Method and apparatus for identifying character attributes

Abstract

An embodiment of the present application discloses a method for identifying human attributes. First, in response to receiving a human attribute identification request from a user, preset scenario description information is displayed. Then, an expression image of the user for the preset scenario description information is acquired, and the expression type of the expression image is identified. Then, based on the expression type of the expression image, human attribute information corresponding to the expression type is generated. The technical solution for human attribute identification provided by the present disclosure generates corresponding human attribute information for the user based on the expression type of the user for the preset scenario description information, enhancing the interest and meeting the personalized needs of the user.

Description

[0001] This application is a divisional application of "Person Attribute Recognition Method and Device". The filing date of the original application is October 30, 2019, the application number of the original application is 201911043156.7, and the title of the invention-creation of the original application is: Person Attribute Recognition Method and Device. Technical Field

[0002] Embodiments of this application relate to the field of computer technology, and particularly to a person attribute recognition method and device. Background Art

[0003] Currently, there are various APPs (Applications) with face recognition functions, but most of them are for appearance scoring and expression imitation, etc., and cannot meet the user's personalized attribute display requirements; for the APPs that guide users to imitate expressions, users cannot express themselves independently and lack fun. Summary of the Invention

[0004] Embodiments of this application propose a person attribute recognition method and device.

[0005] In a first aspect, embodiments of this application provide a person attribute recognition method, where the method includes: in response to receiving a person attribute recognition request from a user, displaying preset scenario description information; obtaining an expression image of the user for the preset scenario description information, and recognizing the expression type of the expression image; generating person attribute information corresponding to the expression type based on the expression type of the expression image.

[0006] In some embodiments, generating person attribute information corresponding to the expression type based on the expression type of the expression image includes: generating the person attribute information of the user based on the recognition times of the expression types obtained by recognizing the expression images of the user within a preset time period.

[0007] In some embodiments, generating the person attribute information of the user based on the recognition times of the expression types obtained by recognizing the expression images of the user within a preset time period includes: determining the ratio of the recognition times of the expression type to the number of pieces of preset scenario description information based on the recognition times of the expression types obtained by recognizing the expression images of the user within a preset time period; generating the person attribute information of the user based on the determined ratio.

[0008] In some embodiments, the person attribute information includes: an avatar, keywords, and a personal signature; the keywords are used to characterize the user's personality traits; generating person attribute information corresponding to the expression type includes: generating an avatar, keywords, and a personal signature corresponding to the expression type.

[0009] In some embodiments, the above method further includes: in response to receiving a sharing request from a user, sharing the character attribute information with the user indicated by the sharing request.

[0010] In some embodiments, the above method further includes: in response to reaching a preset update time, updating the preset scenario description information.

[0011] In a second aspect, an embodiment of the present application provides a character attribute recognition device, where the device includes: a display unit configured to display preset scenario description information in response to receiving a character attribute recognition request from a user; an expression recognition unit configured to obtain an expression image of the user for the preset scenario description information and recognize the expression type of the expression image; an attribute generation unit configured to generate character attribute information corresponding to the expression type based on the expression type of the expression image.

[0012] In some embodiments, the above attribute generation unit is further configured to generate the character attribute information of the above user based on the recognition times of the expression types obtained by recognizing the expression images of the user within a preset period.

[0013] In some embodiments, the above attribute generation unit is further configured to determine the ratio of the recognition times of the expression type to the number of preset scenario description information based on the recognition times of the expression types obtained by recognizing the expression images of the user within a preset period; and generate the character attribute information of the user based on the determined ratio.

[0014] In some embodiments, the character attribute information includes: an avatar, keywords, and a personal signature; the keywords are used to characterize the user's personality traits; generating the character attribute information corresponding to the expression type includes: generating an avatar, keywords, and a personal signature corresponding to the expression type.

[0015] In some embodiments, the above device further includes: a sharing unit configured to share the character attribute information with the user indicated by the sharing request in response to receiving a sharing request from a user.

[0016] In some embodiments, the above device further includes: an update unit configured to update the preset scenario description information in response to reaching a preset update time.

[0017] In a third aspect, an embodiment of the present application provides a computer-readable medium, on which a computer program is stored, where the program, when executed by a processor, implements the method described in any implementation manner of the first aspect.

[0018] Fourthly, an embodiment of the present application provides an electronic device, including: one or more processors; a storage device storing one or more programs thereon, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation manner of the first aspect.

