Equipment and methods for providing beauty consultation information

Abstract

A method and apparatus for providing beauty consultation information are disclosed, which can generate and provide beauty consultation information by executing artificial intelligence (AI) algorithms and / or machine learning algorithms in a 5G environment connected to the Internet of Things. The method for providing beauty consultation information according to embodiments of this disclosure may include: generating a first image set based on shooting information for each predetermined time period, the first image set having categorized a plurality of previously stored images; generating a second image set based on the purpose of providing consultation information, the second image set having categorized a plurality of images contained in the first image set; calculating body features by comparative analysis of the plurality of images contained in the second image set; and providing beauty consultation information when the amount of change between the calculated body features and previously stored existing body features exceeds a predetermined value.

Description

[0001] Cross-reference to related applications

[0002] This application claims the benefit of priority to Korean Patent Application No. 10-2019-0100132, filed on August 16, 2019, entitled “Apparatus and Method for Providing Beauty Consultation Information”, the disclosure of which is incorporated herein by reference. Technical Field

[0003] This disclosure relates to a method and apparatus for providing beauty consultation information, and more specifically, to a method and apparatus for providing beauty consultation information, which calculates body characteristics from a plurality of pre-stored images by analyzing a set of images classified based on the purpose of providing information, and provides beauty consultation information based on the body characteristics. Background Technology

[0004] With increasing life expectancy, there is a greater desire for the diagnosis and management of health conditions. Obesity refers to the excessive accumulation of body fat, caused by a prolonged energy imbalance resulting from energy intake exceeding energy expenditure. Factors such as dietary changes, reduced physical activity, and genetic factors like age, race, and family history have been identified as contributing to obesity. The skin, the part of the body exposed to the external environment, contains various metabolic products and components, and sometimes even serves as an indicator of health status.

[0005] Related technology 1 discloses the use of body mass index (BMI) to diagnose obesity and the use of fitness equipment to recommend fitness equipment to each user by monitoring changes in BMI.

[0006] Related technology 2 discloses the ability to diagnose and manage skin conditions by installing a portable spectral imaging device on a user terminal such as a smartphone or tablet.

[0007] As mentioned above, the diagnosis of obesity and skin conditions is performed using electronic devices such as skin diagnostic devices or obesity measurement devices that come into direct contact with the user. However, diagnostic methods using obesity measurement devices and skin diagnostic devices have low accuracy and are highly dependent on the experience of the person providing the diagnostic results. Furthermore, monitoring of obesity and skin conditions used for diagnosing health conditions requires continuous monitoring. Therefore, there is a need for a method that can be more easily implemented without causing discomfort to the user.

[0008] The above background information is technical information possessed by the inventors in order to obtain the present invention, or technical information obtained by the inventors in the process of obtaining the present invention. Therefore, it should not be interpreted as technology known before the filing date of the present invention.

[0009] Related technical documents

[0010] Patent Literature

[0011] Prior Art 1: Korean Patent Application Publication No. 10-2017-0109962 (published on October 10, 2017)

[0012] Prior Art 2: Korean Patent Application Publication No. 10-2016-0119400 (published on October 13, 2016) SUMMARY

[0013] An object of the present disclosure is to solve the problem in the prior art that it is difficult to measure the degree of obesity and skin condition by using an electronic device such as an obesity degree measuring device, a skin diagnosis device, and continuously monitor the user.

[0014] Another object of the present disclosure is to solve the problem in the prior art that the use of an electronic device such as an obesity degree measuring device, a skin diagnosis device, in measuring the degree of obesity and skin condition in the case of contacting the user can cause the user to be uncomfortable.

[0015] Still another object of the present disclosure is to calculate a body feature by analyzing an image photographed and stored by the user, and provide the user with beauty consultation information according to the body feature, thereby making the user be aware of the body health.

[0016] Still another object of the present disclosure is to calculate the degree of obesity by analyzing an image photographed and stored by the user, and provide the user with beauty consultation information related to obesity according to the degree of obesity, thereby making the user be aware of obesity.

[0017] Still another object of the present disclosure is to generate skin condition information by analyzing an image photographed and stored by the user, and provide the user with consultation information related to skin according to the skin condition information, thereby making the user be aware of skin care.

