CN108629280B - Face recognition method and mobile terminal - Google Patents
Face recognition method and mobile terminal Download PDFInfo
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- CN108629280B CN108629280B CN201810258608.2A CN201810258608A CN108629280B CN 108629280 B CN108629280 B CN 108629280B CN 201810258608 A CN201810258608 A CN 201810258608A CN 108629280 B CN108629280 B CN 108629280B
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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
- G06V40/168—Feature extraction; Face representation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/96—Management of image or video recognition tasks
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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
Abstract
The embodiment of the invention provides a face recognition method and a mobile terminal, wherein the face recognition method is applied to the mobile terminal and comprises the following steps: when a face recognition request of a user is received, scene information is obtained; determining the number of collected face characteristic points corresponding to the face recognition request according to the scene information; and carrying out face recognition according to the collected number of the face characteristic points. By the embodiment of the invention, the face recognition speed can be flexibly controlled, and the face recognition efficiency is improved.
Description
Technical Field
The invention relates to the field of mobile terminals, in particular to a face recognition method and a mobile terminal.
Background
In order to protect the use safety of the mobile terminal and the personal privacy of the user, the mobile terminal can perform face recognition on the user through a face recognition function, and the face recognition mode of the mobile terminal can be fingerprint verification, iris verification, face recognition and the like.
In the existing face recognition method, a matching threshold is usually set, and when the matching result of the acquired face features and the face features stored in advance reaches the matching threshold, it is determined that the face recognition is passed. However, the existing face recognition method mainly focuses on how to improve the face recognition accuracy, and does not consider the influence of the face recognition speed on the face recognition efficiency.
Disclosure of Invention
The embodiment of the invention aims to provide a face recognition method and a mobile terminal, so as to flexibly control the face recognition speed and improve the face recognition efficiency.
To achieve the above object, the embodiment of the present invention is implemented as follows:
in a first aspect, an embodiment of the present invention provides a face recognition method, applied to a mobile terminal, including:
when a face recognition request of a user is received, scene information is obtained;
determining the number of collected face characteristic points corresponding to the face recognition request according to the scene information;
and carrying out face recognition according to the collected number of the face characteristic points.
In a second aspect, an embodiment of the present invention provides a mobile terminal, including:
the system comprises an acquisition unit, a processing unit and a display unit, wherein the acquisition unit is used for acquiring scene information when receiving a face recognition request of a user;
the first determining unit is used for determining the collection number of the face characteristic points corresponding to the face recognition request according to the scene information;
and the face recognition unit is used for carrying out face recognition according to the collected number of the face characteristic points.
In a third aspect, an embodiment of the present invention provides a mobile terminal, including: a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the face recognition method as described in the first aspect above.
In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, and when being executed by a processor, the computer program implements the steps of the face recognition method according to the first aspect.
In the embodiment of the invention, when a face recognition request of a user is received, scene information is obtained, the number of collected face characteristic points corresponding to the face recognition request is determined according to the scene information, and the face recognition is carried out according to the number of collected face characteristic points. Because the number of collected face characteristic points is a parameter influencing the face recognition speed, the face characteristic point collection number during face recognition is determined according to the scene information, the effect of flexibly controlling the face recognition speed in different scenes can be achieved, and the face recognition efficiency is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a face recognition method according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a face recognition method according to another embodiment of the present invention;
fig. 3 is a schematic diagram illustrating a module composition of a mobile terminal according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a hardware structure of a mobile terminal implementing various embodiments of the present invention.
Detailed Description
In order to make those skilled in the art better understand the technical solution of the present invention, the technical solution in the embodiment of the present invention will be clearly and completely described below with reference to the drawings in the embodiment of the present invention, and it is obvious that the described embodiment is only a part of the embodiment of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention provides a face recognition method, a mobile terminal and a computer readable storage medium, which are used for flexibly controlling the face recognition speed and improving the face recognition efficiency. The face recognition method is applied to the mobile terminal side and can be executed by the mobile terminal, and the mobile terminal provided by the embodiment of the invention comprises but is not limited to an intelligent terminal with a face recognition function, such as a mobile phone, a tablet computer, a computer and wearable equipment.
Fig. 1 is a schematic flow chart of a face recognition method according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps:
102, acquiring scene information when receiving a face recognition request of a user;
104, determining the collection quantity of the face characteristic points corresponding to the face recognition request according to the scene information;
and step 106, carrying out face recognition according to the collected number of the face characteristic points.
In the embodiment of the invention, when a face recognition request of a user is received, scene information is obtained, the number of collected face characteristic points corresponding to the face recognition request is determined according to the scene information, and the face recognition is carried out according to the number of collected face characteristic points. Because the number of collected face characteristic points is a parameter influencing the face recognition speed, the face characteristic point collection number during face recognition is determined according to the scene information, the effect of flexibly controlling the face recognition speed in different scenes can be achieved, and the face recognition efficiency is improved.
The face recognition process involved in this embodiment is: the method comprises the steps of collecting a face image of a user, extracting face features from the collected face image, determining that face recognition passes when the matching degree of the extracted face features and the face features stored in advance reaches a certain threshold value, and otherwise, determining that the face recognition does not pass.
In step 102, a face recognition request of the user is received, where the mobile terminal determines to obtain the face recognition request of the user and displays a face recognition interface when receiving a payment operation of the user, and may also determine to obtain the face recognition request of the user and perform face recognition on the user to unlock the mobile terminal if a face image of the user is detected when the mobile terminal is in a screen locking state.