[0019] For the method and device for identifying human attributes provided in the embodiments of the present application, first, in response to receiving a user's request for identifying human attributes, preset scenario description information is displayed; then, an expression image of the user for the preset scenario description information is acquired, and the expression type of the expression image is identified; then, based on the expression type of the expression image, human attribute information corresponding to the expression type is generated. The technical solution for identifying human attributes provided by the present disclosure generates corresponding human attribute information for the user based on the expression type of the user for the preset scenario description information, enhancing the interest and meeting the personalized needs of the user. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Other features, objects, and advantages of the present application will become more apparent by reading the detailed description of the non-limiting embodiments with reference to the following drawings:

[0021] Figure 1 is an exemplary system architecture diagram to which an embodiment of the present application can be applied;

[0022] Figure 2 is a flowchart of an embodiment of the method for identifying human attributes according to the present application;

[0023] Figure 3 is a schematic diagram of an application scenario of the method for identifying human attributes according to the present embodiment;

[0024] Figure 4 is a flowchart of another embodiment of the method for identifying human attributes according to the present application;

[0025] Figure 5 is a structural diagram of an embodiment of the device for identifying human attributes according to the present application;

[0026] Figure 6 is a schematic structural diagram of a computer system suitable for implementing the embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] The present application will be further described in detail below with reference to the drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the related invention and do not limit the invention. Additionally, it should be noted that for the sake of description, only parts related to the relevant invention are shown in the drawings.

[0028] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The following will describe the present application in detail with reference to the drawings and in combination with the embodiments.

[0029] Figure 1 FIG. 100 shows an exemplary architecture to which the method and apparatus for identifying human attributes according to the present application can be applied.

[0030] As Figure 1 shown, the system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0031] The terminal devices 101, 102, 103 may be hardware devices or software that support network connections for data interaction and data processing. When the terminal devices 101, 102, 103 are hardware, they may be various electronic devices that support functions such as taking pictures, information interaction, and network connection, including but not limited to smart phones, tablet computers, e-book readers, laptop computers, and desktop computers, etc. When the terminal devices 101, 102, 103 are software, they may be installed in the above-listed electronic devices. It may be implemented as, for example, multiple software or software modules for providing distributed services, or may be implemented as a single software or software module. No specific limitation is made here.

[0032] The server 105 may be a server that provides various services, such as a server that provides data processing and image recognition functions for the terminal devices 101, 102, 103. The server may store or process various received data and feedback the processing results to the terminal devices.

[0033] It should be noted that the method for identifying human attributes provided by the embodiments of the present disclosure may be executed by the terminal devices 101, 102, 103, or may be executed by the server 105. Correspondingly, the apparatus for identifying human attributes may be provided in the terminal devices 101, 102, 103, or may be provided in the server 105. No specific limitation is made here.

[0034] It should be noted that the server may be hardware or software. When the server is hardware, it may be implemented as a distributed server cluster composed of multiple servers, or may be implemented as a single server. When the server is software, it may be implemented as, for example, multiple software or software modules for providing distributed services, or may be implemented as a single software or software module. No specific limitation is made here.

[0035] It should be understood,Figure 1 The number of terminal devices and servers in [description] is merely illustrative. According to implementation requirements, there can be any number of terminal devices and servers.

[0036] Continuing to refer to Figure 2 , a flowchart 200 of an embodiment of the method for identifying personal attributes according to the present application is shown, including the following steps:

[0037] Step 201: In response to receiving a user's request for identifying personal attributes, display preset scenario description information.

[0038] In this embodiment, the execution subject (such as Figure 1 the terminal device in [description]) displays the preset scenario description information through its own configured display device after receiving the user's request for identifying personal attributes.

[0039] In this embodiment, the operation by which the user initiates a request for identifying personal attributes can be submitted in a human-computer interaction manner in existing technologies or future-developed technologies. These human-computer interaction manners include, but are not limited to: shaking the terminal, clicking a virtual button (such as a virtual button displayed on the display screen), clicking a physical button, gesture recognition, voice recognition, or other human-computer interaction manners to be developed in the future. Taking gesture recognition as an example, the camera of the execution subject acquires the user's gesture information and compares it with the predefined operation gestures corresponding to the operation of initiating a request for identifying personal attributes. If the user's gesture is recognized as the operation gesture corresponding to the operation of initiating a request for identifying personal attributes, then the operation of submitting a request for identifying personal attributes is submitted. Correspondingly, the execution subject of this embodiment can accept and recognize requests for identifying personal attributes submitted based on the above submission methods.