[0018] The beauty consultation information providing method of the present disclosure embodiment can include calculating a body feature by analyzing a group of images classified based on a provision of information purpose from among a plurality of pre-stored images, and providing beauty consultation information according to the body feature.

[0019] In detail, the cosmetic consultation information providing method according to an embodiment of the disclosure can include generating a first image set having classified a plurality of images previously stored based on photographed information for each predetermined period of time, generating a second image set having classified the plurality of images contained in the first image set based on a purpose of providing consultation information, calculating a body feature by performing comparative analysis on the plurality of images contained in the second image set, and providing the cosmetic consultation information when a variation amount between the calculated body feature and an existing body feature previously stored exceeds a predetermined value.

[0020] Through the cosmetic consultation information providing method according to the embodiment, a body feature can be calculated by analyzing images photographed and stored by a user, and cosmetic consultation information can be provided to the user according to the body feature to cause the user to be aware of health, thereby achieving body health care.

[0021] In addition, generating the second image set can include generating the second image set having classified the plurality of images contained in the first image set as images containing at least a part of a body part based on a purpose of providing consultation information on a degree of obesity.

[0022] In addition, calculating the body feature can include separating a region including a body and a region not including the body from the plurality of images contained in the second image set, detecting an edge of the region including the body, and calculating a curvature of the edge.

[0023] In addition, providing the cosmetic consultation information can include providing cosmetic consultation information including obesity-related information when a variation amount between the curvature and an existing curvature previously stored exceeds a predetermined value.

[0024] In addition, generating the second image set can include generating a second image set classified to include face images based on a purpose of providing consultation information on a degree of skin aging from the plurality of images contained in the first image set.

[0025] In addition, calculating the body feature can include detecting a face region from the plurality of images contained in the second image set, and generating skin condition information including one or more of a sheen, pores, wrinkles, fine wrinkles, pigmentation, skin redness, and sebum from the face region.

[0026] In addition, providing the cosmetic consultation information can include providing cosmetic consultation information including skin aging-related information when a variation amount between the skin condition information and existing skin condition information previously stored exceeds a predetermined value.

[0027] The cosmetic consultation information providing apparatus of the present embodiment can include a first generator configured to generate a first image set having classified a plurality of images previously stored, based on photographed information for each predetermined period of time; a second generator configured to generate a second image set having classified the plurality of images contained in the first image set, based on a purpose of providing consultation information; an analyzer configured to calculate a body feature by comparative analysis of the plurality of images contained in the second image set; and a provider configured to provide cosmetic consultation information when a variation amount between the calculated body feature and an existing body feature previously stored exceeds a predetermined value.

[0028] With the cosmetic consultation information providing apparatus of the present embodiment, a body feature can be calculated by analyzing images photographed and stored by a user, and cosmetic consultation information can be provided to the user according to the body feature to cause the user to be aware of health, thereby achieving body health care.

[0029] In addition, the second generator can be configured to generate a second image set classified to contain face images, based on a purpose of providing consultation information on a degree of skin aging from the plurality of images contained in the first image set.

[0030] In addition, the analyzer can be configured to separate a region including a body and a region not including the body from the plurality of images contained in the second image set, detect an edge of the region including the body, and calculate a curvature of the edge.

[0031] In addition, the provider can be configured to provide cosmetic consultation information including obesity-related information when a variation amount between the curvature and an existing curvature previously stored exceeds a predetermined value.

[0032] In addition, the second generator can be configured to generate a second image set classified to contain face images, based on a purpose of providing consultation information on a degree of skin aging from the plurality of images contained in the first image set.

[0033] In addition, the analyzer can be configured to detect a face region from the plurality of images contained in the second image set, and generate skin condition information including one or more of shine, pores, wrinkles, fine wrinkles, pigmentation, skin redness, and sebum from the face region.

[0034] In addition, the provider can be configured to provide cosmetic consultation information including skin aging-related information when a variation amount between the skin condition information and existing skin condition information previously stored exceeds a predetermined value.

[0035] In addition, other methods and other systems for implementing the present disclosure and computer readable media for storing computer programs for executing the above-described methods can be further provided.

[0036] Other aspects, features, and advantages will become apparent from the following drawings, claims, and detailed description.

[0037] According to the present disclosure, obesity and skin conditions can be continuously monitored by measuring obesity and skin conditions on an image photographed by a user, so that the user can lead a healthy life by continuously taking care of obesity and skin.

