System for providing customized makeup recommendations and linking beauty experiences based on facial feature analysis

Abstract

A technology for generating personalized makeup techniques is provided. A method according to one embodiment of the present disclosure may include the steps of: acquiring a target image in which a user's face is captured; performing an analysis based on the target image, including at least some of skin tone, skin type, personal color, and contour regarding the face; generating a makeup draft suitable for the face based on the target image and the result of the analysis; and transmitting the makeup draft to the user's terminal. Here, the makeup draft may be an image that displays a matching of at least one area of ​​the face and a beauty product applied to the area.

Description

Technology Field

[0001] The present disclosure relates to a customized makeup recommendation and beauty experience linkage service system utilizing facial characteristic analysis. Background Technology

[0002] Interest in personalized makeup techniques has been rapidly increasing recently. This is due to the growing desire among consumers to find cosmetics and makeup methods suited to their skin condition and characteristics. In particular, personalized makeup techniques are receiving even more attention with the emergence of skin analysis devices and data-based cosmetic recommendation systems alongside technological advancements. These technologies help analyze a user's skin condition and assist in recommending suitable products or suggesting makeup methods.

[0003] However, despite current technological advancements, there are still limitations to the personalization of customized makeup techniques. The biggest problem is that skin attributes vary significantly from user to user. Since various factors such as skin tone, sensitivity, oil and moisture content, and seasonal changes differ for each individual, it is difficult to provide customized solutions that accurately reflect these characteristics. Existing systems often provide recommendations based on general skin types, frequently failing to adequately reflect the detailed skin characteristics of individual users.

[0004] Furthermore, skin condition can change over time and vary depending on environmental factors or lifestyle habits. Proposing personalized makeup routines that reflect these dynamic changes in real time is a challenging task with current technology. Consequently, users find it difficult to find a makeup routine that perfectly matches their skin condition, and this acts as a major factor limiting the effectiveness of customized makeup techniques. The problem to be solved

[0005] The purpose of the present disclosure is to provide a method for generating an AI-based personalized makeup technique that takes into account skin tone and facial contours, providing a personalized experience to the user. means of solving the problem

[0006] In one embodiment of the present disclosure, a method performed by an electronic device may be provided. The method may include the steps of: acquiring a target image in which a user's face is captured; performing an analysis based on the target image including at least some of skin tone, skin type, personal color, and contour regarding the face; generating a makeup draft suitable for the face based on the target image and the result of the analysis; and transmitting the makeup draft to the user's terminal. The makeup draft may be an image that displays a matching of at least one area of ​​the face and a beauty product applied to the area.

[0007] In one embodiment of the present disclosure, the method may include the step of obtaining a precise diagnostic result including at least some of the measurement result of a diagnostic device regarding the user's face, the actual measurement result of personal color, and comments from a makeup artist, and the step of obtaining the user's beauty purchase history. The step of generating a makeup draft may include the step of generating a makeup draft suitable for the face based on the precise diagnostic result and the beauty purchase history.

[0008] In one embodiment of the present disclosure, the method may include the step of recommending a beauty experience list associated with the makeup draft. The beauty experience list may include a makeup experience, a photography experience, or a precision diagnostic experience.

[0009] In one embodiment of the present disclosure, the method may include the steps of obtaining a list of beauty products preferred by the user, generating a makeup comparison draft for the face based on the beauty product list, and transmitting display information to the user terminal so that the makeup draft and the makeup comparison draft are displayed on the same screen. The step of generating the makeup comparison draft may include the step of virtually applying a beauty product included in the beauty product list to at least one area of ​​the face of the target image, wherein if there is no beauty product corresponding to a specific face area in the beauty product list, the step of generating the makeup comparison draft by virtually applying a beauty product applied to the specific face area in the makeup draft to the specific face area. The step of transmitting the display information to the user terminal may include the step of transmitting display information to the user terminal so that the makeup draft and the makeup comparison draft are each displayed on a screen divided left and right, and that beauty product information applied differently between the makeup draft and the makeup comparison draft is highlighted and displayed.

[0010] In one embodiment of the present disclosure, the step of transmitting the display information to the user terminal may include the step of transmitting to the user terminal a discount promotion regarding a target beauty product that is not in the beauty product list and is not applied to the makeup comparison draft, but is applied only to the makeup draft.

[0011] In one embodiment of the present disclosure, the step of performing the analysis may include: extracting a plurality of facial feature points from the target image; distinguishing a plurality of facial regions, each including a T-zone, a U-zone, an eye area, and lips, based on the plurality of facial feature points; and calculating at least one of a color value representing skin tone and an oil-moisture index representing skin type for each of the plurality of facial regions. The step of generating the makeup draft may include: accessing a database storing a plurality of beauty products matched with attribute information including color information and formulation information; selecting a beauty product from the database having attribute information corresponding to the color value and the oil-moisture index for each of the plurality of facial regions; and virtually applying the beauty product to the corresponding facial region of the target image to generate the makeup draft.