[0040] In this embodiment, the preset scenario description information can be various scenario description information that guides the user to make expressions reflecting their attribute characteristics. For example, preset scenario description information such as "Waking up as a billionaire in the morning" and "The school beauty from the next class wrote me a love letter". In some alternative implementation manners of this embodiment, the preset scenario description information can include at least one of time-sensitive scenario description information and scenario information targeted at user group characteristics. Among them, the time-sensitive scenario description information can be preset scenario description information about news, current affairs hotspots, currently popular movies and TV shows, and celebrities, such as "If XXX (the male lead of a certain movie and TV show) is my boyfriend", etc. The scenario information targeted at user group characteristics can be preset scenario description information about topics and fields that the user group is interested in, such as novels, games, etc.

[0041] In some alternative implementation manners of this embodiment, different numbers of preset scenario description information can be set. For example, two modes can be set, namely, 5 pieces of preset scenario description information and 10 pieces of preset scenario description information. The user can send a person attribute recognition request corresponding to the selected mode. Taking the mode of 5 pieces of preset scenario description information as an example, in response to receiving the person attribute recognition request corresponding to this mode by the execution entity, the first preset scenario description information in this mode is displayed in the preset display order, and the expression image of the user for this scenario description information is obtained; after determining that the expression image is obtained, the operation of displaying the next preset scenario description information and obtaining the expression image is entered until the operation of obtaining the expression images for all scenario description information in this mode is completed. In this embodiment, in response to reaching the preset update moment, the preset scenario description information is updated. In some alternative implementation manners, the preset scenario description information is updated in units of days, and the updated preset scenario description information is completely different from the preset scenario description information before the update.

[0042] Step 202: Obtain the expression image of the user for the preset scenario description information, and recognize the expression type of the expression image.

[0043] In this embodiment, after the preset scenario description information is displayed, the execution entity will obtain the expression image of the expression made by the user for the preset scenario description information. In some alternative implementation manners of this embodiment, after the execution entity displays the preset scenario description information, the preset scenario description information is displayed within a preset display time period, and after the preset display time period, the execution entity automatically triggers the built-in photographing device to photograph the facial expression image of the user. For example, if the preset display time is set to 3 seconds, after the execution entity displays the preset scenario description information for 3 seconds, it can automatically trigger the built-in photographing device to photograph the facial expression image of the user.

[0044] After obtaining the expression image of the user, the execution entity determines the state characteristics of facial organs such as eyebrows, eyes, eyelids, and lips according to the positions of facial key points in the expression image, so as to recognize the expression type of the user's expression image.

[0045] For example, if it is determined according to the positions of facial key points in the expression image that the state of the eyebrows is "raised, becoming higher and more curved, and the skin under the eyebrows is stretched", the state of the forehead is "horizontal wrinkles across the forehead", the state of the eyes is "the eyes are wide open, the upper eyelids are raised, the lower eyelids are lowered, and the white of the eyes is exposed", and the state of the lower half of the face is "the mandible drops and the mouth opens", its expression type can be determined as surprised. According to the expression types shown by the user in daily work and life, the expression types that can be recognized in this embodiment can include, for example: anger, disgust, fear, happiness, sadness, surprise, indifference, being cute, and being funny.

[0046] In some alternative implementation manners, the execution subject of this embodiment may perform expression recognition through a pre-trained expression recognition model. Using machine learning methods, the expression images in the expression image training set are used as the input of the expression recognition model, and the expression types corresponding to the expression images in the expression type training set are used as the target outputs of the expression recognition model, and the expression recognition model is trained. Specifically, the execution subject may use models such as convolutional neural networks, deep learning models, Naive Bayesian Model (NBM), or Support Vector Machine (SVM), use the expression image training set as the input of the model, and use the expression type training set as the output of the model to train the expression recognition model.

[0047] Step 203: Generate person attribute information corresponding to the expression type based on the expression type of the expression image.

