine whether the system is in an online state through USB (Universal Serial Bus), Ethernet shared TBOX (Telematics BOX, vehicle-mounted intelligent communication terminal) network or through the vehicle cabin domain WiFi connected to the mobile phone hotspot. If the network is abnormal, that is, the network is unavailable, the user is prompted to connect to the network and the subsequent process is suspended. If the network is normal, that is, the system is in an online state, the user's facial feature collection device is activated, such as the DMS (Driver Monitoring System) camera. The user clicks OK to jump to the face collection page. At this time, after the DMS camera receives the user's facial image collection instruction, it also triggers a voice prompt for collecting facial features, such as "Face detection login, please look at the front camera", and the DMS camera takes a picture of the user's face to obtain the user's facial image.
[0054] Secondly, the face feature values to be matched of the user are extracted based on the user's face image. For example, quantitative data such as the user's facial geometric feature points, contour curvature, and the distance between facial organs are extracted. Among them, the face recognition algorithm for the face feature values to be matched integrates a third-party DMS algorithm. The comparison result is obtained through the SDK (Software Development Kit) interface for face recognition technology extraction, and the extracted face feature values to be matched are encrypted by AES-256 (Advanced Encryption Standard with 256-bit key) and stored in the encrypted feature database. At the same time, if the user logs in for the first time, the face feature values to be matched need to be associated and bound with the user account. Thus, when the current face image of the user is collected and the face feature values are recognized, the face feature values to be matched stored in the encrypted feature database can be used for matching, and the corresponding user account login method can be obtained based on the matching result.
[0055] Among them, the face recognition algorithm also includes face recognition methods based on geometric features, eigenface-based face recognition methods, neural network-based face recognition methods, elastic graph matching-based face recognition methods, face recognition methods based on the line segment Hausdorff distance, etc. The face recognition algorithm in the embodiments of the present application mainly adopts a face feature point-based recognition algorithm. At the same time, the embodiments of the present application can also automatically adjust the face recognition similarity threshold according to the environmental light intensity (for example, the threshold is reduced by 5% in low light), so as to improve the recognition error tolerance rate.
[0056] In step S102, it is judged whether the matching degree between the face feature values and the pre-stored face feature values to be matched meets the preset matching condition. If the matching degree between the face feature values and the pre-stored face feature values to be matched meets the preset matching condition, it is determined that the current user account verification is successful, and the vehicle personalized settings corresponding to the current user account are automatically imported. Otherwise, it is determined that the current user account verification fails, and the number of verification failures of the current user account is collected at the same time.
[0057] Preferably, after it is determined that the current user account verification is successful, it further includes: judging whether the current user account and the previous user account are the same user account; if the current user account and the previous user account are the same user account, the current user account login state is maintained. Otherwise, the previous user account is logged out, and automatic login is performed based on the account password corresponding to the face feature values of the current user account.
[0058] Preferably, after it is determined that the current user account verification is successful, it further includes: judging whether a personalized modification instruction from the user is received; if a personalized modification instruction is received, the user's personalized modification settings are updated, and the updated personalized modification settings are stored in the current user account.
[0059] Among them, the preset matching condition can be set by those skilled in the art according to actual test requirements, and no specific limitation is made here.
[0060] Specifically, as Figure 2 shown, after the DMS camera obtains the user's current facial image and identifies the facial feature value, first, it is determined whether the matching degree between the facial feature value and the pre-stored facial feature value to be matched meets the preset matching condition, that is, the facial feature value is subjected to similarity matching with the facial feature value to be matched. If the similarity between the facial feature value and the facial feature value to be matched meets the preset matching condition, for example, the similarity between the facial feature value and the facial feature value to be matched reaches 95%, it indicates that the facial feature value and the facial feature value to be matched are highly matched and meet the preset matching condition. At this time, the currently obtained current facial image meets the user account login condition, that is, it is determined that the current user account verification is successful, and the user can log in to the account.
[0061] Furthermore, before the user account is logged in, it is necessary to further determine whether the current user account and the previous user account are the same user account, that is, whether the currently logged-in account and the previous logged-in account are the same person. If the current user account and the previous user account are the same user account, it means that the currently logged-in account and the previous logged-in account are the same person. At this time, there is no need to log in again, and the current user account login status can be maintained. If the current user account and the previous user account are not the same user account, it means that the currently logged-in account and the previous logged-in account are not the same person. At this time, it is necessary to log out of the previous user account, obtain the associated account password based on the facial feature value of the current user account, automatically switch accounts to log in, and automatically import the vehicle personalized settings corresponding to the current user account. Among them, the personalized settings can include adjustments to device parameters such as seats, air conditioners, and ambient lights, bind the vehicle personalized settings with the user account, and store them in an independent data partition (not associated with face data) to reduce the risk of privacy leakage.