[0012] An apparatus according to one embodiment of the present disclosure may be combined with hardware and controlled by a computer program stored on a medium to execute the method of any one of the methods described above. Effects of the invention

[0013] According to one embodiment of the present disclosure, a target image in which a user's face is captured is acquired, and by performing an analysis including at least some of skin tone, skin type, personal color, and contour based on the target image, a personalized analysis based on skin attributes different for each user can be provided. According to one embodiment of the present disclosure, a makeup draft suitable for the user's face is generated based on the analysis results and transmitted to a user terminal, thereby providing a personalized beauty experience to the user. Furthermore, according to one embodiment of the present disclosure, since the makeup draft is provided as an image that matches a specific area of ​​the face with a beauty product suitable for that area, the user can select a beauty product suitable for themselves more intuitively and efficiently. Brief explanation of the drawing

[0014] FIG. 1 illustrates an environment in which a management device according to one embodiment of the present disclosure can be applied. FIG. 2 illustrates an electronic device capable of implementing a management device according to one embodiment of the present disclosure. FIG. 3 illustrates a flowchart showing a method according to one embodiment of the present disclosure. Figure 4 illustrates a flowchart showing the detailed operation of the analysis execution operation described with reference to Figure 3. Figure 5 illustrates a flowchart showing the detailed operation of the creation operation of the cosmetic draft described with reference to Figure 3. FIG. 6 illustrates a flowchart showing a method according to one embodiment of the present disclosure. FIG. 7 illustrates a flowchart showing a method according to one embodiment of the present disclosure. FIG. 8 illustrates a flowchart showing a method according to one embodiment of the present disclosure. FIG. 9 illustrates a cosmetic draft screen that may be referenced in various embodiments of the present disclosure. Specific details for implementing the invention

[0015] The various embodiments described in this disclosure are illustrative for the purpose of clearly explaining the technical concept of this disclosure and are not intended to limit it to specific embodiments. The technical concept of this disclosure includes various modifications, equivalents, alternatives, and embodiments selectively combined from all or part of each embodiment described in this disclosure. Furthermore, the scope of the technical concept of this disclosure is not limited to the various embodiments presented below or the specific descriptions thereof.

[0016] Terms used in this disclosure, including technical or scientific terms, may have the meaning generally understood by a person skilled in the art to which this disclosure pertains, unless otherwise defined. Since such terms may be referred to by various other terms depending on technological development, changes, conventions, and the preferences of skilled persons, the scope of the technical concept of this disclosure is not limited by the meaning of the terms used below.

[0017] Expressions used in this disclosure, such as “comprising,” “may compose,” “possessing,” “possessing,” “having,” and “possessing,” mean that the subject feature (e.g., function, operation, or component, etc.) exists and do not exclude the existence of other additional features. That is, such expressions should be interpreted as open-ended terms implying the possibility of including other embodiments.

[0018] Singular expressions used in this disclosure may include the meaning of the plural form unless otherwise indicated by the context, and this applies likewise to singular expressions described in the claims.

[0019] Ordinal expressions used in this disclosure, such as "first," "second," or "first," "second," etc., are used to distinguish one object from another when referring to a plurality of objects of the same kind, unless otherwise indicated in the context, and do not limit the order or importance of the objects.

[0020] Expressions used in the present disclosure, such as “A, B and C”, “A, B or C”, “at least one of A, B and C”, and “at least one of A, B or C”, may mean each of the listed items or all possible combinations of the listed items. For example, “at least one of A or B” may refer to (i) at least one A, (ii) at least one B, and (iii) at least one A and at least one B.

[0021] The expression “based on” as used in this disclosure is used to describe one or more factors affecting an act or action of a decision or judgment described in the phrase or sentence containing this expression, and this expression does not exclude additional factors affecting said act or action of a decision or judgment.

[0022] As used in the present disclosure, the expression that a certain component (e.g., a first component) is "connected" or "connected" to another component (e.g., a second component) may mean that the certain component is not only directly connected or connected to the other component, but is also connected or connected through a new other component (e.g., a third component).

[0023] As used in this disclosure, the expression "configured to" may have meanings such as "set to," "capable of," "modified to," "made to," or "capable of." This expression is not limited to the meaning of "specifically designed in hardware." For example, a processor configured to perform a specific operation may mean a generic-purpose processor capable of performing that specific operation by executing software, or a special-purpose computer structured through programming to perform that specific operation.

[0024] The expressions “part,” “module,” “model,” etc. used in this disclosure refer to software or hardware components such as FPGAs (Field-Programmable Gate Arrays) and ASICs (Application Specific Integrated Circuits). Here, “part,” “module,” “model,” etc. may be configured to reside in an addressable storage medium and may be configured to operate one or more processors. Accordingly, “part,” “module,” “model,” etc. may include components such as software components, object-oriented software components, class components, and task components, as well as processors, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. Additionally, the functions provided through “part,” “module,” “model,” etc. may be combined into smaller units of “part,” “module,” or “model.”