[0048] In this embodiment, the person attribute information may be information used to characterize the attributes of the user. The manifestation forms of its attributes may include but are not limited to text information and image information. In some alternative implementation manners, the person attribute information includes: avatar, keyword, personal signature, suitable events, and unsuitable events. Among them, the keyword is used to characterize the personality characteristics of the user. In this embodiment, the execution subject generates person attribute information based on the obtained expression type according to the correspondence between the expression type and the person attribute information. The avatar in the person attribute information may be an image of a character or an animal in a movie, TV drama, or anime corresponding to the user's expression type; the keyword may be text information corresponding to the expression type, or text information corresponding to the character or animal corresponding to the selected avatar; the personal signature may be text information characterizing the user's personality, such as text information in literary works or text information processed according to the image characteristics shown by the character or animal in the selected avatar; the suitable events may be events recommended for the user to do according to the user's expression type; the unsuitable events may be events recommended for the user not to do according to the user's expression type.

[0049] For example, if the expression type of the expression made by the user in response to the preset scenario description information is anger, the person attribute information of the user may be set to the person attribute information corresponding to the anger expression type.

[0050] In some alternative implementation manners, the person attribute information may be generated according to a preset database or a pre-trained attribute recognition model. The preset database stores the correspondence data between the expression type and the person attribute information. The attribute recognition model is an attribute recognition model trained using machine learning methods based on the correspondence between the expression type and the person attribute information and can generate person attribute information corresponding to the expression type.

[0051] In some alternative implementation manners of this embodiment, step 203 of this embodiment may be implemented in the following manner: Generate the above-mentioned user's personal attribute information based on the recognition times of the expression types obtained by recognizing the user's expression images within a preset time period. In some alternative implementation manners, first, based on the recognition times of the expression types obtained by recognizing the user's expression images within a preset time period, determine the ratio of the recognition times of the expression types to the number of preset scenario description information. Then, based on the determined ratio, generate the above-mentioned user's personal attribute information.

[0052] The recognition times of the expression types can reflect the user's personal attributes within the preset time period. Within the preset time period, the more the recognition times of a certain expression type, the more this expression type can reflect the user's personal attributes. Since different modes can be set based on the quantity of the preset scenario description information, the ratio of the recognition times of the expression types to the number of the preset scenario description information can more accurately reflect the user's personal attribute information within the preset time period.

[0053] For example, based on recognizing the user's expression images in the mode of 10 preset scenario description information within a preset time period, 10 corresponding expression types are obtained. Among them, the recognition times of the angry expression type is 4, that is, there are 4 angry expression types among the 10 expression types; the recognition times of the cold expression type is 3, that is, there are 3 cold expression types among the 10 expression types; the recognition times of the disgusted expression type is 2, that is, there are 2 disgusted expression types among the 10 expression types; the recognition times of the funny expression type is 1, that is, there is 1 funny expression type among the 10 expression types. Among the 10 expression types, since the angry and cold expression types are in the majority, it can indicate that the user's emotional state is irritable and negative within the preset time period. To more accurately reflect the user's personal attribute information, determine the ratio of the recognition times of the expression types to the number of the preset scenario description information. In some alternative implementation manners, the ratios can be sorted from large to small, and the ratios of the preset rankings can be selected. For example, select the ratios ranked first and second. Among them, the expression type ranked first is angry, and its corresponding ratio is 0.4; the expression type ranked second is cold, and its corresponding ratio is 0.3; based on the above expression types and the ratio of the recognition times of the expression types to the number of the preset scenario description information: the ratio of the angry expression type is 0.4, and the ratio of the cold expression type is 0.3, generate the personal attribute information corresponding to the ratio for characterizing the user as irritable and negative.

[0054] In this embodiment, based on the expression type of the user for the preset scenario description information, corresponding character attribute information is generated for the user, enhancing the fun and meeting the personalized needs of the user. Further, after generating the character attribute information, the execution entity can push information that the user is interested in or associated with according to the user's character attribute information. For example, for an irritable user, articles that relieve anger can be pushed. In this way, the efficiency of information push can be improved.

[0055] Figure 3 An application scenario of the character attribute recognition method according to this embodiment is schematically shown. User 301 clicks on the virtual button on the smart phone 302 to initiate a character attribute recognition request. The phone 302 receives the character attribute recognition request from user 301, and after obtaining the preset scenario description information from the server 303, sequentially displays the preset scenario description information to user 301 through the display screen of the smart phone 302. User 302 makes corresponding expressions in sequence according to the preset scenario description information, and the phone 302 captures the expression image of user 301 and performs expression recognition. It is determined that the angry expression shown by the user is predominant according to the recognized expression type, and character attribute information corresponding to the angry emotion is generated for the user.