In this embodiment, the scene information includes scene category information and mobile terminal operation information; in step 104, determining the number of collected face feature points corresponding to the face recognition request according to the scene information, specifically:
(1) determining the scene type of face recognition according to the scene type information; wherein the scene category comprises a payment category and a non-payment category;
(2) selecting a reference grade corresponding to the face recognition request from a plurality of preset grades according to the scene type; the collection quantity of the face characteristic points corresponding to each grade is different;
(3) determining a target grade corresponding to the face recognition request in a plurality of grades according to the mobile terminal operation information and the reference grade; the number of collected face characteristic points corresponding to the target grade is greater than or less than that corresponding to the reference grade;
(4) and taking the number of collected face characteristic points corresponding to the target grade as the number of collected face characteristic points corresponding to the face recognition request.
In the action (1), the mobile terminal determines the scene type of the face recognition according to the scene type information, and the scene type includes a payment type and a non-payment type. The mobile terminal can detect the type of an application program requesting face recognition, determine that the scene type is a payment type if the application program is a payment type application program, and determine that the scene type is a non-payment type if the application program is a non-payment type application program.
Multiple levels are preset in the mobile terminal, each level corresponds to different face characteristic point collection quantities, for example, a first level, a second level, a third level and a fourth level are preset, and the face characteristic point collection quantities corresponding to the first level, the second level, the third level and the fourth level are gradually increased. In the above operation (2), the mobile terminal selects a reference level corresponding to the face recognition request from a plurality of preset levels according to the scene type. Specifically, the payment type scene corresponds to a reference grade, and the non-payment type scene corresponds to a reference grade, so that the mobile terminal selects the reference grade corresponding to the face recognition request from a plurality of preset grades according to the scene type. The reference level corresponding to the payment scene and the reference level corresponding to the non-payment scene may be set by the mobile terminal by default or may be set by the user in advance. It should be noted that the face feature point collection number corresponding to each of the multiple levels can ensure the accuracy of face recognition.
After the reference grade is determined, the mobile terminal also determines a target grade according to the mobile terminal operation information and the reference grade, wherein the target grade and the reference grade are not the same grade. In one case, if the scene category is the payment category, the mobile terminal may determine the target level by any one of the following manners:
(41) the mobile terminal operation information comprises network information connected with the mobile terminal, and according to the comparison result of the network information and the preset network information, the grade with the corresponding face characteristic point collection quantity larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as a target grade;
(42) the mobile terminal operation information comprises user identity authentication records of the mobile terminal in a preset time period, and according to the user identity authentication records, selecting a grade with the corresponding face characteristic point acquisition quantity larger or smaller than the face characteristic point acquisition quantity corresponding to the reference grade from a plurality of grades as a target grade;
(43) the mobile terminal operation information comprises account information of a payee corresponding to the face recognition request, and a grade with the corresponding face characteristic point collection quantity larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades as a target grade according to the account information of the payee;
(44) the mobile terminal operation information comprises contact information of a goods receiver corresponding to the face recognition request, and according to a comparison result of the contact information of the goods receiver and contact information of a mobile terminal owner, a grade with the corresponding face characteristic point collection quantity larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as a target grade.
In the action (41), the network information connected to the mobile terminal includes at least one of WIFI (wireless fidelity) information and base station information, where the WIFI information at least includes a WIFI identifier, and the base station information at least includes a base station identifier. For example, if the mobile terminal is connected to a WIFI network, the network information connected to the mobile terminal includes an identifier of the WIFI, and if the mobile terminal uses internet traffic provided by an operator, the network information connected to the mobile terminal includes an identifier of the base station. The mobile terminal is internally prestored with a WIFI white list and a base station white list, a WIFI identifier which is safe relative to the mobile terminal is recorded in the WIFI white list, a base station identifier which is safe relative to the mobile terminal is recorded in the base station white list, the mobile terminal compares the WIFI identifier with the WIFI identifier in the WIFI white list, or compares the base station identifier with the base station identifier in the base station white list, if the WIFI identifier connected with the mobile terminal is determined to exist in the WIFI white list according to a comparison result, or the base station identifier connected with the mobile terminal is determined to exist in the base station white list, a network connected with the mobile terminal is considered to be safe, and the mobile terminal selects a grade with the number of face characteristic point collections smaller than the number of face characteristic point collections corresponding to a reference grade from a plurality of grades as a target grade so as to improve the speed of face recognition. On the contrary, if it is determined that the identifier of the WIFI connected to the mobile terminal does not exist in the WIFI white list, or it is determined that the identifier of the base station connected to the mobile terminal does not exist in the base station white list, it is considered that the network connected to the mobile terminal is dangerous, and the mobile terminal selects, as a target level, a level in which the number of collected face characteristic points is greater than the number of collected face characteristic points corresponding to the reference level, so as to ensure the safety of face recognition.
