CN110532744A - Face login method, device, computer equipment and storage medium - Google Patents
Face login method, device, computer equipment and storage medium Download PDFInfo
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- 238000001727 in vivo Methods 0.000 claims abstract description 214
- 238000012795 verification Methods 0.000 claims abstract description 96
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- 238000005070 sampling Methods 0.000 claims abstract description 10
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/31—User authentication
- G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/40—Spoof detection, e.g. liveness detection
- G06V40/45—Detection of the body part being alive
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Abstract
The present invention discloses a kind of face login method, device, computer equipment and storage medium, and it includes login account and recognition code in user's logging request that this method, which includes obtaining user's logging request,；It is logged according to login account and recognition code, obtains login result；If login result is to login successfully, verifying corresponding with login account is fed back to mobile terminal and acquires information；Based on the corresponding target video stream of verifying acquisition real time information sampling, calls In vivo detection interface corresponding with target verification type to carry out In vivo detection to target video stream, obtain target In vivo detection result；If target In vivo detection result is In vivo detection success, target facial image is obtained from target video stream, target facial image standard picture corresponding with login account is matched, obtain images match result；If images match result is successful match, controls mobile terminal and show corresponding display interface, the single problem of the selectivity to improve the verifying of APP living body.
Description
Technical field
The present invention relates to identity validation technology field more particularly to a kind of face login method, device, computer equipment and
Storage medium.
Background technique
Currently, the APP of the downloading of mobile terminal is more and more as electronics technology develops, usual APP login mode is adopted
Logged in the mode or third party's account authorization login mode that account and password combine, with this come guarantee APP safety.
But combined by account and password or third party's account authorization login be easy to by it is non-I operation attack, current portions
APP uses fingerprint recognition mode to increase the safety of APP, but uses the login mode of fingerprint recognition, needs specific hardware
The support of equipment, and when user is entered using APP, mobile terminal can issue the reminder message for needing to carry out fingerprint authentication, user
Fingerprint authentication is carried out according to the reminder message of fingerprint authentication, user's finger dirt, grease and sweat are affected to unlock,
So that it cannot be guaranteed that the accuracy of verifying, therefore, improving the safety that APP is logged in becomes urgent problem to be solved.Part APP is adopted
Increase the safety of APP with recognition of face plus In vivo detection detection model, but verified by a kind of verifying form, is made
It is not high to obtain user's selectivity, and use under not applicable different scenes.
Summary of the invention
The embodiment of the present invention provides a kind of face login method, device, computer equipment and storage medium, current to solve
The single problem of the selectivity of APP living body verifying.
A kind of face login method, comprising:
User's logging request is obtained, includes login account and recognition code in user's logging request；
It is logged according to the login account and the recognition code, obtains login result；
If the login result is to login successfully, verifying acquisition corresponding with the login account is fed back to mobile terminal
Information；
Based on the corresponding target video stream of verifying acquisition real time information sampling, determination is corresponding with the login account
Target verification type calls In vivo detection interface corresponding with the target verification type to carry out living body to the target video stream
Detection obtains target In vivo detection result；
If the target In vivo detection result is In vivo detection success, target face is obtained from the target video stream
Image matches target facial image standard picture corresponding with the login account, obtains images match knot
Fruit；
If described image matching result is successful match, controls mobile terminal and show corresponding display interface.
A kind of face entering device, comprising:
Logging request obtains module, includes login account in user's logging request for obtaining user's logging request
And recognition code；
Login result obtains module, for being logged according to the login account and the recognition code, obtains and logs in
As a result；
Verifying acquisition data obtaining module, if for the login result be login successfully, to mobile terminal feedback with
The corresponding verifying of the login account acquires information；
Target In vivo detection result obtains module, for based on the corresponding target view of verifying acquisition real time information sampling
Frequency flows, and determines target verification type corresponding with the login account, calls living body inspection corresponding with the target verification type
It surveys interface and In vivo detection is carried out to the target video stream, obtain target In vivo detection result；
Images match result obtains module, if being In vivo detection success for the target In vivo detection result, from institute
Acquisition target facial image in target video stream is stated, by target facial image standard drawing corresponding with the login account
As being matched, images match result is obtained；
Display module controls mobile terminal and shows corresponding show if being successful match for described image matching result
Show interface.
A kind of computer equipment, including memory, processor and storage are in the memory and can be in the processing
The computer program run on device, the processor realize above-mentioned face login method when executing the computer program.
A kind of computer readable storage medium, the computer-readable recording medium storage have computer program, the meter
Calculation machine program realizes above-mentioned face login method when being executed by processor.
It is above-mentioned that a kind of face login method, device, computer equipment and storage medium are provided, user's logging request is obtained,
It is logged according to login account and recognition code, if login result is to login successfully, is fed back to mobile terminal and log in account
Number corresponding verifying acquires information, and avoiding login result is login failure, also needs to carry out In vivo detection and the step of face matches,
It reduces server-side and runs resource.Based on the corresponding target video stream of verifying acquisition real time information sampling, determining and login account pair
The target verification type answered calls In vivo detection interface corresponding with target verification type to carry out living body inspection to target video stream
It surveys, obtains target In vivo detection as a result, realizing and In vivo detection is carried out according to the preset Authentication-Type of user, reduction is illegally attacked
It hits, improves the selectivity of Authentication-Type, carry out living body verifying to be applicable under different scenes.If target In vivo detection result is living body
It detects successfully, then target facial image is obtained from target video stream, by target facial image mark corresponding with login account
Quasi- image is matched, if images match result is successful match, is controlled mobile terminal and is shown corresponding display interface, is improved
The safety that APP is logged in.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below by institute in the description to the embodiment of the present invention
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the invention
Example, for those of ordinary skill in the art, without any creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1 is the application environment schematic diagram of face login method in one embodiment of the invention；
Fig. 2 is the flow chart of face login method in one embodiment of the invention；
Fig. 3 is the flow chart of face login method in one embodiment of the invention；
Fig. 4 is the flow chart of face login method in one embodiment of the invention；
Fig. 5 is the flow chart of face login method in one embodiment of the invention；
Fig. 6 is the flow chart of face login method in one embodiment of the invention；
Fig. 7 is the flow chart of face login method in one embodiment of the invention；
Fig. 8 is the flow chart of face login method in one embodiment of the invention；
Fig. 9 is the functional block diagram of face entering device in one embodiment of the invention；
Figure 10 is a schematic diagram of computer equipment in one embodiment of the invention.
Specific embodiment
Below by the attached drawing in knot and the embodiment of the present invention, technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are some of the embodiments of the present invention, instead of all the embodiments.Based on this hair
Embodiment in bright, every other implementation obtained by those of ordinary skill in the art without making creative efforts
Example, shall fall within the protection scope of the present invention.
Face login method provided in an embodiment of the present invention, can be applicable in the application environment such as Fig. 1, the face login side
Method is applied in APP, the server-side network connection of mobile terminal and APP.When getting user's logging request, first according to login
Account and recognition code are logged in, if login successfully, carry out In vivo detection and people to the corresponding target video stream of user
Face matching is user and is living body so as to carry out APP register, improves the safety that APP is logged in.Wherein, mobile
Terminal can be, but not limited to various personal computers, laptop, smart phone, tablet computer and portable wearable set
It is standby.Server-side can be realized with the server-side cluster of the either multiple server-side compositions of independent server-side.