[0038] In addition, obesity and skin conditions can be measured on an image photographed by a user without the user having to contact electronic devices such as an obesity measuring device or a skin diagnosis device, thereby solving the problem of the related art that can cause the user to be uncomfortable when measuring.

[0039] In addition, a body feature can be calculated by analyzing an image photographed and stored by a user, and beauty consultation information can be provided to the user according to the body feature, so that the user can be alert to body health, thereby achieving body care.

[0040] In addition, obesity can be calculated by analyzing an image photographed and stored by a user, and beauty consultation information related to obesity can be provided to the user according to the obesity, so that the user can be alert to obesity, thereby achieving obesity care.

[0041] In addition, skin condition information can be calculated by analyzing an image photographed and stored by a user, and beauty consultation information related to skin aging can be provided to the user according to the skin condition, so that the user can be alert to skin care, thereby achieving skin care.

[0042] Effects of the present disclosure are not limited to those mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1 is a diagram for illustratively explaining a beauty consultation information providing system according to an embodiment of the present disclosure.

[0044] Figure 2 is a diagram for illustratively explaining Figure 1 a detailed structure of a beauty consultation information providing device of the beauty consultation information providing system.

[0045] Figure 3 is a diagram for illustratively explaining Figure 2 a detailed structure of a beauty consultation information manager of the beauty consultation information providing device.

[0046] Figure 4is a diagram for illustratively explaining a beauty consultation information providing system according to another embodiment of the present disclosure.

[0047] Figure 5 is a diagram for illustratively explaining a beauty consultation information providing system according to still another embodiment of the present disclosure.

[0048] Figure 6 is a diagram of beauty consultation information provided by a beauty consultation information providing apparatus according to an embodiment of the present disclosure.

[0049] Figure 7 is a diagram of beauty consultation information provided by a beauty consultation information providing apparatus according to another embodiment of the present disclosure.

[0050] Figure 8 is a flowchart for explaining a beauty consultation information providing method according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0051] The advantages and features of the present disclosure and methods for achieving them will become apparent from the following description with reference to the accompanying drawings. However, the description of the specific exemplary embodiments is not intended to limit the present disclosure to the particular exemplary embodiments disclosed herein, but rather, it is to be understood that the present disclosure will cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present disclosure. The exemplary embodiments disclosed in the following are provided so that the present disclosure will be thorough and complete, and will fully convey the scope of the present disclosure to those skilled in the art. For the purpose of clarity, all technical and scientific terms used in the specification have the same meaning as commonly understood by one of ordinary skill in the art to which the present disclosure belongs. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this present disclosure belongs. The terminology used in the description of the exemplary embodiments herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of the present disclosure. It should be understood that the use of "including", "comprising", "having" and "with" are not intended to exclude other elements or steps. Throughout this specification, unless otherwise indicated, the use of the term "and / or" means "and, or, and / or". The use of the terms "first", "second", and / or other numerical terms does not connote any order, quantity, composition, or importance, but rather are used to distinguish one element from another. In addition, the use of "a" and / or "an" does not exclude a plurality and "multiple" and "plurality" are interchangeable, unless otherwise indicated.

[0052] The terminology used herein is for the purpose of describing particular example embodiments only and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. The terms "comprises", "comprising", "including", "having" and "with" are inclusive and therefore specify the presence of stated features, integers, steps, operations, elements, and / or components but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. Further, these terms, such as "first", "second" and other numerical terminology, are used to distinguish one element from another element but are not otherwise limiting. These terms are generally only used to distinguish one element from another element.

[0053] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. Throughout the specification, like drawing reference numerals will be used to designate like elements, and repetitive description of the elements will not be provided.

[0054] Figure 1is a diagram for illustratively explaining a beauty consultation information providing system according to an embodiment of the present disclosure. Referring to Figure 1 , the beauty consultation information providing system 1 can include a beauty consultation information providing apparatus 100, a user terminal 200, a server 300, and a network 400.

[0055] The beauty consultation information providing apparatus 100 can generate a first image set based on photographed information, the first image set having classified a plurality of images stored at each predetermined time period.