[0025] As used in this disclosure, the term "Artificial Intelligence (AI)" may refer to a technology that mimics human learning ability, reasoning ability, perceptual ability, etc., and implements them on a computer. Such artificial intelligence may include concepts such as machine learning or symbolic logic.

[0026] As used in this disclosure, the term "Machine Learning (ML)" may refer to a process of training an artificial intelligence model using experience in processing data. As a specific example, machine learning may be a technology that enables an artificial intelligence model to self-classify or learn the features of input data. An artificial intelligence model can analyze input data as a machine learning algorithm, learn based on the results of the analysis, and make judgments or predictions regarding new inputs based on the results of the learning. Unlike the examples provided, any technology that learns to mimic the cognitive and judgmental functions of the human brain (e.g., linguistic understanding, visual understanding, reasoning, prediction, knowledge representation, motion control, etc.) may be understood as falling under the category of machine learning. Examples of machine learning algorithms include supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning. Such machine learning may be performed on the device itself where the artificial intelligence model is executed, or through a separate server or system.

[0027] As used in this disclosure, the term "artificial intelligence model" may refer to a model constructed by extracting and analyzing features from given data and modeling the correlations between the data. The process of constructing the correlations of an artificial intelligence model may be referred to as machine learning. An artificial intelligence model may be composed of one or more neural network layers. Each neural network layer has one or more weights and performs neural network operations through operations between the result of a previous layer's operation and one or more weights. The one or more weights possessed by a neural network layer may be optimized based on the learning results of the artificial intelligence model. As a specific example, one or more weights may be updated during the learning process so that the loss value or cost value obtained from the artificial intelligence model is reduced or minimized. Artificial intelligence models may include, for example, CNN (Convolutional Neural Network), DNN (Deep Neural Network), RNN (Recurrent Neural Network), RBM (Restricted Boltzmann Machine), DBN (Deep Belief Network), BRDNN (Bidirectional Recurrent Deep Neural Network), or Deep Q-Networks, but are not limited thereto.

[0028] Embodiments of the present disclosure will be described below with reference to the attached drawings. In the attached drawings, identical or corresponding components are given the same reference numerals. Furthermore, in the description of the embodiments below, the description of identical or corresponding components may be omitted. However, even if a description of a component is omitted, it is not intended that such component is not included in any embodiment.

[0029] FIG. 1 illustrates an environment (100) to which a management device (110) according to one embodiment of the present disclosure can be applied.

[0030] Referring to FIG. 1, the environment (100) may include a management device (110) and a user terminal (120). The environment (100) may be a system environment in which a method for generating a personalized makeup technique according to one embodiment of the present disclosure is implemented. The management device (110) and the user terminal (120) may communicate with each other through a network.

[0031] The management device (110) may be an entity that performs artificial intelligence analysis based on information obtained from the user and generates a personalized makeup technique. The management device (110) may receive a target image of the user's face captured from the user terminal (120). The management device (110) may process the received target image to analyze the user's skin characteristics and generate a customized makeup draft based on the analysis results.

[0032] In one embodiment of the present disclosure, the management device (110) can perform an analysis including at least some of skin tone, skin type, personal color, and contour regarding the face based on a target image. The management device (110) can select a beauty product suitable for the user's face based on the analysis results. Subsequently, the management device (110) can generate a makeup draft by virtually applying the selected beauty product to the target image and transmit the generated makeup draft to a user terminal (120).

[0033] Additionally, the management device (110) can improve the accuracy of the makeup draft by utilizing additional information regarding the user. For example, the management device (110) can additionally obtain precise diagnostic results, such as measurement results from diagnostic equipment, actual measurement results of personal color, or comments from a makeup artist. The management device (110) can obtain the user's beauty product purchase history to identify the user's preferences and reflect them in the creation of the makeup draft. For example, the management device (110) may be a server, a cloud computing system, a distributed computing system, an artificial intelligence (AI) server, a database server, a web server, or an application server. However, the present disclosure is not limited thereto.

[0034] The user terminal (120) may be a device used by the user to utilize a personalized makeup technique generation service. The user terminal (120) may acquire a target image by photographing the user's face through a built-in camera. The user terminal (120) may perform the function of transmitting the acquired target image to a management device (110).

[0035] In one embodiment of the present disclosure, a user terminal (120) may receive a makeup draft from a management device (110) and display it on a display. The user may visually check the makeup draft recommended to them through the screen of the user terminal (120). The user terminal (120) may display information on recommended beauty products, usage methods, and a related beauty experience list together with the makeup draft.