[0062] Furthermore, if the user wants to change the personalized settings according to their own needs, at this time, the user can click on personalized modification in the display window. For example, modify the air conditioner temperature, seat height, etc. At this time, the system will receive the personalized modification instruction, update the user's personalized modification settings based on the personalized modification instruction, and then store the updated personalized modification settings in the current user account so that the updated personalized settings can be used to serve the user when the user logs in to the account again.
[0063] Further, if the matching degree between the facial feature value and the pre-stored facial feature value to be matched does not meet the preset matching condition, for example, the similarity between the facial feature value and the facial feature value to be matched does not reach 95%, or the DMS camera fails to capture the current facial image of the user, it indicates that the facial feature value of the user is not stored in the encrypted feature database at this time. Therefore, it is determined that the current user account verification fails, and at the same time, the number of verification failures of the current user account is collected to further perform the subsequent login operation according to the number of verification failures.
[0064] In step S103, it is determined whether the number of verification failures exceeds the preset verification times. If the number of verification failures exceeds the preset verification times, a warning reminder is generated, and a manual login prompt is given to remind the user to perform a manual login.
[0065] Preferably, after the number of verification failures exceeds the preset verification times and a warning reminder is generated, it further includes: determining whether there is an account login currently; if there is an account login currently, the account login is exited, and a manual login prompt for the user is generated based on the preset window, otherwise, a manual login prompt for the user is directly generated based on the preset window.
[0066] Among them, the preset verification times and the preset window can be set by those skilled in the art according to actual test requirements, and no specific limitation is made here.
[0067] Specifically, as Figure 2 shown, when the current user account verification fails, the number of verification failures of the current user account is further collected, and it is determined whether the number of verification failures exceeds the preset verification times, such as 3 times. That is to say, after the user fails the first verification, the user verifies two more times at an interval of 5 seconds and still fails. That is, after 3 verifications fail, a warning reminder is generated at this time to prompt the user that the number of face verifications has reached the set value. If there is an account login currently, the logged-in account is exited, and a manual login prompt for the user is generated based on the preset window to prompt the user that they can perform a manual login, that is, the user manually enters the account number and password to log in. If there is no account login currently, a manual login prompt can be directly given to the user through the preset window.
[0068] Further, if the user does not log in according to the manual login prompt generated by the preset window, the process will end directly at this time. Subsequently, the user can also actively enter the personal account application, log in by entering the account number and password. After successful login, a corresponding file path will be established in the data partition (this partition is created for driver configuration and is a specific protected partition that cannot be overwritten by system upgrades), and the account number and password will be stored (the account password is encrypted through an encryption algorithm). After login, the system will automatically import the personalized setting data corresponding to the user account. At the same time, if the user modifies the personalized settings, the updated personalized setting data will be stored before the system powers off. This data is bound to the stored user account and is not associated with the stored facial feature values to be matched. The purpose of not being associated with the facial feature values to be matched is that the user can also log in to the personal account through manual login. Therefore, the stored personalized setting data is associated with the user account and password, while face recognition is bound to the user account.
[0069] Thus, when the facial feature values of the user are recognized, the user account can be automatically logged in based on the facial feature values, or when the facial feature values are not recognized or recognized incorrectly, the user account can be logged in manually. Thus, after the user logs in, the personalized settings corresponding to the user account will be automatically imported. Through this link, whether it is automatic login through face recognition or manual login by the user, the extraction and synchronization of personalized setting data can ultimately be achieved.
[0070] In summary, based on the specific descriptions of the above embodiments, the present application can achieve the following beneficial effects:
[0071] (1) Improve login efficiency and convenience, achieve touchless login through face recognition, and the user does not need to manually enter the account password or swipe the card, reducing the operation steps;
[0072] (2) Optimize the user experience and personalized services, dynamically bind the account with personalized settings (such as seat parameters, air conditioner settings, screen brightness), and achieve automatic data synchronization;
[0073] (3) Enhance system security and privacy protection, store the account password and face feature values in an independent data partition using the AES-256 encryption algorithm to prevent unauthorized access. Only the feature values (not the original images) of the face data are stored, and they are decoupled from the personalized settings, reducing the risk of privacy leakage;
[0074] (4) Improve system robustness and compatibility, associate personalized settings with the account password instead of directly binding to the face data, be compatible with the manual login scenario, and at the same time, the face recognition similarity threshold can be automatically adjusted according to the environmental light intensity (such as reducing the threshold by 5% in low light), improving the recognition error tolerance.