In one embodiment, as shown in Fig. 2, providing a kind of face login method, the service in Fig. 1 is applied in this way
It is illustrated, specifically comprises the following steps: for end
S10: obtaining user's logging request, includes login account and recognition code in user's logging request.
Wherein, user's logging request refers to the request for the access APP that user is triggered based on mobile terminal.Wherein, triggering side
The modes such as APP icon are including but not limited to clicked, touch or slided to formula.Login account refers to carries out APP in the terminal
The required account used when login authentication can be determined whether that user is allowed to access APP by login account.Recognition code refers to
Password corresponding with login account when APP login authentication is carried out in mobile terminal.
It specifically, include the corresponding application icon of multiple APP in mobile terminal, when user is based on shown by mobile terminal
When user's logging request of application icon triggering, for server-side to get user's logging request, user's logging request includes to log in
Account and recognition code, server-side can determine whether the user may have access to APP by login account and recognition code, to guarantee
The safety of APP.
S20: being logged according to login account and recognition code, obtains login result.
Wherein, login result refers to the result that server-side is verified according to login account and recognition code, wherein logs in
It as a result include logining successfully and login failure.
Specifically, when mobile terminal initiates logging request to server-side for the first time, login account and password is not transmitted, is serviced
End generates a pair of of public key and private key using RSA Algorithm.Public key is sent to client, and retains private key, client receives public key
Afterwards, recognition code is encrypted, mobile terminal initiates second of logging request to server-side, transmits login account and encrypted identification
Password.Server-side is decrypted ciphertext using the private key retained, obtains real password, and according to login account and identify close
Code is compared with account registered in database, and judges the accuracy of recognition code, to obtain login result.
Further, server-side first passes through Keywords matching algorithm and carries out account registered in login account and database
Matching, obtains the corresponding password of registered account of successful match, and recognition code password corresponding with registered account is carried out
Matching；If successful match, getting login result is to login successfully；If it fails to match, login failure prompting message is fed back.
More specifically, server-side is had not been obtained from database by Keywords matching algorithm to matching with login account
Registered account, then may the login account it is unregistered, then get login result be login failure, generate account error prompting
Information, and server-side is fed back to, so that user logs in or registers again according to prompting message；Or pass through keyword
The registered account to match with login account is got from database with algorithm, if recognition code and the password match lose
It loses, then getting login result is login failure, and generates password error prompting information, and feed back to server-side, so as to user
Recognition code is re-entered according to prompting message, to log in again.
S30: if login result is to login successfully, verifying acquisition letter corresponding with login account is fed back to mobile terminal
Breath.
Wherein, verifying acquisition information refers to the acquisition information determined according to login account, since different login accounts are corresponding
Authentication-Type it is different, then the verifying acquisition information generated is different.
Specifically, server-side is logged according to login account and recognition code, and login result is to login successfully, then basis
Login account searches preset target verification type corresponding with login account；Target verification type and default words art are combined,
It generates verifying acquisition information and feeds back to mobile terminal.Wherein, target verification type refers to corresponding with login account preset
Authentication-Type, including silent living body Authentication-Type and action live body Authentication-Type.Wherein, silent living body Authentication-Type refers to user
Only facial image need to be placed in pickup area, cooperated without user action, can judge that image to be processed is in target video stream
No is living body.Action live body Authentication-Type refers to that user needs to cooperate according to deliberate action instruction, such as opens one's mouth, shakes the head, blinks
Eye, to the left rotary head and head of turning right etc., correct user's cooperation is then living body, and user cooperates mistake to be then non-living body.
If target verification type is silent living body Authentication-Type, fed back to default words art as verifying acquisition information
Mobile terminal, wherein default words art can be " face is please placed in pickup area ", and user can acquire information according to verifying, be based on
Mobile terminal carries out corresponding operating.If target verification type is action live body Authentication-Type, deliberate action instruction is obtained, is preset
Action command include open one's mouth, shake the head, blinking, rotary head to the left and head of turning right etc., deliberate action corresponding with login account is referred to
It enables and default words art is used as verifying acquisition information to feed back to mobile terminal, for example, " face being please placed in pickup area, and is executed
Xx movement ", user can be based on mobile terminal, carry out corresponding operating according to verifying acquisition information.Wherein, deliberate action instruction refers to
User is based on the preset action command that can be used for living body verifying of mobile terminal.
S40: based on the corresponding target video stream of verifying acquisition real time information sampling, target corresponding with login account is determined
Authentication-Type calls In vivo detection interface corresponding with target verification type to carry out In vivo detection to target video stream, obtains mesh
Mark In vivo detection result.
Wherein, target video stream refers to that user cooperates according to verifying acquisition information, collected a series of images shape
At video flowing.In vivo detection refers to whether the biological characteristic judged in target video stream comes from lived individual.Living body inspection
It surveys interface and refers to the pre-configured interface that can be used for In vivo detection.Target In vivo detection result, which refers to, flows into target video
After row detection, the biological characteristic that is judged whether be living body result, wherein target In vivo detection result include In vivo detection at
Function, i.e., biological characteristic is living body in target video stream, further includes In vivo detection failure, i.e., biological characteristic is non-in target video stream
Living body.
Specifically, user can be based on mobile terminal, carry out corresponding operation according to verifying acquisition information, server-side, which obtains, claps
Take the photograph the corresponding target video stream that module acquires in real time, wherein the shooting module concretely camera built in mobile terminal.Clothes
After business end gets target video stream, corresponding In vivo detection interface is called to carry out In vivo detection to target video stream, obtains mesh
Mark In vivo detection result.
More specifically, the corresponding verifying acquisition information of different target Authentication-Type is different, acquisition of information is acquired according to verifying
To target video stream corresponding with target verification type, when target verification type is silent living body Authentication-Type, server-side tune
In vivo detection is carried out to target video stream with the In vivo detection model in the corresponding In vivo detection interface of silent living body Authentication-Type,
Obtain target In vivo detection result；When target verification type is action live body Authentication-Type, then calls and instructed with deliberate action
In vivo detection model in corresponding In vivo detection interface carries out In vivo detection to target video stream, obtains target In vivo detection knot
Fruit.Server-side acquires information by presetting Authentication-Type according to user, to mobile terminal feedback validation, to obtain target view
Frequency stream is video flowing corresponding with target verification type, by calling In vivo detection interface corresponding with target verification type to mesh
It marks video flowing and carries out In vivo detection, so that In vivo detection is more accurate, and is suitable for different application scene and carries out In vivo detection, lead to
Silent living body Authentication-Type and action live body Authentication-Type are crossed to improve the selectivity of the Authentication-Type of In vivo detection.
S50: if target In vivo detection result is In vivo detection success, target face figure is obtained from target video stream
Picture matches target facial image standard picture corresponding with login account, obtains images match result.