[0056] Here, the predetermined time period can include a certain period including several days to several weeks. In addition, the predetermined time period can include a generation time of photographing event information in which the user starts photographing. Here, the generation time of photographing event information can include a time at which a shutter input signal input by the user is received from the user terminal 200. That is, every time the photographing event information is generated, the beauty consultation information providing apparatus 100 can generate the first image set. If the photographing event information is successfully generated a plurality of times, the first image set can be generated by using images generated from the time at which the image after the previous photographing event information has been generated until the time at which the last photographing event information is generated.

[0057] In addition, the photographing information can include photographing mode information of the user terminal 200 when the image is photographed, and for example, the photographing information can include a self-photographing mode, a continuous photographing mode, and a moving image photographing mode, etc. In addition, the photographing information can include photographing setting information as metadata stored together when the image is stored, and for example, the photographing setting information can include one or more of brightness, contrast, saturation, color, gamma, exposure, ISO sensitivity, aperture, and shutter speed of the photographed image.

[0058] The beauty consultation information providing apparatus 100 can generate a second image set having classified a plurality of images included in the first image set based on a purpose of providing consultation information. Here, the purpose of providing consultation information can include one or more of obesity degree and skin aging degree, and can be set to one or more by the user.

[0059] In the case of a purpose of providing consultation information about obesity degree, the plurality of images included in the second image set can be images including body parts (face, chest, waist, arm, leg, and hip, etc.) in which at least some of the plurality of images included in the first image set are bare. For example, it can be seen that at least the arm and the leg of the user are bare in an image in which the user is wearing a swimsuit, and at least the leg of the user is bare in an image in which the user is wearing shorts.

[0060] In addition, in the case of providing consultation information about the degree of skin aging, the plurality of images included in the second image set can include an image including a face among the plurality of images included in the first image set.

[0061] The beauty consultation information providing apparatus 100 can calculate a body feature by performing comparative analysis on the plurality of images included in the second image set. Since the second image set can include a plurality of images, calculating an average value thereof after calculating a body feature for each image can be a body feature.

[0062] In the case of providing consultation information about the degree of obesity, the body feature can separate a region including a body and a region not including a body from the plurality of images included in the second image set, detect an edge of the region including a body, and include a result of calculating a curvature of the edge.

[0063] In the case of providing consultation information about the degree of skin aging, the body feature can detect a face region from the plurality of images included in the second image set, and include a result of generating skin condition information including one or more from face region information including gloss, pores, wrinkles, fine wrinkles, pigmentation, skin redness, and sebum.

[0064] The beauty consultation information providing apparatus 100 can provide beauty consultation information when a change amount between the calculated body feature and a previously stored existing body feature exceeds a predetermined value.

[0065] Here, the beauty consultation information can include a value of the degree of obesity (for example, including being xx Kg fatter than in the past), and a future body image compared to the current body image. Here, the future body image can include an image that is fatter than the current body image. To this end, the beauty consultation information providing apparatus 100 can output a prediction result of the future body image by analyzing information about a body using a deep neural network model previously trained, thereby outputting a prediction result of a user body image at a specific future time by analyzing user body-related information including a body image of the user, a curvature calculation result, and time information at which the body image has been photographed.

[0066] In addition, the beauty consultation information can include a value of a degree of skin aging (e.g., older by XX years than last year), and a future facial image compared to a current facial image. Here, the future facial image can include an image older than the current facial image. To this end, the beauty consultation information providing apparatus 100 can output a prediction result of a future facial image by analyzing facial-related information using a previously trained deep neural network model, thereby outputting a prediction result of a user's facial image at a specific future time by analyzing facial-related information of a user including a facial image of the user, a result of generating skin condition information, and time information of a facial image that has been photographed.

[0067] As an optional embodiment, the beauty consultation information providing apparatus 100 can provide exercise information and / or diet information for solving obesity as recommendation information when providing consultation information about obesity. In addition, the beauty consultation information providing apparatus 100 can provide skin care information and / or diet information and / or program information that can alleviate skin aging as recommendation information when providing skin aging degree consultation information.

[0068] The user terminal 200 can receive a service for driving or controlling the beauty consultation information providing apparatus 100 through an authentication process after accessing a driving application of the beauty consultation information providing apparatus or a driving website of the beauty consultation information providing apparatus. In the present embodiment, the user terminal 200 that has completed the authentication process can drive the beauty consultation information providing apparatus 100 and control the operation of the beauty consultation information providing apparatus 100.