In this embodiment, the WIFI white list may be established in the following manner. The method comprises the steps of determining a WIFI network with a password, the connection frequency of the mobile terminal exceeds a certain frequency, recording an identifier (such as a name or an ID) of the WIFI network, and obtaining a WIFI white list, wherein the WIFI network with the connection frequency exceeding the certain frequency of the mobile terminal is generally family WIFI or company WIFI of a user, and the WIFI network with the password is recorded in the WIFI white list, so that potential threat of insecurity of the WIFI network without the password to face identification can be prevented. When the identifier of the WIFI connected with the mobile terminal is determined not to exist in the WIFI white list, the fact that the WIFI connected with the mobile terminal is a WIFI network which is rarely connected in a public place or a WIFI network without a password is indicated, the WIFI network connected with the mobile terminal is considered to be dangerous, and the grade with the number of the collected face characteristic points which is larger than the number of the collected face characteristic points which are corresponding to the reference grade is selected from the multiple grades to serve as a target grade, so that the safety of face recognition is guaranteed.
In this embodiment, the white list of the base station may be established in the following manner. The method comprises the steps of determining a base station of which the residence time of the mobile terminal exceeds a certain time, recording an identifier (such as a name or an ID) of the base station to obtain a white list of the base station, wherein the mobile terminal can identify the identifier of the resident base station, and the base station of which the residence time exceeds the certain time is usually a base station near a user home or a base station near a company. When the identification of the base station connected with the mobile terminal is determined not to exist in the white list of the base station, the base station connected with the mobile terminal is indicated to be a base station in an uncommon geographical area, and at the moment, a grade with the corresponding face characteristic point acquisition quantity being larger than that corresponding to the reference grade is selected from a plurality of grades to serve as a target grade, so that the safety of face recognition is guaranteed.
In the act (42), the mobile terminal operation information includes a user authentication record of the mobile terminal in a preset time period, the user authentication record of the mobile terminal in the preset time period (for example, in the time period before 30 seconds from the current time) is obtained, and a level, in which the corresponding face feature point collection number is greater than or less than the face feature point collection number corresponding to the reference level, is selected from the multiple levels as the target level according to the user authentication record. For example, if the mobile terminal has records of successful fingerprint verification, successful pupil verification or successful face recognition within a preset time period, the current environment of the mobile terminal is considered to be safe, a grade with the corresponding number of collected face characteristic points smaller than the number of collected face characteristic points corresponding to the reference grade is selected as a target grade to improve the face recognition speed, otherwise, if the mobile terminal has records of failed fingerprint verification, failed pupil verification or failed face recognition within the preset time period, or if the number of failed face recognition exceeds a certain number within the preset time period, the current environment of the mobile terminal is considered to be dangerous, and if the mobile terminal has conditions of malicious unlocking or malicious payment, a grade with the corresponding number of collected face characteristic points larger than the number of collected face characteristic points corresponding to the reference grade is selected as a target grade, so as to ensure the safety of face recognition.
In one embodiment, when a user performs offline payment in a physical store such as a supermarket, the user performs fingerprint unlocking firstly, then performs payment through face recognition, and when the mobile terminal performs face recognition, the mobile terminal detects that a record of successful fingerprint verification exists within one minute, determines that the current environment is safe, selects a grade with the corresponding number of face characteristic point acquisitions being smaller than the number of face characteristic point acquisitions corresponding to a reference grade as a target grade, and improves the face recognition speed.
In the above operation (43), the scene type is a payment type, the operation information of the mobile terminal includes account information of a payee corresponding to the face recognition request, and a level, in which the number of collected face feature points corresponding to the plurality of levels is greater than or less than the number of collected face feature points corresponding to the reference level, is selected as the target level according to the account information of the payee. For example, if the account of the payee is an account of a stranger (a person who is not in the friend list), or the friend adding time of the account of the payee is less than a certain time (for example, one day), in order to prevent a behavior of malicious transfer, a level with the corresponding face characteristic point collection number being greater than the face characteristic point collection number corresponding to the reference level is selected as a target level, so as to ensure the safety of face recognition. For another example, if the account of the payee is a friend account, or the account of the payee is an account with a history transfer frequency exceeding a certain frequency, the payment condition is considered to be safe, and a grade with the corresponding face characteristic point acquisition quantity smaller than the face characteristic point acquisition quantity corresponding to the reference grade is selected as a target grade, so that the face recognition speed is improved.
In the above action (44), the scene type is a payment type, the operation information of the mobile terminal includes contact information of the consignee corresponding to the face recognition request, and a level, in which the corresponding face feature point collection number is greater than or less than the face feature point collection number corresponding to the reference level, is selected from the multiple levels as a target level according to the contact information of the consignee. For example, if the contact information of the consignee is the contact information of the owner of the mobile terminal, the payment condition is considered to be safe, the grade with the corresponding face characteristic point collection quantity being smaller than the face characteristic point collection quantity corresponding to the reference grade is selected as the target grade to improve the face recognition speed, and if the contact information of the consignee is not the contact information of the owner of the mobile terminal, the payment condition is considered to have a certain potential safety hazard, and the grade with the corresponding face characteristic point collection quantity being larger than the face characteristic point collection quantity corresponding to the reference grade is selected as the target grade to ensure the safety of the face recognition. The contact information includes name, address, mobile phone number, etc.
In one case, if the scene category is a non-payment category, the target level may be determined by any one of the following methods:
(45) the mobile terminal operation information comprises network information connected with the mobile terminal, and according to the comparison result of the network information and the preset network information, the grade with the corresponding face characteristic point collection quantity larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as a target grade;
(46) the mobile terminal operation information comprises user identity authentication records of the mobile terminal in a preset time period, and according to the user identity authentication records, selecting a grade with the corresponding face characteristic point acquisition quantity larger or smaller than the face characteristic point acquisition quantity corresponding to the reference grade from a plurality of grades as a target grade;
the specific processes of acts (45) and (46) may refer to the specific processes of acts (41) and (42) described above, and are not repeated here.