Wherein, target facial image refer to that candid photograph arrives for the matched user's face image of face.Images match result
Refer to the matching result of target facial image and standard picture, wherein images match result includes successful match, then target face
Image matches with standard picture, is that legitimate user carries out register；Further include that it fails to match, then target facial image and mark
Quasi- image mismatches, then illegal user carries out register.
Specifically, if target In vivo detection result is In vivo detection success, illustrate that biological characteristic is work in target video stream
Body, then server-side gets the facial image in target video stream by OpenCV tool, carries out positive face detection to facial image,
To get the face image of user as target facial image, to improve the matched accuracy of face.By target facial image
And the standard picture corresponding with login account of preparatory typing is matched in database, to get images match result.More
Specifically, server-side first extracts the corresponding characteristics of image of target facial image, calculates characteristics of image using cosine similarity algorithm
The similarity of feature corresponding with standard picture, if similarity is greater than preset threshold, the images match result got is
With success；If similarity is not more than preset threshold, the images match result got is that it fails to match.
S60: it if images match result is successful match, controls mobile terminal and shows corresponding display interface.
Specifically, if images match result is successful match, illustrate that the login account of user's input and recognition code log in
Success, which is living body and is legitimate user's operation, then server-side control mobile terminal shows the display interface of APP.
In step S10-S60, user's logging request is obtained, server-side is logged according to login account and recognition code,
If login result is to login successfully, verifying corresponding with login account is fed back to mobile terminal and acquires information, avoid logging in and tie
Fruit is login failure, also needs the step of carrying out In vivo detection and face matching, reduces server-side and run resource.It is acquired based on verifying
The corresponding target video stream of real time information sampling determines target verification type corresponding with login account, calling and target verification
The corresponding In vivo detection interface of type carries out In vivo detection to target video stream, obtains target In vivo detection as a result, realizing basis
The preset Authentication-Type of user carries out In vivo detection, reduces rogue attacks, improves the selectivity of Authentication-Type, to be applicable in not
With being verified under scene.If target In vivo detection result is In vivo detection success, server-side obtains target from target video stream
Facial image matches target facial image standard picture corresponding with login account, if images match result is
It with success, then controls mobile terminal and shows corresponding display interface, improve the safety that APP is logged in.
In one embodiment, as shown in figure 3, before step S10, i.e., before obtaining user's logging request, face is stepped on
Recording method also specifically comprises the following steps:
S101: obtaining account registration request, includes login account, log-in password and user information in account registration request.
Wherein, log-in password refers to the password inputted when account registration, subsequent to can be used to judge when user APP is logged in
Whether recognition code is correct.
Specifically, when user carries out APP login, user needs to carry out in advance account registration operation, which provides an account
Number registered port obtains the account registration request that mobile terminal is sent by the registered port, includes stepping in account registration request
Record account, log-in password and user information, wherein include name, age, occupation, annual income and contact method in user information
Deng.
S102: account registration is carried out according to login account, log-in password and user information, user is determined based on user information
Grade, and obtain Authentication-Type corresponding with user gradation and select information.
Specifically, it is close according to login account, registration after server-side gets login account, log-in password and user information
Code and user information carry out account registration, are logged in so as to subsequent according to login account and recognition code.After account registration, by
It needs to carry out In vivo detection and face matching in APP login setting, therefore, user gradation is first determined according to user information,
Corresponding Authentication-Type selection information is determined according to user gradation, wherein Authentication-Type selection information refers to and user gradation
The information of the corresponding Authentication-Type that can be chosen, such as comprising silent living body Authentication-Type and action live body Authentication-Type.It can
To understand ground, user gradation is higher, and selectable is the higher living body Authentication-Type of safety coefficient, conversely, user gradation is lower,
Each living body Authentication-Type may be selected.For example, the safety coefficient of silent living body Authentication-Type is lower, individual part living body verifies class
The safety coefficient of type is medium, and the safety coefficient of multiple combinative movement living body Authentication-Types is higher etc..
S103: obtaining target verification type and standard picture of the mobile terminal based on Authentication-Type selection information feedback, will
Login account, log-in password, target verification type and standard picture associated storage are into database.
Wherein, target verification type refers to that user is based on mobile terminal, and the verifying of information feedback is selected according to Authentication-Type
Type.Standard picture refers to the face image of user's typing, can be used for subsequent face matching, it is determined whether carry out for legitimate user
APP register.
Specifically, target verification type of the mobile terminal based on Authentication-Type selection information feedback is obtained, if target verification
Type is action live body Authentication-Type, also needs to determine that deliberate action instruction is shaken the head that is, from opening one's mouth, blink, rotary head to the left and to the right
At least one action command chosen in rotary head, if the non-selected action command of user, is defaulted as stochastic instruction, i.e. target verification
When type is action live body Authentication-Type, from opening one's mouth, shake the head, blink, randomly selected in rotary head to the left and to the right rotary head one or
Multiple action commands are instructed as deliberate action.When logging in due to the APP, need to carry out face matching, therefore also need to obtain
The standard picture of user, wherein user's specification image can be the image of front shooting, and login account, log-in password, target are tested
Type and standard picture associated storage are demonstrate,proved into database.
In step S101-S103, server-side obtains account registration request, is believed according to login account, log-in password and user
Breath carries out account registration, carries out APP register according to login account so as to subsequent.User gradation is determined based on user information,
And obtain Authentication-Type corresponding with user gradation and select information, realize the selectable Authentication-Type of different user grade not
Together.Target verification type and standard picture of the mobile terminal based on Authentication-Type selection information feedback are obtained, subsequent basis is convenient for
Target verification type carries out living body verifying, carries out face matching according to standard picture.
In one embodiment, as shown in figure 4, being stepped on according to login account and recognition code after step S20
Record, after obtaining login result, face login method also specifically comprises the following steps:
S201: if login result is login failure, login failure number is updated；
Wherein, login failure number refers to user according to the number of login account and recognition code login failure.
Specifically, if according to login account and recognition code login failure, login failure information is updated, so as to based on login
The frequency of failure either reminds operation so that whether subsequent determining server-side needs to conduct the locking operations to login account.
S202: if login failure number is greater than preset times threshold value, login account is carried out within the default locking time limit
Locking.
Wherein, preset times threshold value, which refers to, preset is used to determine whether to need to conduct the locking operations to login account
Threshold value.Preferably, preset times threshold value is 5 times.
Specifically, server-side is by the way that login failure number to be compared with preset times threshold value, if login failure number
Greater than preset times threshold value, then login account is locked within the default locking time limit, to improve the safety of APP login,
User is avoided to accidentally touch or overdue situations such as hitting.Wherein, presetting the locking time limit refers to and preset locks to login account
The fixed time limit can not carry out login behaviour according to login account and recognition code for example, locking in one day to login account
Make.
S203: if login failure number is not more than preset times threshold value, stepping on for inquiry is generated based on login failure number
Record failure prompting message.