[0075] According to the login method of the user account proposed in the embodiments of the present application, the facial feature value of the current facial image is recognized. When the matching degree between the facial feature value and the pre-stored facial feature value to be matched meets the preset matching condition, it is determined that the current user account verification is successful, and the vehicle personalized settings corresponding to the current user account are automatically imported. Otherwise, it is determined that the current user account verification fails. At the same time, when the number of verification failures exceeds the preset verification times, a warning reminder is generated, and a manual login reminder is given to remind the user to perform a manual login. Thus, the problems in the related art such as low efficiency and insufficient security of the login method, and at the same time, the personalized settings are not bound to the account, and the user needs to repeat operations are solved. By collecting the user's facial features, using the dual-path binding logic of face and manual to log in, and dynamically associating the personalized settings with the account, the login efficiency is improved, and the user experience is improved.
[0076] Next, a login device for a user account according to an embodiment of the present application will be described with reference to the accompanying drawings.
[0077] Figure 3 It is a block diagram of a login device for a user account according to an embodiment of the present application.
[0078] As Figure 3 shown, the login device 10 for the user account includes: an acquisition module 100, a judgment module 200, and a reminder module 300.
[0079] Among them, the acquisition module 100 is used to acquire the current facial image of the user and recognize the facial feature value of the current facial image;
[0080] The judgment module 200 is used to judge whether the matching degree between the facial feature value and the pre-stored facial feature value to be matched meets the preset matching condition. If the matching degree between the facial feature value and the pre-stored facial feature value to be matched meets the preset matching condition, it is determined that the current user account verification is successful, and the vehicle personalized settings corresponding to the current user account are automatically imported. Otherwise, it is determined that the current user account verification fails, and at the same time, the number of verification failures of the current user account is collected;
[0081] The reminder module 300 is used to judge whether the number of verification failures exceeds the preset verification times. If the number of verification failures exceeds the preset verification times, a warning reminder is generated, and a manual login reminder is given to remind the user to perform a manual login.
[0082] Preferably, before acquiring the current facial image of the user, the acquisition module 100 is further used to:
[0083] Receive the facial image acquisition instruction of the user;
[0084] Collect the facial feature values to be matched of the user based on the facial image acquisition instruction, store the facial feature values to be matched, and at the same time, associate and bind the facial feature values to be matched with the user account.
[0085] Preferably, after determining that the current user account verification is successful, the judgment module 200 is further configured to:
[0086] Determine whether the current user account and the previous user account are the same user account;
[0087] If the current user account and the previous user account are the same user account, maintain the login state of the current user account, otherwise, log out the previous user account and automatically log in based on the account password corresponding to the facial feature value of the current user account.
[0088] Preferably, after determining that the current user account verification is successful, the judgment module 200 is further configured to:
[0089] Determine whether a personalized modification instruction from the user is received;
[0090] If a personalized modification instruction is received, update the user's personalized modification settings and store the updated personalized modification settings in the current user account.
[0091] Preferably, after the number of verification failures exceeds the preset number of verification times and a warning reminder is generated, the reminder module 300 further includes:
[0092] Determine whether there is an account login currently;
[0093] If there is an account login currently, log out of the account login and generate a manual login prompt for the user based on a preset window, otherwise, directly generate a manual login prompt for the user based on the preset window.
[0094] According to the user account login device proposed in the embodiment of the present application, the facial feature values of the current facial image are recognized. When the matching degree between the facial feature values and the pre-stored facial feature values to be matched meets the preset matching condition, it is determined that the current user account verification is successful, and the vehicle personalized settings corresponding to the current user account are automatically imported. Otherwise, it is determined that the current user account verification fails. At the same time, when the number of verification failures exceeds the preset number of verification times, a warning reminder is generated and a manual login prompt is given to remind the user to log in manually. Thus, the problems in the related art such as low login efficiency, insufficient security, and the lack of binding between personalized settings and the account, and the need for users to repeat operations are solved. By collecting the user's facial features, using the dual-path binding logic of face and manual login, and dynamically associating the personalized settings with the account, the login efficiency is improved and the user experience is enhanced.
[0095] Figure 4The structural schematic diagram of the vehicle provided by the embodiment of the present application. The vehicle may include:
[0096] A memory 401, a processor 402, and a computer program stored on the memory 401 and executable on the processor 402.
[0097] When the processor 402 executes the program, it implements the user account login method provided in the above embodiments.
[0098] Furthermore, the vehicle further includes:
[0099] A communication interface 403 for communication between the memory 401 and the processor 402.
[0100] The memory 401 is used to store a computer program executable on the processor 402.
[0101] The memory 401 may include a high-speed RAM (Random Access Memory) memory, and may also include a non-volatile memory, such as at least one disk memory.
[0102] If the memory 401, the processor 402, and the communication interface 403 are implemented independently, the communication interface 403, the memory 401, and the processor 402 can be interconnected through a bus and complete communication with each other. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, Figure 4 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.
[0103] Optionally, in a specific implementation, if the memory 401, the processor 402, and the communication interface 403 are integrated on a chip, the memory 401, the processor 402, and the communication interface 403 can complete communication with each other through an internal interface.