In the embodiment of the present invention, in a payment scenario, the target level may be determined in any one of the manners (41) to (44) described above, and in the embodiment of the present invention, in a non-payment scenario, the target level may be determined in the above-described action (45) or (46), so that different scenarios are adapted to determine corresponding target levels, and the flexibility of face recognition is improved.
Considering that the face recognition parameters further include a face comparison passing threshold, in this embodiment of the application, before performing face recognition by using the collected number of the face feature points, the method further includes: and determining a face comparison passing threshold corresponding to the face identification request according to the scene information. Correspondingly, the face recognition is carried out according to the collection number of the face characteristic points, and the method comprises the following steps: and carrying out face recognition by using the collected number of the face characteristic points and the face comparison through a threshold value.
Wherein, according to the scene information, determining a face comparison passing threshold corresponding to the face recognition request comprises:
(a) determining the scene type of face recognition according to the scene type information; wherein the scene category comprises a payment category and a non-payment category;
(b) selecting a reference grade corresponding to the face recognition request from a plurality of preset grades according to the scene type; wherein, the face comparison corresponding to each grade is different through a threshold value;
(c) determining a target grade corresponding to the face recognition request in a plurality of grades according to the mobile terminal operation information and the reference grade; the face comparison passing threshold corresponding to the target level is greater than or less than the face comparison passing threshold corresponding to the reference level;
(d) and comparing the face corresponding to the target grade with a passing threshold value to serve as a face comparison passing threshold value corresponding to the face identification request.
When the scene type is a payment type, determining a target level corresponding to the face recognition request in a plurality of levels according to the mobile terminal operation information and the reference level, specifically comprising:
(c1) the mobile terminal operation information comprises network information connected with the mobile terminal, and according to the comparison result of the network information and the preset network information, the grade with the corresponding face comparison passing threshold value larger or smaller than the face comparison passing threshold value corresponding to the reference grade is selected from the multiple grades to serve as the target grade;
(c2) the mobile terminal operation information comprises user identity authentication records of the mobile terminal in a preset time period, and according to the user identity authentication records, selecting a grade with a corresponding face comparison passing threshold value larger or smaller than a face comparison passing threshold value corresponding to a reference grade from a plurality of grades as a target grade;
(c3) the mobile terminal operation information comprises account information of a payee corresponding to the face recognition request, and according to the account information of the payee, a grade of which the corresponding face comparison passing threshold is greater than or less than the face comparison passing threshold corresponding to the reference grade is selected from a plurality of grades to serve as a target grade;
(c4) the mobile terminal operation information comprises contact information of a goods receiver corresponding to the face recognition request, and according to a comparison result of the contact information of the goods receiver and contact information of a mobile terminal owner, a grade with a corresponding face comparison passing threshold value larger or smaller than a face comparison passing threshold value corresponding to the reference grade is selected from the multiple grades to serve as a target grade.
When the scene type is a non-payment type, determining a target level corresponding to the face recognition request in a plurality of levels according to the mobile terminal operation information and the reference level, wherein the method specifically comprises the following steps:
(c5) the mobile terminal operation information comprises network information connected with the mobile terminal, and according to the comparison result of the network information and the preset network information, the grade with the corresponding face comparison passing threshold value larger or smaller than the face comparison passing threshold value corresponding to the reference grade is selected from the multiple grades to serve as the target grade;
(c6) the mobile terminal operation information comprises user identity authentication records of the mobile terminal in a preset time period, and according to the user identity authentication records, selecting a grade with a corresponding face comparison passing threshold value larger or smaller than a face comparison passing threshold value corresponding to a reference grade from a plurality of grades as a target grade;
as can be seen, the specific process of determining that the face comparison corresponding to the face recognition request passes the threshold according to the scene information is similar to that in step 104, and is not repeated here.
Fig. 2 is a schematic flow chart of a face recognition method according to another embodiment of the present invention, as shown in fig. 2, the method includes the following steps:
and step 208, performing face recognition according to the collected number of the face characteristic points and the comparison of the face and the face passing threshold.
By the method in fig. 2, the number of the collected face feature points and the face comparison passing threshold are determined according to the scene information, so that the beneficial effects of balancing the speed and accuracy of face recognition under different scenes can be achieved, and the purposes of improving the efficiency, reliability and safety of face recognition under different scenes can be achieved.
Based on the face recognition method in the foregoing embodiment, an embodiment of the present invention provides a mobile terminal, configured to execute the face recognition method, and fig. 3 is a schematic diagram illustrating module components of the mobile terminal according to an embodiment of the present invention, as shown in fig. 3, where the mobile terminal includes:
an obtaining unit 31, configured to obtain scene information when receiving a face recognition request of a user;
a first determining unit 32, configured to determine, according to the scene information, a number of collected face feature points corresponding to the face recognition request;
and a face recognition unit 33, configured to perform face recognition according to the collected number of the face feature points.