Specifically, if login failure number is greater than preset times threshold value, server-side is based on the generation of login failure number and looks into
Login failure prompting message is fed back to mobile terminal by the login failure prompting message of inquiry, which also wraps
Including can login times, wherein login times refer to the number determined according to login times and login failure number is preset.For example,
Preset times threshold value is 5 times, and login failure number is 1 time, then login failure prompting message is that " you are good, your login account
Or recognition code is incorrect, there are also 4 chances, login accounts to be locked for you ".
In step S201-S203, if login result is login failure, login failure number is updated；If login failure number
Greater than preset times threshold value, then login account is locked within the default locking time limit, improves the safety that APP is logged in.If
Login failure number is not more than preset times threshold value, then the login failure that server-side generates inquiry based on login failure number is reminded
Information logs in convenient for user according to login failure prompting message again.
In one embodiment, as shown in figure 5, in step S40, i.e., based on the corresponding target of verifying acquisition real time information sampling
Video flowing determines target verification type corresponding with login account, calls In vivo detection interface corresponding with target verification type
In vivo detection is carried out to target video stream, obtains target In vivo detection as a result, specifically comprising the following steps:
S41: based on verifying acquisition information, Face datection is carried out to the original image of shooting module acquisition in real time, if original
Facial image is detected in image, then obtains the target video stream of preset time period.
Wherein, original image refers to the image acquired in real time by shooting module.Facial image refers to the figure comprising face
Picture.Preset time period refers to the period of preset acquisition In vivo detection.
Specifically, after server-side acquires information to mobile terminal feedback validation, user carries out according to verifying acquisition information
Corresponding operation, server-side then carry out Face datection to the original image of shooting module acquisition in real time, OpenCV specifically can be used
Tool carries out Face datection to original image, to judge whether the original image in pickup area includes face, if original image
Not comprising facial image, then step S41 is continued to execute；If original image includes facial image, from detecting that facial image opens
Begin, obtain the target video stream in preset time period, for example, obtaining the 10 seconds target video stream comprising facial image.
S42: enhancing processing is carried out to frame images to be recognized each in target video stream using ACE algorithm, is obtained to be processed
Image.
Wherein, images to be recognized refers to through the collected image comprising face of shooting module.Image to be processed refers to
The image of enhancing processing is carried out to images to be recognized.
Specifically, target video stream includes at least two frame images to be recognized.Server-side from the target video stream got,
Each frame images to be recognized is extracted according to timing, image increasing is carried out to each images to be recognized of target video stream by ACE algorithm
Strength reason, obtains image to be processed, to improve the precision of subsequent In vivo detection, and extracts each frame figure to be identified according to timing
Picture prevents midway from switching people.Wherein, ACE (Automatic Color Enhancement, auto color enhance algorithm), due to
The biological characteristic of images to be recognized is living body in target video stream, in dynamic, in order to keep the details of the image got more clear
The accuracy rate of Chu, In vivo detection is more accurate, therefore joined ACE algorithm and carry out enhancing processing to images to be recognized.Wherein, ACE
The principle of algorithm is that piece image is divided into two parts: first is that low frequency part, can pass through low-pass filtering (the smooth mould of image
Paste) it obtains；Second is that high frequency section, can subtract low frequency part by original image and obtain.And the target of algorithm is that enhancing represents details
High frequency section, i.e., to high frequency section multiplied by some yield value, the image that then recombination is enhanced is image to be processed.
S43: determining corresponding target verification type according to login account, is examined using living body corresponding with target verification type
Interface is surveyed, In vivo detection is carried out to image to be processed, obtains target In vivo detection result.
Specifically, the incidence relation of login account Yu target verification type is stored in database.It is looked by login account
Database is looked for, target verification type corresponding with login account is obtained, is connect using In vivo detection corresponding with target verification type
Mouthful In vivo detection is carried out to image to be processed, i.e. target verification type is silent living body Authentication-Type, then uses and silent living body
The corresponding In vivo detection interface of Authentication-Type carries out In vivo detection to image to be processed, obtains target In vivo detection result；Target
Authentication-Type is action live body Authentication-Type, then using In vivo detection interface corresponding with action live body Authentication-Type to be processed
Image carries out In vivo detection, obtains target In vivo detection result.
In step S41-S43, server-side is based on verifying acquisition information, carries out in real time to the original image of shooting module acquisition
Face datection obtains the target video stream of preset time period, avoids subsequent living body if detecting facial image in original image
Facial image is not included when detection in target video stream.Using ACE algorithm to frame images to be recognized each in target video stream into
Row enhancing processing, obtains image to be processed, improves the accuracy of subsequent In vivo detection.Server-side is determined according to login account and is corresponded to
Target verification type In vivo detection is carried out to image to be processed using In vivo detection interface corresponding with target verification type,
It realizes that different Authentication-Types correspond to different In vivo detection interfaces, improves the accuracy of In vivo detection.
In one embodiment, target verification type includes silent living body Authentication-Type and action live body Authentication-Type.
As shown in fig. 6, In vivo detection interface corresponding with target verification type is used, to figure to be processed in step S43
As carrying out In vivo detection, target In vivo detection is obtained as a result, specifically comprising the following steps:
S4311: it if target verification type is silent living body Authentication-Type, obtains corresponding quiet with silent living body Authentication-Type
Silent In vivo detection model.
Wherein, silent In vivo detection model refers to the preparatory trained model for carrying out true man's living body verification.
Specifically, server-side first obtains preset target verification type corresponding with login account, if target verification
Type is silent living body Authentication-Type, then obtains silent In vivo detection model corresponding with silent living body Authentication-Type, specifically may be used
Using existing silent In vivo detection model, usually silence In vivo detection model can provide api interface, by calling api interface
Silent In vivo detection model is got, carries out In vivo detection by obtaining In vivo detection model corresponding with target verification type,
So that target In vivo detection result is more accurate.
S4312: In vivo detection is carried out to image to be processed using silent In vivo detection model, obtains each image to be processed
Corresponding single frame detection result.
Wherein, single frame detection result refers to the testing result by silent In vivo detection model to each image to be processed.
Specifically, each image to be processed is input in silent In vivo detection model, passes through silent In vivo detection model
Image to be processed is identified, acquisition is corresponding with each image to be processed to refer to score value, if being greater than score value threshold with reference to score value
Value gets single frame detection result corresponding with image to be processed then as In vivo detection success；If being not more than score value with reference to score value
Threshold value gets single frame detection result corresponding with image to be processed then as In vivo detection failure.Wherein, refer to reference to score value logical
It crosses silent In vivo detection model to identify image to be processed, the score value exported.Point threshold, which refers to, rule of thumb to be set
For determining whether image to be processed is that In vivo detection is successfully worth.
S4313: if all single frame detection results are In vivo detection success, the target In vivo detection result obtained is to live
Physical examination is surveyed successfully.
Specifically, server-side obtains the corresponding single frame detection of each image to be processed as a result, if each single frame detection result
It is In vivo detection success, then target In vivo detection result is In vivo detection success；At least one single frame detection result if it exists
For In vivo detection failure, then target In vivo detection result is In vivo detection failure.