[0069] The user terminal 200 can include a communication terminal capable of performing a function of a computing apparatus and performing a function of photographing an image. In the present embodiment, the user terminal 200 can include, but is not limited to, a desktop computer 201, a smart phone 202, a notebook 203, a tablet, a smart TV, a cell phone, a personal digital assistant (PDA), a notebook computer, a media player, a micro server, a global positioning system (GPS) apparatus, an electronic book terminal, a digital broadcasting terminal, a navigation apparatus, a kiosk, an MP3 player, a digital camera, a home appliance, and other mobile or fixed computing apparatuses operated by a user. Further, the user terminal 200 can be a wearable terminal having a communication function and a data processing function, such as a watch, glasses, a headband, or a ring. The user terminal 200 is not limited to the above-described apparatuses, and thus can employ any terminal supporting web browsing.

[0070] The server 300 can be a database server for providing big data required to apply various artificial intelligence algorithms and data for operating the beauty consultation information providing apparatus 100. In addition, the server 300 can include a web server or an application server capable of controlling the beauty consultation information providing apparatus 100 operation by using a driving application of the beauty consultation information providing apparatus or a driving web browser of the beauty consultation information providing apparatus, which has been installed on the user terminal 200.

[0071] Here, artificial intelligence (AI) is a field of computer engineering and information technology for researching methods of making computers think, learn, and self-develop, etc. in imitation of human intelligence, and can express intelligent behavior of computers imitating humans.

[0072] In addition, artificial intelligence itself does not exist, but it is directly or indirectly related to many other fields in computer science. In recent years, many attempts have been made to introduce elements of AI into various fields of information technology to solve problems in each field.

[0073] Machine learning is a field of artificial intelligence that includes a research field in which a computer learns without explicit programming. Specifically, machine learning can be a technology for researching and constructing a system for learning, predicting, and improving its own performance based on experience data and its algorithm. A machine learning algorithm can be employed instead of only executing a strictly set static program command as a method for constructing a model for making predictions and decisions from input data.

[0074] The server 300 can receive the plurality of images included in the second image set from the beauty consultation information providing apparatus 100, and calculate body features through comparative analysis of the plurality of images included in the second image set. When a change amount between the calculated body features and previously stored existing body features exceeds a predetermined value, the server 300 can generate beauty consultation information to be transmitted to the beauty consultation information providing apparatus 100. The server 300 can generate and learn a deep neural network model in order to generate the beauty consultation information.

[0075] According to the processing capacity of the beauty consultation information providing apparatus 100, at least some of the calculation of body features and the generation of beauty consultation information can be performed through the beauty consultation information providing apparatus 100.

[0076] The network 400 can be used to connect the beauty consultation information providing apparatus 100, the user terminal 200, and the server 300. For example, the network 400 can include a wired network such as a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), and an integrated services digital network (ISDN), or a wireless network such as a wireless LAN, CDMA, Bluetooth, and satellite communication, but the scope of the present disclosure is not limited thereto. In addition, the network 400 can transmit and receive information using short distance communication or long distance communication. Here, the short distance communication can include Bluetooth, radio frequency identification (RFID), infrared data association (IrDA), ultra wideband (UWB), ZigBee, and wireless fidelity (Wi-Fi) technology.

[0077] The long distance communication can include code division multiple access (CDMA), frequency division multiple access (FDMA), time division multiple access (TDMA), orthogonal frequency division multiple access (OFDMA), and single carrier frequency division multiple access (SC-FDMA) technology.

[0078] The network 400 can include a connection of network elements such as a hub, a bridge, a router, a switch, and a gateway. The network 400 can include one or more connected networks, including a public network such as the Internet and a private network such as a secure corporate private network.

[0079] For example, the network can include a multi-network environment. Access to the network 400 can be provided via one or more wired or wireless access networks. In addition, the network 400 can support 5G communication or the Internet of Things (IoT) for exchanging and processing information between distributed elements such as objects.

[0080] Figure 2 is a detailed structural diagram of a beauty consultation information providing apparatus in a beauty consultation information providing system. Figure 1 Hereinafter, in order to avoid repetitive description, the common parts previously described with reference to Figure 1 are omitted. With reference to Figure 2 , the beauty consultation information providing apparatus 100 can include a transceiver 110, a storage medium 120, a program memory 130, a database 140, a beauty consultation information manager 150, and a controller 160.