Optionally, the scene information includes scene category information and mobile terminal operation information; the first determining unit 32 is specifically configured to:
determining the scene type of face recognition according to the scene type information; wherein the scene categories include a paid category and a non-paid category;
selecting a reference grade corresponding to the face recognition request from a plurality of preset grades according to the scene category; the collection quantity of the face characteristic points corresponding to each grade is different;
determining a target grade corresponding to the face recognition request in the plurality of grades according to the mobile terminal operation information and the reference grade; the number of collected face characteristic points corresponding to the target grade is greater than or less than the number of collected face characteristic points corresponding to the reference grade;
and taking the number of collected face characteristic points corresponding to the target grade as the number of collected face characteristic points corresponding to the face recognition request.
Optionally, the scene category is a payment class; the first determining unit 32 is specifically configured to implement any one of the following manners:
the mobile terminal operation information comprises network information connected with the mobile terminal, and according to a comparison result of the network information and preset network information, a grade with the corresponding face characteristic point collection quantity larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade;
the mobile terminal operation information comprises user identity authentication records of the mobile terminal in a preset time period, and according to the user identity authentication records, selecting a grade with the corresponding face characteristic point acquisition quantity being greater than or less than the face characteristic point acquisition quantity corresponding to the reference grade from the plurality of grades as the target grade;
the mobile terminal operation information comprises account information of a payee corresponding to the face recognition request, and a grade with the corresponding face characteristic point collection quantity larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade according to the account information of the payee;
the mobile terminal operation information comprises contact information of a consignee corresponding to the face recognition request, and according to a comparison result of the contact information of the consignee and contact information of a mobile terminal owner, a grade with the corresponding face characteristic point collection quantity being larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade.
Optionally, the scene category is a non-payment category; the first determining unit 32 is specifically configured to implement any one of the following manners:
the mobile terminal operation information comprises network information connected with the mobile terminal, and according to a comparison result of the network information and preset network information, a grade with the corresponding face characteristic point collection quantity larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade;
the mobile terminal operation information comprises user identity authentication records of the mobile terminal in a preset time period, and according to the user identity authentication records, the grade with the corresponding face characteristic point acquisition quantity larger or smaller than the face characteristic point acquisition quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade.
Optionally, the apparatus further comprises:
the second determining unit is used for determining a face comparison passing threshold corresponding to the face recognition request according to the scene information before carrying out face recognition according to the collected number of the face characteristic points;
the face recognition unit 33 is specifically configured to:
and carrying out face recognition according to the collected number of the face characteristic points and the comparison of the faces and a threshold value.
In the embodiment of the invention, when a face recognition request of a user is received, scene information is obtained, the number of collected face characteristic points corresponding to the face recognition request is determined according to the scene information, and the face recognition is carried out according to the number of collected face characteristic points. Because the number of collected face characteristic points is a parameter influencing the face recognition speed, the face characteristic point collection number during face recognition is determined according to the scene information, the effect of flexibly controlling the face recognition speed in different scenes can be achieved, and the face recognition efficiency is improved.
Fig. 4 is a schematic diagram of a hardware structure of a mobile terminal for implementing various embodiments of the present invention, and as shown in fig. 4, the mobile terminal 800 includes, but is not limited to: a radio frequency unit 801, a network module 802, an audio output unit 803, an input unit 804, a sensor 805, a display unit 806, a user input unit 807, an interface unit 808, a memory 809, a processor 810, and a power supply 811. Those skilled in the art will appreciate that the mobile terminal architecture shown in fig. 4 is not intended to be limiting of mobile terminals, and that a mobile terminal may include more or fewer components than shown, or some components may be combined, or a different arrangement of components. In the embodiment of the present invention, the mobile terminal includes, but is not limited to, a mobile phone, a tablet computer, a notebook computer, a palm computer, a vehicle-mounted terminal, a wearable device, a pedometer, and the like.
The memory 809 stores a computer program, and when the computer program is executed by the processor 810, the following processes can be implemented:
when a face recognition request of a user is received, scene information is obtained;
determining the number of collected face characteristic points corresponding to the face recognition request according to the scene information;
and carrying out face recognition according to the collected number of the face characteristic points.
Optionally, when the computer program is executed by the processor 810, the context information includes context category information and mobile terminal operation information;
determining the number of collected face characteristic points corresponding to the face recognition request according to the scene information, wherein the number of collected face characteristic points comprises the following steps:
determining the scene type of face recognition according to the scene type information; wherein the scene categories include a paid category and a non-paid category;
selecting a reference grade corresponding to the face recognition request from a plurality of preset grades according to the scene category; the collection quantity of the face characteristic points corresponding to each grade is different;
determining a target grade corresponding to the face recognition request in the plurality of grades according to the mobile terminal operation information and the reference grade; the number of collected face characteristic points corresponding to the target grade is greater than or less than the number of collected face characteristic points corresponding to the reference grade;
and taking the number of collected face characteristic points corresponding to the target grade as the number of collected face characteristic points corresponding to the face recognition request.