In step S4311-S4313, if target verification type is silent living body Authentication-Type, server-side is obtained and silence
The corresponding silent In vivo detection model of living body Authentication-Type, realizes the In vivo detection model of different target verification type uses not
Together, In vivo detection success rate is improved.Server-side carries out In vivo detection to image to be processed using silent In vivo detection model, obtains
The corresponding single frame detection of each image to be processed obtains as a result, if all single frame detection results are In vivo detection success
Target In vivo detection result is In vivo detection success, avoids the attack of human face photo and face prosthese mask etc., improves safety.
Alternatively,
S4321: if target verification type be action live body Authentication-Type, it is determined that it is corresponding with login account at least one
Deliberate action instruction, obtains movement In vivo detection model corresponding with the instruction of at least one deliberate action.
Specifically, if server-side judges that preset Authentication-Type corresponding with login account is action live experience card
Type then further obtains preset at least one deliberate action instruction corresponding with login account, it is possible to understand that ground, in advance
If action command can be individual part instruction, it is also possible to multiple action commands, can also be that random action instructs, if with
Family setting is random action instruction, then can be combined as deliberate action according to randomly selecting movement in deliberate action or acting
Instruction.Server-side is instructed according at least one deliberate action, obtains movement living body corresponding with the instruction of at least one deliberate action
Detection model.
Further, different deliberate actions instruct corresponding movement In vivo detection model different.Carrying out action live physical examination
When surveying model training, the sample under the different conditions of server-side deliberate action instruction is inputted, for example, action command is to open one's mouth to move
Make, obtains a large number of users and shut up, part mouth sample corresponding with the action states such as open one's mouth a little, and correspondingly marked, then pass through
Model is trained, to get the movement In vivo detection model that can export the corresponding probability such as shut up, part mouth a little and open one's mouth,
In the present embodiment, model includes but is not limited to SVM classifier and convolutional neural networks (Convolutional Neural
Networks, CNN) model etc..Follow-up service end can differentiate this by the action states such as shut up, part mouth a little and open one's mouth of output
Whether user is living body.
S4322: In vivo detection is carried out to image to be processed using movement In vivo detection model, obtains each image to be processed
Corresponding motion detection result.
Wherein, motion detection result refer to by act In vivo detection model image to be processed is identified, determine with
The result of the corresponding action state of image to be processed.
Specifically, each image to be processed is input in movement In vivo detection model by server-side, passes through action live physical examination
It surveys model to identify image to be processed, obtains the corresponding output probability of each image to be processed, determined according to output probability
The corresponding action state of each image to be processed is as motion detection as a result, exporting each action state it is to be appreciated that obtaining
Corresponding probability, using the corresponding action state of maximum probability as motion detection result corresponding with image to be processed.For example, with
The corresponding default verification condition of login account is to open one's mouth, and is identified, is obtained to each image to be processed by motion detection model
The output probability with image to be processed is taken, it is 3 percent and that the probability such as shut up, which is 95 percent, parts the probability of mouth a little
The probability opened one's mouth is 2 percent, then action state corresponding with image to be located is to shut up, i.e., will be shut up as motion detection
As a result.
S4323: if the corresponding motion detection result of at least two frames image to be processed is not identical, the target living body obtained is examined
Result is surveyed as In vivo detection success.
Specifically, server-side obtain the corresponding motion detection of each image to be processed as a result, it is i.e. determining with it is each to be processed
The corresponding action state of image judges whether the corresponding action state of each figure to be processed is identical；If at least two frames are to be processed
The corresponding action state of image is not identical, then the target In vivo detection result obtained is In vivo detection success；If each to be processed
The corresponding action state of image is identical, then the target In vivo detection result obtained is In vivo detection failure.It should be noted that In
If after the corresponding action state of at least two frames image to be processed is not identical, being judged whether it is according to each action state and being met often
The complete movement of rule.→ mouth is parted a little → for example, from shutting up to open one's mouth.
Further, each image to be processed carries time identifier, each to treat place using movement In vivo detection model
Reason image is when being identified, according to timing judge each image to be processed whether be whether be consecutive image, if consecutive image,
And the corresponding motion detection result of at least two frames image to be processed is not identical, then the target In vivo detection result obtained is living body inspection
It surveys successfully.
In step S4321-S43224, if target verification type is action live body Authentication-Type, it is determined that with login account
Corresponding at least one deliberate action instruction, obtains movement In vivo detection model corresponding with the instruction of at least one deliberate action,
Realize different deliberate action instructions, used movement In vivo detection model is different.By instructing respective action with deliberate action
In vivo detection model carries out In vivo detection, improves In vivo detection accuracy rate.Using movement In vivo detection model to image to be processed
In vivo detection is carried out, obtains the corresponding motion detection of each image to be processed as a result, if at least two frames image to be processed is corresponding
Motion detection result is not identical, then the target In vivo detection result obtained is In vivo detection success, to prevent in In vivo detection
The deceptive practices such as photos and videos editing mode improve the reliability and safety of In vivo detection.
In step S4311-S4313 and step S4321-S43224, different target verification types corresponds to different living bodies
Interface is detected, i.e. the respectively different In vivo detection model of silence living body Authentication-Type and action live body Authentication-Type carries out living body inspection
It surveys, improves In vivo detection accuracy rate.By providing silent In vivo detection type and movement two kinds of Authentication-Types of In vivo detection type,
To improve the Authentication-Type of user's selection, and different Authentication-Types can be applied to different application scene, for example, silent living body verifying
Type is applicable to meeting, public arena and formal occasion etc..
Further, it since different scenes need different Authentication-Types, obtains the Authentication-Type that mobile terminal is sent and cuts
Request is changed, Authentication-Type switching request includes modification Authentication-Type；Target verification type is cut according to Authentication-Type switching request
Shift to modification Authentication-Type.Specifically, it when target verification type is action live body Authentication-Type, if user needs to have a meeting, needs
Switch target verification type, then send Authentication-Type switching request to server-side, include in the next emerging switching request of verifying repairs
Change type as silent living body Authentication-Type, server-side is according to Authentication-Type switching request, by target verification type from movement living body
Authentication-Type switches to silent living body Authentication-Type.By this step, it can be achieved that switching Authentication-Type in real time according to user demand,
To be preferably applied for different scenes.
In one embodiment, as shown in fig. 7, face login method also specifically comprises the following steps:
S501:, will if target In vivo detection result is In vivo detection failure or images match result is that it fails to match
Random verification code, which is sent to, logs in the corresponding mobile terminal of the associated phone number of account number.
Wherein, random verification code refers to by verifying the identifying code that generates at random of code generator, and concretely 6 digits are tested
Demonstrate,prove code.
It specifically, then may be by malicious attack or image when target physical examination result living is that In vivo detection fails
It is that it fails to match with result, then may not be that legitimate user carries out APP register, server-side is determined and stepped on according to login account
The corresponding phone number of account is recorded, random verification code is generated by verifying code generator, random verification code is sent to cell-phone number
The corresponding mobile terminal of code, to determine whether to carry out APP register for malicious attack or legitimate user.
S502: obtaining the login authentication code that mobile terminal is sent, if login authentication code and random verification code successful match,
Control mobile terminal shows corresponding display interface.