[0036] Additionally, the user terminal (120) may provide an interface that receives input from the user and transmits it to the management device (110). For example, the user may input a list of preferred beauty products through the user terminal (120). The user terminal (120) may receive a recommended makeup sample and a makeup comparison sample based on the user's preferred products from the management device (110) and display them on the same screen, thereby enabling the user to intuitively compare the two samples. For example, the user terminal (120) may be a smartphone, a tablet computer, a personal computer (PC), a laptop, a smart watch, smart glass, or a kiosk. However, the present disclosure is not limited thereto.

[0037] A network connecting a management device (110) and a user terminal (120) can be implemented through various communication technologies, including wired or wireless communication methods. The network can provide a communication channel to enable smooth transmission and reception of data between the two devices. Through this, an image acquired from the user terminal (120) can be rapidly transmitted to the management device (110), and a makeup design generated by the management device (110) can be delivered to the user terminal (120) without delay. For example, the network may be the Internet, a Local Area Network (LAN), a Wide Area Network (WAN), Wi-Fi, Bluetooth, a 5th Generation (5G) mobile network, or a Long Term Evolution (LTE) network. However, the present disclosure is not limited thereto.

[0038] FIG. 2 illustrates an electronic device (200) capable of implementing a management device (110) according to one embodiment of the present disclosure.

[0039] Referring to FIG. 2, the electronic device (200) may implement a management device (110) according to one embodiment of the present disclosure. The electronic device (200) may be a computing device of various forms, such as a server computer, a cloud server, or a personal computer (PC). The electronic device (200) may include a processor (210), a memory (220), and a communication interface (230).

[0040] The processor (210) can control the overall operation of the electronic device (200). The processor (210) can perform various data processing and computation functions by executing instructions stored in memory (220). The processor (210) can interact with other components within the electronic device (200) to perform the role of controlling the system so that it operates smoothly.

[0041] In the present disclosure, the processor (210) can execute an artificial intelligence model to perform a method for generating a personalized makeup technique. For example, the processor (210) can analyze the user's skin tone, skin type, personal color, and facial contours based on a target image received through a communication interface (230). Additionally, the processor (210) can perform an operation to select a beauty product suitable for the user based on the analyzed results, and to virtually apply it to generate a makeup draft.

[0042] The processor (210) can be implemented as various types of processing units. For example, the processor (210) may be a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), a Neural Processing Unit (NPU), a Digital Signal Processor (DSP), an Application-Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or a Microcontroller Unit (MCU). However, the present disclosure is not limited thereto.

[0043] The memory (220) can store data or programs necessary for the operation of the processor (210). The memory (220) can provide a space for temporarily or permanently storing data to be processed by the processor (210), data currently being processed, or data that has been processed. The memory (220) can store the operating system (OS) and various applications of the electronic device (200).

[0044] In the present disclosure, the memory (220) may store various information for generating a personalized makeup technique. Specifically, the memory (220) may include a database in which an artificial intelligence model for skin analysis, analysis result data, and attribute information of a beauty product are stored, which are obtained from a user. Additionally, the memory (220) may temporarily store makeup draft image data generated by the processor (210) and then transmit it through a communication interface (230).

[0045] The memory (220) may include both volatile memory and non-volatile memory. For example, the memory (220) may be Random Access Memory (RAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Read-Only Memory (ROM), Flash Memory, Solid State Drive (SSD), or Hard Disk Drive (HDD). However, the present disclosure is not limited thereto.

[0046] The communication interface (230) can perform a communication function that enables the electronic device (200) to transmit and receive data with an external device. The communication interface (230) can connect to a network via a wired or wireless communication method. The communication interface (230) can mediate communication with another device by generating or interpreting data packets according to a defined communication protocol.

[0047] In the present disclosure, the communication interface (230) may be responsible for exchanging data with the user terminal (120). The communication interface (230) may perform the role of receiving a target image in which the user's face is captured from the user terminal (120). Additionally, the communication interface (230) may perform the role of transmitting makeup drafts and related beauty product information generated by the processor (210) to the user terminal (120).

[0048] The communication interface (230) may support various communication technologies. For example, the communication interface (230) may be Bluetooth, Bluetooth Low Energy (BLE), Zigbee, Wi-Fi, Ethernet, 3rd Generation (3G), 4th Generation (4G) Long Term Evolution (LTE), or 5th Generation (5G) communication technology. However, the present disclosure is not limited thereto.

[0049] FIG. 3 illustrates a flowchart showing a method (S300) according to one embodiment of the present disclosure.

[0050] Referring to FIG. 3, the method (S300) can be performed by a management device (110).

[0051] In step S310, the management device (110) can acquire a target image in which the user's face is captured. The management device (110) can receive the target image from the user terminal (120) via a network. The target image may be a still image captured by the user using a camera provided in the user terminal (120). The target image may be a specific frame image of a video capturing the user's face.

[0052] In step S320, the management device (110) can perform an analysis of the face based on the target image. The management device (110) can execute an artificial intelligence model stored in memory (220) using a processor (210). The artificial intelligence model can extract feature information regarding the user's face from the target image. The artificial intelligence model can perform an analysis using the extracted feature information.