Optionally, the computer program, when executed by the processor 810, is for the scenario category to be a payment category; determining a target grade corresponding to the face recognition request in the plurality of grades according to the mobile terminal operation information and the reference grade, wherein the target grade comprises any one of the following modes:
the mobile terminal operation information comprises network information connected with the mobile terminal, and according to a comparison result of the network information and preset network information, a grade with the corresponding face characteristic point collection quantity larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade;
the mobile terminal operation information comprises user identity authentication records of the mobile terminal in a preset time period, and according to the user identity authentication records, selecting a grade with the corresponding face characteristic point acquisition quantity being greater than or less than the face characteristic point acquisition quantity corresponding to the reference grade from the plurality of grades as the target grade;
the mobile terminal operation information comprises account information of a payee corresponding to the face recognition request, and a grade with the corresponding face characteristic point collection quantity larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade according to the account information of the payee;
the mobile terminal operation information comprises contact information of a consignee corresponding to the face recognition request, and according to a comparison result of the contact information of the consignee and contact information of a mobile terminal owner, a grade with the corresponding face characteristic point collection quantity being larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade.
Optionally, the computer program, when executed by the processor 810, is of a non-payment class; determining a target grade corresponding to the face recognition request in the plurality of grades according to the mobile terminal operation information and the reference grade, wherein the target grade comprises any one of the following modes:
the mobile terminal operation information comprises network information connected with the mobile terminal, and according to a comparison result of the network information and preset network information, a grade with the corresponding face characteristic point collection quantity larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade;
the mobile terminal operation information comprises user identity authentication records of the mobile terminal in a preset time period, and according to the user identity authentication records, the grade with the corresponding face characteristic point acquisition quantity larger or smaller than the face characteristic point acquisition quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade.
Optionally, the computer program, when executed by the processor 810, further comprises, before performing face recognition with the number of collected face feature points:
determining a face comparison passing threshold corresponding to the face identification request according to the scene information;
and performing face recognition according to the collected number of the face characteristic points, wherein the face recognition comprises the following steps:
and carrying out face recognition according to the collected number of the face characteristic points and the comparison of the faces and a threshold value.
In the embodiment of the invention, when a face recognition request of a user is received, scene information is obtained, the number of collected face characteristic points corresponding to the face recognition request is determined according to the scene information, and the face recognition is carried out according to the number of collected face characteristic points. Because the number of collected face characteristic points is a parameter influencing the face recognition speed, the face characteristic point collection number during face recognition is determined according to the scene information, the effect of flexibly controlling the face recognition speed in different scenes can be achieved, and the face recognition efficiency is improved.
It should be understood that, in the embodiment of the present invention, the radio frequency unit 801 may be used for receiving and sending signals during a message sending and receiving process or a call process, and specifically, receives downlink data from a base station and then processes the received downlink data to the processor 810; in addition, the uplink data is transmitted to the base station. In general, radio frequency unit 801 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, and the like. Further, the radio frequency unit 801 can also communicate with a network and other devices through a wireless communication system.
The mobile terminal provides the user with wireless broadband internet access through the network module 802, such as helping the user send and receive e-mails, browse webpages, access streaming media, and the like.
The audio output unit 803 may convert audio data received by the radio frequency unit 801 or the network module 802 or stored in the memory 809 into an audio signal and output as sound. Also, the audio output unit 803 may also provide audio output related to a specific function performed by the mobile terminal 800 (e.g., a call signal reception sound, a message reception sound, etc.). The audio output unit 803 includes a speaker, a buzzer, a receiver, and the like.
The input unit 804 is used for receiving an audio or video signal. The input Unit 804 may include a Graphics Processing Unit (GPU) 8041 and a microphone 8042, and the Graphics processor 8041 processes image data of a still picture or video obtained by an image capturing device (such as a camera) in a video capturing mode or an image capturing mode. The processed image frames may be displayed on the display unit 806. The image frames processed by the graphics processor 8041 may be stored in the memory 809 (or other storage medium) or transmitted via the radio frequency unit 801 or the network module 802. The microphone 8042 can receive sound, and can process such sound into audio data. The processed audio data may be converted into a format output transmittable to a mobile communication base station via the radio frequency unit 801 in case of a phone call mode.
The mobile terminal 800 also includes at least one sensor 805, such as light sensors, motion sensors, and other sensors. Specifically, the light sensor includes an ambient light sensor that can adjust the brightness of the display panel 8061 according to the brightness of ambient light, and a proximity sensor that can turn off the display panel 8061 and/or the backlight when the mobile terminal 800 moves to the ear. As one of the motion sensors, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally three axes), detect the magnitude and direction of gravity when stationary, and can be used to identify the posture of the mobile terminal (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), and vibration identification related functions (such as pedometer, tapping); the sensors 805 may also include fingerprint sensors, pressure sensors, iris sensors, molecular sensors, gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc., which are not described in detail herein.
The display unit 806 is used to display information input by the user or information provided to the user. The Display unit 806 may include a Display panel 8061, and the Display panel 8061 may be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), or the like.
The user input unit 807 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the mobile terminal. Specifically, the user input unit 807 includes a touch panel 8071 and other input devices 8072. The touch panel 8071, also referred to as a touch screen, may collect touch operations by a user on or near the touch panel 8071 (e.g., operations by a user on or near the touch panel 8071 using a finger, a stylus, or any other suitable object or accessory). The touch panel 8071 may include two portions of a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to the processor 810, receives a command from the processor 810, and executes the command. In addition, the touch panel 8071 can be implemented by various types such as a resistive type, a capacitive type, an infrared ray, and a surface acoustic wave. In addition to the touch panel 8071, the user input unit 807 can include other input devices 8072. In particular, other input devices 8072 may include, but are not limited to, a physical keyboard, function keys (e.g., volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which are not described in detail herein.