Wherein, login authentication code refers to that mobile terminal is sent to the identifying code of server-side according to random verification code.
Specifically, server-side obtain mobile terminal send login authentication code, using matching algorithm by login authentication code with
Random verification code is matched, and matching result is obtained.If login authentication code and random verification code are successful match, movement is controlled
Terminal shows corresponding display interface.If login authentication code is with random verification code, it fails to match, right within the default locking time limit
Login account is locked.Wherein, matching algorithm includes but is not limited to DFA algorithm, AC automatic machine and KMP (Knuth-
Morris-Pratt, Nu Te-Mo Lisi-Alexandre Desplat) algorithm.
In step S501-S502, if target In vivo detection result is In vivo detection failure or images match result is
With failure, then random verification code is sent to and logs in the corresponding mobile terminal of the associated phone number of account number, obtain mobile terminal
The login authentication code of transmission controls mobile terminal and shows corresponding show if login authentication code and random verification code successful match
Show interface, is verified with realizing by random verification code, avoid malicious attack.
In one embodiment, as shown in figure 8, after step S60, if being successful match in images match result,
After control mobile terminal shows corresponding display interface, face login method also specifically comprises the following steps:
S601: carrying out operation monitoring to display interface in real time, obtains the non-operating time.
Wherein, the dwell time that the non-operating time refers to that user is operated in display interface last time is current to system
The period of time.
Specifically, server-side can call operate () function to determine whether not carrying out to display interface for a long time corresponding
Operation；If so, obtaining the dwell time and current time in system that last time is operated, worked as according to dwell time and system
The preceding time determines the non-operating time.For example, dwell time be 1 point five minutes, the current time in system be 1 point 15 minutes, then not
Operating time is ten minutes.Display interface is monitored by monitoring function, to determine whether user does not operate for a long time, if
User does not operate for a long time, to avoid occupying server-side resource, can carry out screen locking operation.
S602: if the non-operating time reaches preset time threshold, screen locking operation is carried out to display interface.
Wherein, preset time threshold refer to it is preset need to display interface into line-locked value, for example, if user
The non-operating time reaches ten minutes, then carries out screen locking operation, i.e. preset time threshold is ten minutes.
Specifically, the non-operating time is obtained in real time, will be compared with preset time threshold the non-operating time, if not operating
Time reaches preset time threshold, illustrates that user in display interface does not carry out corresponding operation for a long time, then to display interface into
Row screen locking operation.For example, the non-operating time is ten minutes in step S601 shown in embodiment, preset time threshold is ten minutes,
Then on one point 15 points to display interface carry out screen locking operation, reduce server-side run resource.
S603: obtaining interface operation request, and interface operation request includes the operating time.
Wherein, when the operating time refers to that mobile terminal sends interface operation request to server-side, display interface carries out screen locking
Time to the current time in system time.For example, 1 point carries out screen locking operation to display interface in 15 minutes, and sent out to server-side
When interface operation being sent to request, the current time in system be 1 point 16 minutes, then the operating time be one minute.
Specifically, after display interface screen locking, when user needs again to operate display interface, then based on mobile whole
It holds to server-side and sends interface operation request, include the operating time in interface operation request.
S604: if the operating time within the default screen locking time, controls mobile terminal and shows corresponding display interface.
Wherein, presetting the screen locking time is after preset display interface carries out screen locking, without verification operation again when
Between.For example, user sends interface operation request within two minutes after display interface screen locking, then without re-starting verifying behaviour
Make, corresponding display interface can be directly displayed.
Specifically, after server-side gets the operating time, the operating time is compared with the default screen locking time, if operation
Time within the default screen locking time, then requests control mobile terminal to show corresponding display interface according to interface operation.For example, behaviour
Making the time is one minute, and presetting the screen locking time is two minutes, then is requested according to interface operation, and control mobile terminal is shown accordingly
Display interface.
S605: if the operating time not within the default screen locking time, to mobile terminal send log in prompting message, execute to
Mobile terminal feeds back the step of verifying acquisition information corresponding with login account.
Wherein, the prompting message for needing to re-start verifying that prompting message is directed to mobile terminal transmission is logged in.For example,
" due to not operated for a long time, please logging in again ".
Specifically, it if the operating time is not within the default screen locking time, is sent to mobile terminal and logs in prompting message, and executed
Verifying corresponding with login account is fed back to mobile terminal and acquires information, is i.e. execution step S30, is tested so that user re-starts
Card.For example, presetting the screen locking time is two minutes if the operating time is five minutes, is then sent to mobile terminal and logs in prompting message,
Execute step S30.
In step S601-S605, operation monitoring is carried out to display interface in real time, the non-operating time is obtained, if do not operate
Between reach preset time threshold, then to display interface carry out screen locking operation, with reduce server-side operation resource.Obtain interface operation
Request, interface operation request include the operating time, if the operating time within the default screen locking time, controls mobile terminal and shows phase
The display interface answered avoids user from repeating to verify.If the operating time not within the default screen locking time, is sent out to mobile terminal
Login prompting message is sent, executes to mobile terminal and feeds back verifying acquisition information corresponding with login account, to improve safety.
It should be understood that the size of the serial number of each step is not meant that the order of the execution order in above-described embodiment, each process
Execution sequence should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present invention constitutes any limit
It is fixed.
In one embodiment, a kind of face entering device is provided, which steps on face in above-described embodiment
Recording method corresponds.As shown in figure 9, the face entering device includes that logging request obtains module 10, login result obtains mould
Block 20, verifying acquisition data obtaining module 30, target In vivo detection result obtains module 40, images match result obtains module 50
With display module 60.Detailed description are as follows for each functional module:
Logging request obtains module 10, for obtaining user's logging request, in user's logging request comprising login account and
Recognition code.
Login result obtains module 20, for being logged according to login account and recognition code, obtains login result.
Verifying acquisition data obtaining module 30 feeds back and steps on to mobile terminal if being to login successfully for login result
It records the corresponding verifying of account and acquires information.
Target In vivo detection result obtains module 40, for based on the corresponding target video of verifying acquisition real time information sampling
Stream determines target verification type corresponding with login account, calls In vivo detection interface corresponding with target verification type to mesh
It marks video flowing and carries out In vivo detection, obtain target In vivo detection result.
Images match result obtains module 50, if being In vivo detection success for target In vivo detection result, from target
Target facial image is obtained in video flowing, and target facial image standard picture corresponding with login account is matched, is obtained
Take images match result.
Display module 60 controls mobile terminal and shows corresponding display if being successful match for images match result
Interface.
In one embodiment, before logging request obtains module 10, face entering device includes that account registration request obtains
Take unit, Authentication-Type selection information acquisition unit and data storage cell.
Account registration request acquiring unit, for obtaining account registration request, include in account registration request login account,
Log-in password and user information.
Authentication-Type selects information acquisition unit, for carrying out account according to login account, log-in password and user information
Registration determines user gradation based on user information, and obtains Authentication-Type corresponding with user gradation and select information.