[0056] Continue to refer to Figure 4 which shows a schematic flow 400 of another embodiment of the character attribute recognition method according to the present application, including the following steps:

[0057] Step 401: In response to receiving a user's character attribute recognition request, display the preset scenario description information.

[0058] In this embodiment, step 401 is executed in a similar manner to step 201 and will not be elaborated here.

[0059] Step 402: Obtain the expression image of the user for the preset scenario description information, and recognize the expression type of the expression image.

[0060] In this embodiment, step 402 is executed in a similar manner to step 202 and will not be elaborated here.

[0061] Step 403: Based on the expression type of the expression image, generate character attribute information corresponding to the expression type.

[0062] In this embodiment, step 403 is executed in a similar manner to step 203 and will not be elaborated here.

[0063] Step 404: In response to receiving a user's sharing request, share the character attribute information with the user indicated by the sharing request.

[0064] In this embodiment, the operation of the user initiating a sharing request can be submitted in a human-computer interaction manner in the existing technology or future-developed technologies. These human-computer interaction manners include, but are not limited to: shaking the terminal, clicking a virtual button (such as a virtual button displayed on the display screen), clicking a physical button, gesture recognition, voice recognition, or other human-computer interaction manners to be developed in the future. Taking gesture recognition as an example, the camera of the execution entity acquires the user's gesture information and compares it with the predefined operation gesture corresponding to the operation of the sharing request. If the user's gesture is recognized as the operation gesture corresponding to the operation of initiating the sharing request, the operation of submitting the sharing request is submitted. Correspondingly, the execution entity of this embodiment can accept and recognize the sharing request submitted based on the above submission methods.

[0065] In this embodiment, the sharing request includes the account information of the shared object, and the shared object is the user indicated by the sharing request. The execution entity shares the character attribute information with the user indicated by the sharing request according to the sharing request.

[0066] In some optional implementation manners of this embodiment, the character attribute information can be shared with the shared object in the form of a picture. After receiving the user's sharing request, a picture including the character attribute recognition information is generated, and the picture including the character attribute recognition information is shared to the account of the shared object.

[0067] From Figure 4 it can be seen that compared with the corresponding embodiment of Figure 2 , the process 400 of the character attribute recognition method in this embodiment specifically illustrates that after generating the character attribute information, the character attribute information can be shared with a specified user. In this way, the communication and interaction between users are increased, and the interestingness is improved.

[0068] Continuing to refer to Figure 5 , as an implementation of the methods shown in the above figures, an embodiment of a character attribute recognition device is provided in the present disclosure. This device embodiment corresponds to the method embodiment shown in Figure 2 , and this device can be specifically applied to various electronic devices.

[0069] As Figure 5 shown, the character attribute recognition device includes: a display unit 501, an expression recognition unit 502, an attribute generation unit 503, a sharing unit 504, and an update unit 505.

[0070] The display unit 501 is configured to display preset scenario description information in response to receiving a user's request for character attribute recognition; the expression recognition unit 502 is configured to obtain an expression image of the user for the preset scenario description information and recognize the expression type of the expression image; the attribute generation unit 503 is configured to generate character attribute information corresponding to the expression type based on the expression type of the expression image; the sharing unit 504 is configured to share the character attribute information with the user indicated by the sharing request in response to receiving the user's sharing request; the updating unit 505 is configured to update the preset scenario description information in response to reaching a preset update time.

[0071] The attribute generation unit 503 is further configured to calculate the ratio of the number of expression types to the number of preset scenario description information based on the expression type of the expression image; and generate character attribute information corresponding to the ratio based on the ratio of the number of expression types to the number of preset scenario description information.

[0072] The following refers to Figure 6 , which shows a schematic structural diagram of a computer system 600 suitable for use in implementing the devices (such as Figure 1 the devices 101, 102, 103, 105 shown) of the embodiments of the present application. Figure 6 The devices shown are merely examples and should not impose any limitations on the functions and usage scope of the embodiments of the present application.

[0073] As Figure 6 shown, the computer system 600 includes a processor (such as a CPU, central processing unit) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage section 608 into a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the system 600 are also stored. The processor 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0074] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, a modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed so that a computer program read from it can be installed into the storage section 608 as needed.

[0075] In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment of the present disclosure includes a computer program product that includes a computer program carried on a computer-readable medium, and the computer program includes program code for performing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 609, and / or installed from the removable medium 611. When the computer program is executed by the processor 601, the above functions defined in the methods of the present application are performed.