Further, the touch panel 8071 can be overlaid on the display panel 8061, and when the touch panel 8071 detects a touch operation on or near the touch panel 8071, the touch operation is transmitted to the processor 810 to determine the type of the touch event, and then the processor 810 provides a corresponding visual output on the display panel 8061 according to the type of the touch event. Although the touch panel 8071 and the display panel 8061 are shown in fig. 4 as two separate components to implement the input and output functions of the mobile terminal, in some embodiments, the touch panel 8071 and the display panel 8061 may be integrated to implement the input and output functions of the mobile terminal, which is not limited herein.
The interface unit 808 is an interface through which an external device is connected to the mobile terminal 800. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, an audio input/output (I/O) port, a video I/O port, an earphone port, and the like. The interface unit 808 may be used to receive input (e.g., data information, power, etc.) from external devices and transmit the received input to one or more elements within the mobile terminal 800 or may be used to transmit data between the mobile terminal 800 and external devices.
The memory 809 may be used to store software programs as well as various data. The memory 809 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, the memory 809 can include high speed random access memory, and can also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.
The processor 810 is a control center of the mobile terminal, connects various parts of the entire mobile terminal using various interfaces and lines, and performs various functions of the mobile terminal and processes data by running or executing software programs and/or modules stored in the memory 809 and calling data stored in the memory 809, thereby integrally monitoring the mobile terminal. Processor 810 may include one or more processing units; preferably, the processor 810 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into processor 810.
The mobile terminal 800 may also include a power supply 811 (e.g., a battery) for powering the various components, and the power supply 811 may be logically coupled to the processor 810 via a power management system that may be used to manage charging, discharging, and power consumption.
In addition, the mobile terminal 800 includes some functional modules that are not shown, and thus, are not described in detail herein.
Preferably, an embodiment of the present invention further provides a mobile terminal, which includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, where the computer program, when executed by the processor, implements each process of the above-mentioned embodiment of the face recognition method, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here.
Further, an embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the above-mentioned embodiment of the face recognition method, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (6)
1. A face recognition method is applied to a mobile terminal and is characterized by comprising the following steps:
when a face recognition request of a user is received, scene information is obtained;
determining the number of collected face characteristic points corresponding to the face recognition request according to the scene information;
carrying out face recognition according to the collected number of the face characteristic points;
the scene information comprises scene category information and mobile terminal operation information;
determining the number of collected face characteristic points corresponding to the face recognition request according to the scene information, wherein the number of collected face characteristic points comprises the following steps:
determining the scene type of face recognition according to the scene type information; wherein the scene categories include a paid category and a non-paid category;
selecting a reference grade corresponding to the face recognition request from a plurality of preset grades according to the scene category; the collection quantity of the face characteristic points corresponding to each grade is different;
determining a target grade corresponding to the face recognition request in the plurality of grades according to the mobile terminal operation information and the reference grade; the number of collected face characteristic points corresponding to the target grade is greater than or less than the number of collected face characteristic points corresponding to the reference grade;
taking the collected number of the face characteristic points corresponding to the target grade as the collected number of the face characteristic points corresponding to the face recognition request;
before performing face recognition according to the number of collected face feature points, the method further comprises:
determining a face comparison passing threshold corresponding to the face identification request according to the scene information;
and performing face recognition according to the collected number of the face characteristic points, wherein the face recognition comprises the following steps:
and carrying out face recognition according to the collected number of the face characteristic points and the comparison of the faces and a threshold value.
2. The method of claim 1, wherein the scene category is a payment class; determining a target grade corresponding to the face recognition request in the plurality of grades according to the mobile terminal operation information and the reference grade, wherein the target grade comprises any one of the following modes:
the mobile terminal operation information comprises network information connected with the mobile terminal, and according to a comparison result of the network information and preset network information, a grade with the corresponding face characteristic point collection quantity larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade;
the mobile terminal operation information comprises user identity authentication records of the mobile terminal in a preset time period, and according to the user identity authentication records, selecting a grade with the corresponding face characteristic point acquisition quantity being greater than or less than the face characteristic point acquisition quantity corresponding to the reference grade from the plurality of grades as the target grade;
the mobile terminal operation information comprises account information of a payee corresponding to the face recognition request, and a grade with the corresponding face characteristic point collection quantity larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade according to the account information of the payee;
the mobile terminal operation information comprises contact information of a consignee corresponding to the face recognition request, and according to a comparison result of the contact information of the consignee and contact information of a mobile terminal owner, a grade with the corresponding face characteristic point collection quantity being larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade.
3. The method of claim 1, wherein the scene category is a non-payment category; determining a target grade corresponding to the face recognition request in the plurality of grades according to the mobile terminal operation information and the reference grade, wherein the target grade comprises any one of the following modes:
the mobile terminal operation information comprises network information connected with the mobile terminal, and according to a comparison result of the network information and preset network information, a grade with the corresponding face characteristic point collection quantity larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade;
the mobile terminal operation information comprises user identity authentication records of the mobile terminal in a preset time period, and according to the user identity authentication records, the grade with the corresponding face characteristic point acquisition quantity larger or smaller than the face characteristic point acquisition quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade.