[0053] In one embodiment of the present disclosure, the step of performing an analysis (S320) may perform an analysis including at least some of skin tone, skin type, personal color, and contour regarding the face. The management device (110) may extract a user's skin color value from a target image through a deep learning-based image analysis model. The management device (110) may determine the skin tone based on the extracted skin color value. The management device (110) may estimate the oil and moisture status of a specific area of ​​the image. The management device (110) may classify the skin type based on the estimated oil and moisture status.

[0054] In step S330, the management device (110) can generate a makeup draft suitable for the face based on the target image and the results of the analysis. The management device (110) can generate a personalized makeup draft based on the user's unique facial characteristics analyzed in step S320. For example, the management device (110) can select a beauty product of a shade that matches the analyzed personal color. The management device (110) can apply a makeup technique that can complement the analyzed facial contours. The management device (110) can generate a makeup draft based on the selected beauty product and the applied makeup technique.

[0055] In one embodiment of the present disclosure, the makeup draft may be an image that matches and displays at least one area of ​​the face with a beauty product applied to that area. The management device (110) may generate a composite image in which a beauty product is virtually applied to the face of the target image. The generated image may display a beauty product applied to a specific facial area, such as eyes, nose, or lips, and a method of application.

[0056] In step S340, the management device (110) can transmit a makeup draft to a user terminal (120). The management device (110) can transmit data regarding the generated makeup draft to the user terminal (120) using a communication interface (230). The user terminal (120) can display an image of the makeup draft using the received data. The user terminal (120) can provide the user with information about related beauty products.

[0057] FIG. 4 illustrates a flowchart showing the detailed operation (S400) of the analysis execution operation (S320) described with reference to FIG. 3.

[0058] Referring to FIG. 4, the detailed operation (S400) of the analysis execution operation (S320) described with reference to FIG. 3 can be performed by the management device (110).

[0059] In step S410, the management device (110) can extract a plurality of facial feature points from a target image. The management device (110) can identify points in the user's facial image using an Artificial Intelligence (AI) model. The plurality of facial feature points can be used to define structural characteristics of the face. For example, facial feature points may be the ends of the eyes, the tip of the nose, the nostrils, the ends of the lips, the jawline, the boundary of the forehead, and the protrusions of the cheekbones. However, the present disclosure is not limited thereto. The management device (110) can precisely extract facial feature points through a deep learning-based facial landmark detection algorithm.

[0060] In step S420, the management device (110) can distinguish multiple facial regions, including the T-zone, U-zone, eye area, and lips, based on multiple facial feature points. The management device (110) can generate a mask that divides the face into multiple regions by connecting the extracted facial feature points. The T-zone may be a region including the forehead, nose, and chin. The U-zone may be a region including both cheeks and the jawline. The skin characteristics of each region may differ. Therefore, region division may be performed for customized analysis by region. For example, the multiple facial regions may be the T-zone, U-zone, eye area, lips, C-zone, apple zone, and philtrum. However, the present disclosure is not limited thereto.

[0061] In step S430, the management device (110) can calculate at least one of a color value representing skin tone and an oil-moisture index representing skin type for each of a plurality of facial regions. The management device (110) can calculate an average color value by analyzing the color information of pixels within each separated facial region. For example, the color value may be expressed as coordinates in an RGB (Red, Green, Blue) color space, a Hue, Saturation, Value (HSV) color space, a CIELAB color space, a YCbCr color space, an HSL color space, a CMYK color space, or a YUV color space. However, the present disclosure is not limited thereto. The management device (110) may use an algorithm that analyzes the texture, gloss, fine wrinkles, etc. of an image. The management device (110) can calculate an oil-moisture index by estimating the oil and moisture status of each area through the above algorithm. The oil-moisture index can be used as a basis for determining whether the skin is dry, oily, combination, or normal.

[0062] FIG. 5 illustrates a flowchart showing the detailed operation (S500) of the operation (S330) for generating a cosmetic draft described with reference to FIG. 3.

[0063] Referring to FIG. 5, the detailed operation (S500) may be a detailed operation of the creation operation (S330) of a cosmetic draft performed by the management device (110).

[0064] In step S510, the management device (110) may access a database that stores a plurality of beauty products matched with attribute information including color information and formulation information. The management device (110) may access a database stored in an internal memory (220) or on an external server connected via a network. The database may systematically store and manage detailed information about various beauty products. For example, beauty products may be foundation, concealer, eyeshadow, lipstick, blush, highlighter, shading product, primer, or eyeliner. However, the present disclosure is not limited thereto. The attribute information may include Red Green Blue (RGB) values, Hex codes, Pantone color codes, etc., representing the color of the beauty product. The attribute information may include information such as matte, glossy, powder, liquid, or cream, indicating the formulation of the beauty product.