[0104] The processor 402 may be a CPU (Central Processing Unit), or an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application.
[0105] An embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the login method of the user account as described above is implemented.
[0106] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms are not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.
[0107] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "N" is at least two, such as two, three, etc., unless otherwise specifically defined.
[0108] Any process or method description shown in the flowchart or described in other ways herein may be understood to represent a module, segment, or portion of code including one or N executable instructions for implementing a customized logic function or process, and the scope of the preferred embodiments of the present application includes additional implementations, where the functions may be executed in a substantially simultaneous manner or in a reverse order according to the involved functions, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present application belong.
[0109] It should be understood that each part of the present application may be implemented by hardware, software, firmware, or a combination thereof. In the above embodiment, the N steps or methods may be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, any one or a combination of the following well-known technologies in the art may be used: discrete logic circuits having logic gate circuits for implementing logic functions on data signals, application-specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays, field-programmable gate arrays, etc.
[0110] Those of ordinary skill in the art can understand that all or part of the steps carried out in implementing the above-described embodiment methods can be completed by instructing relevant hardware through a program. The program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.
[0111] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.
Claims
1. A method for logging in to a user account, characterized in that It includes the following steps: Obtain the current facial image of the user and identify the facial feature values of the current facial image; Determine whether the matching degree between the facial feature values and the pre-stored facial feature values to be matched meets the preset matching condition. If the matching degree between the facial feature values and the pre-stored facial feature values to be matched meets the preset matching condition, it is determined that the current user account verification is successful, and the vehicle personalized settings corresponding to the current user account are automatically imported. Otherwise, it is determined that the current user account verification fails, and at the same time, the number of verification failures of the current user account is collected; Determine whether the number of verification failures exceeds the preset number of verification times. If the number of verification failures exceeds the preset number of verification times, a warning reminder is generated and a manual login prompt is given to remind the user to perform a manual login.
2. The method according to claim 1, characterized in that Before obtaining the current facial image of the user, it further includes: Receive the facial image collection instruction of the user; Collect the facial feature values to be matched of the user based on the facial image collection instruction, store the facial feature values to be matched, and at the same time, associate and bind the facial feature values to be matched with the user account.
3. The method according to claim 1, wherein After determining that the current user account verification is successful, it further includes: Determine whether the current user account and the previous user account are the same user account; If the current user account and the previous user account are the same user account, maintain the current user account login status. Otherwise, log out the previous user account and automatically log in based on the account password corresponding to the facial feature values of the current user account.
4. The method according to claim 3, characterized in that After determining that the current user account verification is successful, it further includes: Determine whether a personalized modification instruction from the user is received; If a personalized modification instruction is received, update the personalized modification settings of the user and store the updated personalized modification settings in the current user account.
5. The method according to claim 1, characterized in that After the number of verification failures exceeds the preset number of verification times and a warning reminder is generated, it further includes: Determine whether there is an account login currently; If there is an account login currently, log out the account login and generate a manual login prompt for the user based on a preset window. Otherwise, directly generate a manual login prompt for the user based on the preset window.
6. A login device for a user account, characterized in that, It includes: An acquisition module, which is used to obtain the current facial image of the user and identify the facial feature values of the current facial image; A judgment module, which is used to judge whether the matching degree between the facial feature values and the pre-stored facial feature values to be matched meets the preset matching condition. If the matching degree between the facial feature values and the pre-stored facial feature values to be matched meets the preset matching condition, it is determined that the current user account verification is successful, and the vehicle personalized settings corresponding to the current user account are automatically imported. Otherwise, it is determined that the current user account verification fails, and at the same time, the number of verification failures of the current user account is collected; A reminder module, which is used to judge whether the number of verification failures exceeds the preset number of verification times. If the number of verification failures exceeds the preset number of verification times, a warning reminder is generated and a manual login prompt is given to remind the user to perform a manual login.
7. The device according to claim 6, wherein Before obtaining the current facial image of the user, the obtaining module is further configured to: Receive the facial image acquisition instruction of the user; Collect the facial feature values to be matched of the user based on the facial image acquisition instruction, store the facial feature values to be matched, and at the same time, associate and bind the facial feature values to be matched with the user account.
8. The device according to claim 6, characterized in that, After determining that the current user account verification is successful, the judging module is further configured to: Judge whether the current user account and the previous user account are the same user account; If the current user account and the previous user account are the same user account, maintain the login state of the current user account, otherwise, log out the previous user account and automatically log in based on the account password corresponding to the facial feature value of the current user account.
9. A vehicle, characterized in that, Including: A memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the program to implement the user account login method according to any one of claims 1-5.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to be used to implement the user account login method according to any one of claims 1-5.