Data storage cell, for obtain mobile terminal based on Authentication-Type selection information feedback target verification type and
Standard picture, by login account, log-in password, target verification type and standard picture associated storage into database.
In one embodiment, after login result obtains module 20, face entering device further includes login failure number
Updating unit, login account lock cell and login failure prompting message feedback unit.
Login failure number updating unit updates login failure number if being login failure for login result.
Login account lock cell, if being greater than preset times threshold value for login failure number, in the default locking time limit
It is interior that login account is locked.
Login failure prompting message feedback unit is based on if being not more than preset times threshold value for login failure number
Login failure number generates the login failure prompting message of inquiry.
In one embodiment, target In vivo detection result obtains module 40, including target video stream acquiring unit, to be processed
Image acquisition unit and target In vivo detection result acquiring unit.
Target video stream acquiring unit, for acquiring information based on verifying, in real time to the original image of shooting module acquisition
It carries out Face datection and obtains the target video stream of preset time period if detecting facial image in original image.
Image acquisition unit to be processed, for being carried out using ACE algorithm to frame images to be recognized each in target video stream
Enhancing processing, obtains image to be processed.
Target In vivo detection result acquiring unit is used for determining corresponding target verification type according to login account
In vivo detection interface corresponding with target verification type carries out In vivo detection to image to be processed, obtains target In vivo detection knot
Fruit.
In one embodiment, target verification type includes silent living body Authentication-Type and action live body Authentication-Type.
Target In vivo detection result acquiring unit, including silent In vivo detection model obtain subelement, single frame detection result
It obtains subelement and first object In vivo detection result obtains subelement, alternatively, target In vivo detection result acquiring unit includes
It acts In vivo detection model and obtains subelement, motion detection result acquisition subelement and the second target In vivo detection result acquisition
Unit.
Silent In vivo detection model obtains subelement, if being silent living body Authentication-Type for target verification type, obtains
Silence In vivo detection model corresponding with silent living body Authentication-Type.
Single frame detection result obtains subelement, for carrying out living body inspection to image to be processed using silent In vivo detection model
It surveys, obtains the corresponding single frame detection result of each image to be processed.
First object In vivo detection result obtains subelement, if for all single frame detection results be In vivo detection at
Function, then the target In vivo detection result obtained are In vivo detection success.
Alternatively,
It acts In vivo detection model and obtains subelement, if being action live body Authentication-Type for target verification type, really
Fixed at least one deliberate action instruction corresponding with login account, obtains action live corresponding with the instruction of at least one deliberate action
Body detection model.
Motion detection result obtains subelement, for carrying out living body inspection to image to be processed using movement In vivo detection model
It surveys, obtains the corresponding motion detection result of each image to be processed.
Second target In vivo detection result obtains subelement, if being used for the corresponding motion detection of at least two frames image to be processed
As a result not identical, then the target In vivo detection result obtained is In vivo detection success.
In one embodiment, face entering device further includes that random verification code transmission unit and the display of the first display interface are single
Member.
Random verification code transmission unit, if being In vivo detection failure or images match for target In vivo detection result
As a result for it fails to match, then random verification code is sent to and logs in the corresponding mobile terminal of the associated phone number of account number.
First display interface display unit, for obtain mobile terminal transmission login authentication code, if login authentication code with
Random verification code successful match then controls mobile terminal and shows corresponding display interface.
In one embodiment, after display module 60, face entering device includes non-operating time acquiring unit, screen locking
Operating unit, interface operation request unit, the second display interface display unit and authentication unit.
Non- operating time acquiring unit obtains the non-operating time for carrying out operation monitoring to display interface in real time.
Screen locking operating unit carries out screen locking behaviour to display interface if reaching preset time threshold for the non-operating time
Make.
Interface operation request unit, for obtaining interface operation request, interface operation request includes the operating time.
Second display interface display unit, if it is aobvious to control mobile terminal for the operating time within the default screen locking time
Show corresponding display interface.
Authentication unit, if the operating time not within the default screen locking time, sends to mobile terminal and logs in prompting message, hold
The step of row feeds back verifying acquisition information corresponding with login account to mobile terminal.
Specific about face entering device limits the restriction that may refer to above for face login method, herein not
It repeats again.Modules in above-mentioned face entering device can be fully or partially through software, hardware and its group and to realize.On
Stating each module can be embedded in the form of hardware or independently of in the processor in computer equipment, can also store in a software form
In memory in computer equipment, the corresponding operation of the above modules is executed in order to which processor calls.
In one embodiment, a kind of computer equipment is provided, which can be server-side, internal junction
Composition can be as shown in Figure 10.The computer equipment include by system bus connect processor, memory, network interface and
Database.Wherein, the processor of the computer equipment is for providing calculating and control ability.The memory packet of the computer equipment
Include non-volatile memory medium, built-in storage.The non-volatile memory medium is stored with operating system, computer program and data
Library.The built-in storage provides environment for the operation of operating system and computer program in non-volatile memory medium.The calculating
The database of machine equipment is used to store generation or the data obtained etc. during face login method, for example, storage In vivo detection
Interface and standard picture etc..The network interface of the computer equipment is used to communicate with external terminal by network connection.It should
To realize a kind of face login method when computer program is executed by processor.
In one embodiment, a kind of computer equipment is provided, including memory, processor and storage are on a memory simultaneously
The computer program that can be run on a processor, processor realize face login side in above-described embodiment when executing computer program
The step of method, for example, step S10 shown in Fig. 2 to step S60, alternatively, step as shown in Figures 3 to 8.Alternatively, processor
The function that each module in above-described embodiment in face entering device is realized when executing computer program, for example, module shown in Fig. 9
10 to module 60 function.To avoid repeating, details are not described herein again.
In one embodiment, a kind of computer readable storage medium is provided, computer program, computer are stored thereon with
Face login method in above method embodiment is realized when program is executed by processor, for example, step S10 shown in Fig. 2 is extremely walked
Rapid S60, alternatively, step as shown in Figures 3 to 8.Alternatively, the computer program realizes above-described embodiment when being executed by processor
The function of each module in middle face entering device, for example, function of the module 10 shown in Fig. 9 to module 60.To avoid repeating, herein
It repeats no more.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, computer program can be stored in a non-volatile computer and can be read
In storage medium, the computer program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein, the application
To any reference of memory, storage, database or other media used in provided each embodiment, may each comprise non-
Volatibility and/or volatile memory.Nonvolatile memory may include read-only memory (ROM), programming ROM (PROM),
Electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM) or flash memory.Volatile memory may include arbitrary access
Memory (RAM) or external cache.By way of illustration and not limitation, RAM is available in many forms, such as static
RAM (SRAM), dynamic ram (DRAM), synchronous dram (SDRAM), double data rate sdram (DDRSDRAM), enhanced SDRAM
(ESDRAM), synchronization link (Synchlink) DRAM (SLDRAM), memory bus (RambuS) directly RAM (RDRAM), straight
Connect memory bus dynamic ram (DRDRAM) and memory bus dynamic ram (RDRAM) etc..