[0065] In step S520, the management device (110) can select a beauty product from a database having attribute information corresponding to color values ​​and oil-moisture indicators for each of a plurality of facial regions. For example, the management device (110) can select a foundation with a matte formulation that has an oil control function for the T-zone region, which has a high oil content. The management device (110) can select a concealer with a moisturizing formulation containing moisturizing ingredients for the eye area, which has dry and thin skin. The management device (110) can select a lipstick color to be applied to the lip area based on the user's personal color diagnosis results.

[0066] In step S530, the management device (110) can generate a makeup draft by virtually applying a beauty product to the corresponding facial area of ​​the target image. The management device (110) can precisely render the selected beauty product to the facial area of ​​the target image using Augmented Reality (AR) technology or computer graphics technology. During the rendering process, the color, texture, color intensity, and gloss of the beauty product can be expressed similarly to actual makeup. The generated makeup draft may be a simulation image that allows the user to intuitively see what they would look like when using the recommended beauty product.

[0067] FIG. 6 illustrates a flowchart showing a method (S600) according to one embodiment of the present disclosure.

[0068] Referring to FIG. 6, the method (S600) can be performed by a management device (110). The method (S600) may be an embodiment of the method (S300) of FIG. 3.

[0069] In step S610, the management device (110) can obtain a precise diagnostic result regarding the user's face. The precise diagnostic result may include specific skin condition information of the user that is difficult to ascertain solely through the analysis of the target image. The management device (110) can obtain more objective and scientific data through the precise diagnostic result. The precise diagnostic result may include at least some of the measurement results of the diagnostic equipment, the actual measurement results of personal color, and comments from a makeup artist. For example, the diagnostic equipment may be a skin moisture meter, an oil meter, a skin elasticity meter, a pigmentation analyzer, a wrinkle depth meter, a pore size analyzer, a skin tone meter, or a skin sensitivity meter. However, the present disclosure is not limited thereto. The actual measurement results of personal color may be the result of a professional measuring a color group that harmonizes with the user's body color using a diagnostic cloth. The comments from the makeup artist may be expert opinions written by a professional who comprehensively judges the user's facial structure, skin texture, overall image, etc.

[0070] In step S620, the management device (110) can obtain the user's beauty purchase history. The beauty purchase history can be used to identify the user's product preferences, price sensitivity, brand loyalty, etc. The management device (110) can receive the beauty purchase history from an online shopping mall server linked to the user terminal (120). Alternatively, the management device (110) can receive the beauty purchase history from an external database where the user's membership information is stored. The beauty purchase history may include information such as the name of the purchased product, brand, color, formulation, purchase date, and purchase cycle.

[0071] In step S630, the management device (110) can generate a makeup draft suitable for the face based on the precision diagnosis results and beauty purchase history. The management device (110) can select the beauty product most suitable for the user's current skin condition using the precision diagnosis results obtained in step S610. For example, if the skin moisture measurement results diagnose dry skin, the management device (110) can generate a makeup draft by selecting a foundation enhanced with moisturizing ingredients. Additionally, the management device (110) can recommend beauty products that suit the user's taste by referring to the beauty purchase history obtained in step S620. For example, if the user has a history of frequently purchasing lipstick of a specific brand, the management device (110) can include a new lipstick product of that brand in the makeup draft.

[0072] FIG. 7 illustrates a flowchart showing a method (S700) according to one embodiment of the present disclosure.

[0073] Referring to FIG. 7, the method (S700) can be performed by a management device (110).

[0074] In step S710, the management device (110) can recommend a list of beauty experiences associated with a makeup draft. The management device (110) can analyze the characteristics of the generated makeup draft. Based on the analysis results, the management device (110) can suggest useful offline or online linked services to the user. Such recommendations can contribute to expanding the user's beauty experience and increasing satisfaction with the service. The management device (110) can transmit the recommended list of beauty experiences to the user terminal (120) for display.

[0075] In one embodiment of the present disclosure, the method (S700) may further include the step of recommending a beauty experience list associated with a makeup sample. The beauty experience list may include a makeup experience, a photography experience, or a precision diagnosis experience. For example, the beauty experience list may include a makeup experience, a photography experience, a precision diagnosis experience, personal color consulting, a beauty class, participation in a new product launch event, or a visit to a brand pop-up store. However, the present disclosure is not limited thereto. A makeup experience may be a service of receiving makeup directly from a professional using products presented in the makeup sample. A photography experience may be a service of taking a profile photo at a professional studio after applying recommended makeup techniques. A precision diagnosis experience may be a service of measuring and analyzing skin condition in greater detail using professional equipment.

[0076] In one embodiment of the present disclosure, step S710 may include identifying brand information of a beauty product included in a generated cosmetic design, and generating a beauty experience list including a promotion or event associated with the identified brand information. The management device (110) may acquire geographical location information of the user. Based on the acquired geographical location information, the management device (110) may prioritize recommending beauty experiences available near the user.