4. A mobile terminal, comprising:
the system comprises an acquisition unit, a processing unit and a display unit, wherein the acquisition unit is used for acquiring scene information when receiving a face recognition request of a user;
the first determining unit is used for determining the collection number of the face characteristic points corresponding to the face recognition request according to the scene information;
the face recognition unit is used for carrying out face recognition according to the collected number of the face characteristic points;
the scene information comprises scene category information and mobile terminal operation information; the first determining unit is specifically configured to:
determining the scene type of face recognition according to the scene type information; wherein the scene categories include a paid category and a non-paid category;
selecting a reference grade corresponding to the face recognition request from a plurality of preset grades according to the scene category; the collection quantity of the face characteristic points corresponding to each grade is different;
determining a target grade corresponding to the face recognition request in the plurality of grades according to the mobile terminal operation information and the reference grade; the number of collected face characteristic points corresponding to the target grade is greater than or less than the number of collected face characteristic points corresponding to the reference grade;
taking the collected number of the face characteristic points corresponding to the target grade as the collected number of the face characteristic points corresponding to the face recognition request;
wherein the mobile terminal further comprises: the second determining unit is used for determining a face comparison passing threshold corresponding to the face recognition request according to the scene information before carrying out face recognition according to the collected number of the face characteristic points;
the face recognition unit is specifically configured to:
and carrying out face recognition according to the collected number of the face characteristic points and the comparison of the faces and a threshold value.
5. The mobile terminal of claim 4, wherein the scene category is a payment class; the first determining unit is specifically configured to implement any one of the following modes:
the mobile terminal operation information comprises network information connected with the mobile terminal, and according to a comparison result of the network information and preset network information, a grade with the corresponding face characteristic point collection quantity larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade;
the mobile terminal operation information comprises user identity authentication records of the mobile terminal in a preset time period, and according to the user identity authentication records, selecting a grade with the corresponding face characteristic point acquisition quantity being greater than or less than the face characteristic point acquisition quantity corresponding to the reference grade from the plurality of grades as the target grade;
the mobile terminal operation information comprises account information of a payee corresponding to the face recognition request, and a grade with the corresponding face characteristic point collection quantity larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade according to the account information of the payee;
the mobile terminal operation information comprises contact information of a consignee corresponding to the face recognition request, and according to a comparison result of the contact information of the consignee and contact information of a mobile terminal owner, a grade with the corresponding face characteristic point collection quantity being larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade.
6. The mobile terminal of claim 4, wherein the scene category is a non-payment category; the first determining unit is specifically configured to implement any one of the following modes:
the mobile terminal operation information comprises network information connected with the mobile terminal, and according to a comparison result of the network information and preset network information, a grade with the corresponding face characteristic point collection quantity larger or smaller than the face characteristic point collection quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade;
the mobile terminal operation information comprises user identity authentication records of the mobile terminal in a preset time period, and according to the user identity authentication records, the grade with the corresponding face characteristic point acquisition quantity larger or smaller than the face characteristic point acquisition quantity corresponding to the reference grade is selected from the multiple grades to serve as the target grade.
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| CN109829706A (en) * | 2018-12-15 | 2019-05-31 | 深圳壹账通智能科技有限公司 | Transfer account method, device, computer equipment and storage medium based on recognition of face |
| CN110335386B (en) * | 2019-06-25 | 2021-08-03 | 腾讯科技（深圳）有限公司 | Identity authentication method, device, terminal and storage medium |
| CN112948792A (en) * | 2019-11-26 | 2021-06-11 | 华为技术有限公司 | Unlocking method and device |
| CN112417184B (en) * | 2020-11-23 | 2021-05-25 | 上海点泽智能科技有限公司 | Multi-scene characteristic information storage structure and comparison method, equipment and storage medium thereof |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105469033A (en) * | 2015-11-13 | 2016-04-06 | 广东欧珀移动通信有限公司 | Fingerprint identification method, fingerprint identification device and terminal equipment |
| CN106022059A (en) * | 2016-05-27 | 2016-10-12 | 广东欧珀移动通信有限公司 | Fingerprint unlocking method and terminal |
| CN106803058A (en) * | 2016-11-30 | 2017-06-06 | 努比亚技术有限公司 | A kind of terminal and fingerprint identification method |
| CN107766872A (en) * | 2017-09-05 | 2018-03-06 | 百度在线网络技术（北京）有限公司 | A kind of method and apparatus for identifying illumination Driving Scene |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104036176B (en) * | 2014-07-03 | 2018-02-09 | 南昌欧菲生物识别技术有限公司 | Method, authentication method and terminal device based on level of security registered fingerprint characteristic point |
| CN107220620A (en) * | 2017-05-27 | 2017-09-29 | 北京小米移动软件有限公司 | Face identification method and device |
-
2018
- 2018-03-27 CN CN201810258608.2A patent/CN108629280B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105469033A (en) * | 2015-11-13 | 2016-04-06 | 广东欧珀移动通信有限公司 | Fingerprint identification method, fingerprint identification device and terminal equipment |
| CN106022059A (en) * | 2016-05-27 | 2016-10-12 | 广东欧珀移动通信有限公司 | Fingerprint unlocking method and terminal |
| CN106803058A (en) * | 2016-11-30 | 2017-06-06 | 努比亚技术有限公司 | A kind of terminal and fingerprint identification method |
| CN107766872A (en) * | 2017-09-05 | 2018-03-06 | 百度在线网络技术（北京）有限公司 | A kind of method and apparatus for identifying illumination Driving Scene |
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