It is apparent to those skilled in the art that for convenience of description and succinctly, only with above-mentioned each function
Can unit, module division progress for example, in practical application, can according to need and by above-mentioned function distribution by different
Functional unit, module are completed, i.e., the internal structure of device are divided into different functional unit or module, to complete above description
All or part of function.
The above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although with reference to the foregoing embodiments
Invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each implementation
Technical solution documented by example is modified or equivalent replacement of some of the technical features；And these modification or
Replacement, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution should all include
Within protection scope of the present invention.
Claims (10)
1. a kind of face login method characterized by comprising
User's logging request is obtained, includes login account and recognition code in user's logging request；
It is logged according to the login account and the recognition code, obtains login result；
If the login result is to login successfully, verifying acquisition letter corresponding with the login account is fed back to mobile terminal
Breath；
Based on the corresponding target video stream of verifying acquisition real time information sampling, target corresponding with the login account is determined
Authentication-Type calls In vivo detection interface corresponding with the target verification type to carry out living body inspection to the target video stream
It surveys, obtains target In vivo detection result；
If the target In vivo detection result is In vivo detection success, target face figure is obtained from the target video stream
Picture matches target facial image standard picture corresponding with the login account, obtains images match result；
If described image matching result is successful match, controls mobile terminal and show corresponding display interface.
2. face login method as described in claim 1, which is characterized in that before acquisition user's logging request, institute
Stating face login method includes:
Account registration request is obtained, includes login account, log-in password and user information in the account registration request；
Account registration is carried out according to the login account, the log-in password and the user information, is based on the user information
It determines user gradation, and obtains Authentication-Type corresponding with the user gradation and select information；
Target verification type and standard picture of the mobile terminal based on Authentication-Type selection information feedback are obtained, is stepped on described
Account, the log-in password, the target verification type and the standard picture associated storage are recorded into database.
3. face login method as described in claim 1, which is characterized in that described according to the login account and the knowledge
Other password is logged in, after obtaining login result, the face login method further include:
If the login result is login failure, login failure number is updated；
If the login failure number is greater than preset times threshold value, the login account is locked within the default locking time limit
It is fixed；
If the login failure number is not more than preset times threshold value, the login of inquiry is generated based on the login failure number
Failure prompting message.
4. face login method as described in claim 1, which is characterized in that described to be adopted in real time based on verifying acquisition information
Collect corresponding target video stream, determine target verification type corresponding with the login account, calls and the target verification class
The corresponding In vivo detection interface of type carries out In vivo detection to the target video stream, obtains target In vivo detection result, comprising:
Information is acquired based on the verifying, Face datection is carried out to the original image of shooting module acquisition in real time, if described original
Facial image is detected in image, then obtains the target video stream of preset time period；
Enhancing processing is carried out to each frame images to be recognized in the target video stream using ACE algorithm, obtains image to be processed；
Corresponding target verification type is determined according to the login account, is examined using living body corresponding with the target verification type
Interface is surveyed, In vivo detection is carried out to the image to be processed, obtains target In vivo detection result.
5. face login method as claimed in claim 4, which is characterized in that the target verification type includes that silent living body is tested
Demonstrate,prove type and action live body Authentication-Type；
It is described to use In vivo detection interface corresponding with the target verification type, living body inspection is carried out to the image to be processed
It surveys, obtains target In vivo detection result, comprising:
If the target verification type is silent living body Authentication-Type, silence corresponding with the silence living body Authentication-Type is obtained
In vivo detection model；
In vivo detection is carried out to the image to be processed using silent In vivo detection model, obtains each image pair to be processed
The single frame detection result answered；
If all single frame detection results are In vivo detection success, the target In vivo detection result obtained is In vivo detection
Success；
Alternatively,
If the target verification type is action live body Authentication-Type, it is determined that corresponding with the login account at least one is pre-
If action command, movement In vivo detection model corresponding with the instruction of deliberate action described at least one is obtained；
In vivo detection is carried out to the image to be processed using the movement In vivo detection model, obtains each figure to be processed
As corresponding motion detection result；
If the corresponding motion detection result of image to be processed described at least two frames is not identical, the target In vivo detection result obtained
For In vivo detection success.
6. face login method as described in claim 1, which is characterized in that the face login method further include:
If the target In vivo detection result is In vivo detection failure or described image matching result is that it fails to match, will
Random verification code is sent to the corresponding mobile terminal of the associated phone number of the login account number；
The login authentication code that mobile terminal is sent is obtained, if the login authentication code and the random verification code successful match,
Control mobile terminal shows corresponding display interface.
7. face login method as described in claim 1, which is characterized in that if being matching in the described image matching result
Success then controls after mobile terminal shows corresponding display interface, and the face login method includes:
Operation monitoring is carried out to the display interface in real time, obtains the non-operating time；
If the non-operating time reaches preset time threshold, screen locking operation is carried out to the display interface；
Interface operation request is obtained, the interface operation request includes the operating time；
If the operating time within the default screen locking time, controls mobile terminal and shows corresponding display interface；
If the operating time not within the default screen locking time, sends to mobile terminal and logs in prompting message, institute is executed
State the step of feeding back verifying acquisition information corresponding with the login account to mobile terminal.
8. a kind of face entering device characterized by comprising
Logging request obtains module, includes login account and knowledge in user's logging request for obtaining user's logging request
Other password；
Login result obtains module, for being logged according to the login account and the recognition code, obtains login result；
Verifying acquisition data obtaining module, if for the login result be login successfully, to mobile terminal feedback with it is described
The corresponding verifying of login account acquires information；
Target In vivo detection result obtains module, for based on the corresponding target video of verifying acquisition real time information sampling
Stream determines target verification type corresponding with the login account, calls In vivo detection corresponding with the target verification type
Interface carries out In vivo detection to the target video stream, obtains target In vivo detection result；
Images match result obtains module, if being In vivo detection success for the target In vivo detection result, from the mesh
Mark video flowing in obtain target facial image, by target facial image standard picture corresponding with the login account into
Row matching, obtains images match result；
Display module controls mobile terminal and shows corresponding display circle if being successful match for described image matching result
Face.
9. a kind of computer equipment, including memory, processor and storage are in the memory and can be in the processor
The computer program of upper operation, which is characterized in that the processor realized when executing the computer program as claim 1 to
Any one of 7 face login methods.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In realization face login method as described in any one of claim 1 to 7 when the computer program is executed by processor.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910662143.1A CN110532744A (en) | 2019-07-22 | 2019-07-22 | Face login method, device, computer equipment and storage medium |
| PCT/CN2020/093354 WO2021012791A1 (en) | 2019-07-22 | 2020-05-29 | Face login method, apparatus, computer device and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910662143.1A CN110532744A (en) | 2019-07-22 | 2019-07-22 | Face login method, device, computer equipment and storage medium |
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| Publication Number | Publication Date |
|---|---|
| CN110532744A true CN110532744A (en) | 2019-12-03 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910662143.1A Pending CN110532744A (en) | 2019-07-22 | 2019-07-22 | Face login method, device, computer equipment and storage medium |
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| Country | Link |
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| WO (1) | WO2021012791A1 (en) |
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Application publication date: 20191203 |