[0077] FIG. 8 illustrates a flowchart showing a method (S800) according to one embodiment of the present disclosure.

[0078] Referring to FIG. 8, the method (S800) can be performed by a management device (110).

[0079] In step S810, the management device (110) can obtain a list of beauty products preferred by the user. The management device (110) can receive the user's purchase history data from the user terminal (120). Alternatively, the management device (110) can receive preferred product information directly entered by the user through the interface of the user terminal (120). The beauty product list may include detailed information such as product name, brand, color code, formulation, etc.

[0080] In step S820, the management device (110) can generate a makeup comparison draft for the face based on a beauty product list. The management device (110) can virtually apply each product included in the acquired beauty product list to the corresponding facial area of ​​the target image. Through this, a makeup comparison draft, which is a new makeup draft reflecting the user's preference, can be generated.

[0081] In one embodiment of the present disclosure, the step of generating a makeup comparison draft may virtually apply a beauty product included in a beauty product list to at least one area of ​​the face of a target image. If there is no beauty product corresponding to a specific face area in the beauty product list, the management device (110) may generate a makeup comparison draft by virtually applying a beauty product applied to a specific face area in a makeup draft to the specific face area. For example, if there is no eyeshadow product in the user's beauty product list, the management device (110) may generate a complete makeup comparison draft by virtually applying an eyeshadow product included in a makeup draft recommended by artificial intelligence.

[0082] In step S830, the management device (110) can transmit display information to the user terminal (120) so that the makeup draft and the makeup comparison draft are displayed on the same screen. The management device (110) can generate user interface (UI) data that allows the two drafts to be compared side by side. The generated data can be transmitted to the user terminal (120) and rendered on the screen.

[0083] In one embodiment of the present disclosure, the step of transmitting display information to a user terminal (120) may display a makeup draft and a makeup comparison draft on a screen divided into left and right sides, respectively. Additionally, display information may be transmitted to the user terminal (120) to highlight and display beauty product information that is applied differently between the makeup draft and the makeup comparison draft. For example, if the AI-recommended lipstick and the user's preferred lipstick are different, the lipstick product information of each draft is visually highlighted so that the user can easily recognize the difference.

[0084] In one embodiment of the present disclosure, the step of transmitting display information to a user terminal (120) may include the step of transmitting a discount promotion regarding a target beauty product to the user terminal (120). The target beauty product may be a product that is not present in the beauty product list and is not applied to the makeup comparison draft, but is applied only to the makeup draft. This can be utilized as a marketing strategy to induce the purchase of a recommended product that the user does not possess.

[0085] FIG. 9 illustrates a cosmetic design screen (900) that may be referenced in various embodiments of the present disclosure.

[0086] Referring to FIG. 9, the makeup draft screen (900) may be a user interface screen that displays a makeup draft generated according to various embodiments of the present disclosure. The makeup draft screen (900) may be generated by a management device (110), transmitted to a user terminal (120), and displayed on a display. Through the makeup draft screen (900), the user can intuitively check a virtual makeup result optimized for their facial characteristics analyzed based on artificial intelligence.

[0087] The makeup preview screen (900) may include an image in which a beauty product is virtually applied to a target image containing the user's face. Additionally, the makeup preview screen (900) may display detailed information about the beauty product applied to a specific area of ​​the face. For example, as illustrated in FIG. 9, information about a blush product applied to the cheek area and information about a lipstick product applied to the lip area may be displayed by matching them with the respective facial areas. This product information may include the product name, brand, color code, formulation, and purchase link.

[0088] The virtual makeup displayed on the makeup draft screen (900) can be generated based on the results of a comprehensive analysis of the user's skin tone, skin type, personal color, etc. by the management device (110). The management device (110) can select the products most suitable for the analysis results from among a plurality of beauty products stored in a database. The selected beauty products can be precisely applied to the corresponding facial area of ​​the target image through Augmented Reality (AR) technology or Computer Graphics technology to generate a makeup draft.

[0089] In one embodiment of the present disclosure, the makeup draft screen (900) may be used for displaying a plurality of makeup drafts for comparison. For example, the makeup draft screen (900) may be divided into left and right sides, and on one side, a makeup draft recommended by the management device (110) may be displayed. On the other side, a makeup comparison draft generated based on a list of beauty products preferred by the user may be displayed. In this case, the makeup draft screen (900) may help the user easily recognize the difference by visually highlighting the beauty product information applied differently between the two drafts.

[0090] In one embodiment of the present disclosure, the makeup draft screen (900) may include marketing information to induce the purchase of beauty products. For example, if there is no product corresponding to a specific facial area in the beauty product list preferred by the user, and the product is not applied to the makeup comparison draft, the makeup draft screen (900) may provide information about the product. Specifically, the makeup draft screen (900) may increase the user's purchase conversion rate by displaying discount coupons or promotional information regarding target beauty products applied only to AI-recommended makeup drafts.