[0076] It should be noted that the computer-readable medium of the present application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present application, the computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries the computer-readable program code. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted by any suitable medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0077] Computer program code for performing the operations of this application can be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the client computer, partially on the client computer, executed as a stand-alone software package, partially on the client computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the client computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., by connecting through the Internet using an Internet service provider).

[0078] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of apparatuses, methods, and computer program products according to various embodiments of this application. In this regard, each block in the flowchart or block diagram can represent a module, a program segment, or a portion of code that contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks can occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown can actually be executed substantially in parallel, and they can sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0079] The units involved in the embodiments described in this application can be implemented in software or in hardware. The described units can also be provided in a processor. For example, it can be described as: a processor including a display unit, an expression recognition unit, an attribute generation unit, an update unit, and a sharing unit. Among them, the names of these units do not constitute a limitation on the unit itself in some cases. For example, the attribute generation unit can also be described as a unit that "generates person attribute information corresponding to the expression type based on the expression type of the expression image".

[0080] As another aspect, the present application also provides a computer-readable medium, which may be included in the device described in the above embodiments; or may exist separately without being assembled into the device. The above computer-readable medium carries one or more programs, and when the one or more programs are executed by the device, the computer device is caused to: display preset scenario description information in response to receiving a user's request for identifying personal attributes; obtain an expression image of the user for the preset scenario description information, and identify the expression type of the expression image; and generate personal attribute information corresponding to the expression type based on the expression type of the expression image.

[0081] The above description is only a preferred embodiment of the present application and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above inventive concept. For example, a technical solution formed by mutually replacing the above features with technical features (but not limited to) having similar functions disclosed in the present application.

Claims

1. A method for identifying user attributes, wherein, the method includes: In response to receiving a user's request for identifying user attributes, display preset scenario description information, wherein the preset scenario description information is used to describe a preset scenario and guide the user to make an expression that reflects their attribute characteristics in the preset scenario, including at least one of time-sensitive scenario description information and scenario information for user group characteristics; Obtain the user's expression image for the preset scenario description information, and identify the expression type of the expression image; Through a pre-trained attribute recognition model, based on the number of times of identifying the expression type obtained from the user's expression images within a preset time period, determine the ratio of the number of times of identifying the expression type to the number of preset scenario description information; Based on the determined ratio, generate user attribute information corresponding to the expression type, wherein the user attribute information is used to characterize the user's attributes, including an avatar, keywords, and a personal signature, and the keywords are used to characterize the user's personality characteristics; The method further includes: In response to reaching a preset update time, update the preset scenario description information.

2. The method according to claim 1, wherein, the method further includes: In response to receiving the user's sharing request, share the user attribute information with the user indicated by the sharing request.

3. The method according to claim 1, wherein, generating the user attribute information corresponding to the expression type includes: Generating an avatar, keywords, and a personal signature corresponding to the expression type.

4. A device for identifying user attributes, wherein, the device includes: A display unit configured to display preset scenario description information in response to receiving a user's request for identifying user attributes, wherein the preset scenario description information is used to describe a preset scenario and guide the user to make an expression that reflects their attribute characteristics in the preset scenario, including at least one of time-sensitive scenario description information and scenario information for user group characteristics; An expression recognition unit configured to obtain the user's expression image for the preset scenario description information and identify the expression type of the expression image; An attribute generation unit configured to, through a pre-trained attribute recognition model, based on the number of times of identifying the expression type obtained from the user's expression images within a preset time period, determine the ratio of the number of times of identifying the expression type to the number of preset scenario description information; and based on the determined ratio, generate user attribute information corresponding to the expression type, wherein the user attribute information is used to characterize the user's attributes, including an avatar, keywords, and a personal signature, and the keywords are used to characterize the user's personality characteristics; The device further includes: An update unit configured to update the preset scenario description information in response to reaching a preset update time.

5. The device according to claim 4, wherein, the device further includes: A sharing unit configured to share the user attribute information with the user indicated by the sharing request in response to receiving the user's sharing request.

6. The device according to claim 4, wherein, Generating the person attribute information corresponding to the expression type includes: Generating an avatar, keywords, and a personal signature corresponding to the expression type.

7. A computer-readable medium having a computer program stored thereon, wherein, when the program is executed by a processor, the method described in any one of claims 1-3 is implemented.

8. An electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon, when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any one of claims 1-3.

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