[0091] Although the operations included in the method of the present disclosure have been described in a sequential order according to the flowchart in which the method is illustrated, the operations included in the method of the present disclosure may be executed in any other combination. Furthermore, detailed changes or modifications may be made to the operations included in the method of the present disclosure, and the fact that such operations are included in the flowchart does not imply that they are essential for executing the method of the present disclosure. In one embodiment, at least some of the operations included in the method of the present disclosure may be performed in parallel, iteratively, or heuristically. Additionally, in another embodiment, at least some of the operations included in the method of the present disclosure may be omitted.

[0092] Various embodiments of the present disclosure may be implemented as software on a machine-readable storage medium (MRSM). Additionally, software may be inferred from the various embodiments of the present disclosure by a person skilled in the art to which the present disclosure pertains. For example, the software may be a computer program containing instructions that can be read by a computing device. In one embodiment, the processor of the computing device may execute a called instruction to cause the components of the computing device to perform a function corresponding to that instruction. The storage medium may refer to any type of recording medium in which information that can be read by a device is stored. The storage medium may include, for example, ROM, RAM, CD-ROM, magnetic tape, floppy disk, or optical information storage device. In one embodiment, the storage medium may be implemented in a distributed form in a networked computer system, etc. Here, the software may be stored in a distributed manner in a computer system, etc. Additionally, in another embodiment, the storage medium may be a non-transitory storage medium. Non-transient storage media refer to media that exist regardless of whether information is stored semi-permanently or temporarily, and do not include signals that are transmitted transiently.

[0093] A method according to one embodiment of the present disclosure may be provided by being included in a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., Compact Disc Read Only Memory (CD-ROM)) or distributed online (e.g., download or upload) through an application store or directly between two user devices (e.g., smartphones). In the case of online distribution, at least a portion of the computer program product (e.g., downloadable app) may be temporarily stored or temporarily created on a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0094] Although the technical concept according to the present disclosure has been described by various embodiments above, the technical concept according to the present disclosure includes various substitutions, modifications, and changes that can be made within the scope of understanding by a person skilled in the art to which the present disclosure pertains. Furthermore, such substitutions, modifications, and changes should be interpreted as being included within the scope of the claims.

Claims

Claim 1 A method performed by an electronic device comprises: acquiring a target image in which a user's face is captured; performing an analysis including skin tone, skin type, personal color, and contour regarding the face based on the target image; generating a makeup draft suitable for the face based on the target image and the result of the analysis; and transmitting the makeup draft to the user's terminal, wherein the makeup draft is an image that displays a matching of at least one region of the face and a beauty product applied to the region, and the step of performing the analysis comprises: extracting a plurality of facial feature points from the target image; and distinguishing a plurality of facial regions based on the plurality of facial feature points. The method comprises the step of calculating a color value representing the skin tone and an oil-moisture index representing the skin type based on an analysis algorithm that analyzes the texture, gloss, and fine wrinkles of an image for each of the plurality of facial regions, wherein the plurality of facial feature points include the ends of the user's eyes, the tip of the nose, the nostrils, the ends of the lips, the jawline, the boundary of the forehead, and the protrusion of the cheekbones extracted based on a facial detection algorithm, and the method further comprises the step of obtaining a precise diagnostic result including the measurement result of a diagnostic device regarding the user's face, the actual measurement result of personal color, and the comment of a makeup artist; and the step of obtaining the user's beauty purchase history, wherein the step of generating a makeup draft includes the step of generating a makeup draft suitable for the face based on the precise diagnostic result and the beauty purchase history, and the method further comprises the step of obtaining a list of beauty products preferred by the user; and the step of generating a makeup comparison draft regarding the face based on the beauty product list.The method further comprises the step of transmitting display information to the user terminal such that the makeup draft and the makeup comparison draft are displayed on the same screen, wherein the step of generating the makeup comparison draft includes the step of virtually applying a beauty product included in the beauty product list to at least one area of ​​the face of the target image, and if there is no beauty product corresponding to the specific face area in the beauty product list, the step of virtually applying a beauty product applied to the specific face area in the makeup draft to the specific face area to generate the makeup comparison draft, wherein the step of transmitting the display information to the user terminal includes the step of transmitting display information to the user terminal such that the makeup draft and the makeup comparison draft are each displayed on a screen divided left and right, and that beauty product information applied differently between the makeup draft and the makeup comparison draft is highlighted and displayed, and wherein the step of transmitting the display information to the user terminal includes the step of transmitting a discount promotion to the user terminal regarding a target beauty product that is not present in the beauty product list and is not applied to the makeup comparison draft, but is applied only to the makeup draft. Claim 2 delete Claim 3 The method of claim 1 further comprises the step of recommending a beauty experience list associated with the makeup design, wherein the beauty experience list includes a makeup experience, a photography experience, or a precision diagnosis experience. Claim 4 delete Claim 5 delete

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