[0081] The transceiver 110 is interlocked with the network 400 to provide a communication interface required for providing transmission / reception signals in the form of packet data between the beauty consultation information providing apparatus 100 and / or the user terminal 200 and / or the server 300. In addition, the transceiver 110 can be used to receive a predetermined information request signal from the user terminal 200 and to transmit information processed by the beauty consultation information providing apparatus 100 to the electronic user terminal 200. In addition, the transceiver 110 can transmit the predetermined information request signal received from the electronic user terminal 200 to the server 300 and can transmit a response signal to the user terminal 200. In addition, the transceiver 110 can be an apparatus including hardware and software required to transmit and receive signals (e.g., control signals and data signals) to another network apparatus through a wired or wireless connection.

[0082] In addition, the transceiver 110 can support various object-to-object intelligent communications, such as Internet of Things (IoT), Internet of Everything (IoE), and Internet of Small Things (IoST), and can support, for example, Machine to Machine (M2M) communication, Vehicle to Machine (V2X) communication, and Device to Device (D2D) communication.

[0083] In the present embodiment, the storage medium 120 can temporarily or permanently store data processed by the controller 160. In addition, the storage medium 120 can store various information required for the operation of the beauty consultation information providing apparatus 100, and include a volatile or non-volatile recording medium. In addition, the storage medium 120 can store a plurality of images photographed by a user.

[0084] Here, the storage medium 120 can include a magnetic storage medium or a flash memory storage medium, but the present disclosure is not limited thereto. The storage medium 120 can include an internal memory and an external memory, and can include a volatile memory such as DRAM, SRAM, or SDRAM; a non-volatile memory such as One Time Programmable ROM (OTPROM), PROM, EPROM, EEPROM, mask ROM, flash ROM, NAND flash, or NOR flash; and a storage device such as HDD or a flash drive such as SSD, CF card, SD card, micro-SD card, mini-SD card, Xd card, or memory stick.

[0085] The program memory 130 can install control software for performing each of the following tasks: generating a first image set that has classified a plurality of images previously stored based on the photographed information for each predetermined period of time; generating a second image set that has classified a plurality of images contained in the first image set based on the purpose of providing consultation information; calculating a body feature by performing comparative analysis on the plurality of images contained in the second image set; providing the beauty consultation information when the amount of change between the calculated body feature and the existing body feature previously stored exceeds a predetermined value; providing exercise information and / or diet information capable of solving obesity as recommendation information when the consultation information on the degree of obesity is included in the beauty consultation information; and providing skin care information and / or diet information and / or program information capable of reducing skin aging as recommendation information when the consultation information on the degree of skin aging is included in the beauty consultation information, etc.

[0086] The database 140 can include a management database for storing information collected and generated by the beauty consultation information providing apparatus 100. Here, the management database can store first image set generation information, second image set generation information, existing body feature information, existing skin condition information, calculated body curvature information, generated facial skin condition information, time information for generating the beauty consultation information, recommendation information including exercise information and diet information capable of solving obesity, and recommendation information including skin care information, diet information, and process information capable of reducing skin aging.

[0087] In addition, the database 140 can further include a user database for storing basic information about a user. Here, the user database can store user information about a user who wants to receive beauty consultation information. Here, the user information can include: basic information about the user such as name, affiliation, personal data, gender, age, contact information, e-mail, and address; authentication (login) information such as ID (or e-mail) and password; information about access such as access country, access location, information about a device used for access, and a network environment accessed. In addition, the user database can include information about the amount of change in the cumulative curvature of the body of each user, information about the amount of change in the cumulative skin condition of the skin of the face, information about the amount of change in the calculated curvature, information about the amount of change in the skin condition of the face, and time information for generating the beauty consultation information.

[0088] The beauty consultation information manager 150 can generate a first image set based on shooting information, which has been classified into multiple images stored for each predetermined time period; generate a second image set based on the purpose of providing consultation information, which has been classified into multiple images contained in the first image set; calculate body characteristics by comparing and analyzing the multiple images contained in the second image set; and provide beauty consultation information when the amount of change between the calculated body characteristics and the previously stored existing body characteristics exceeds a predetermined value.

[0089] In this embodiment, the beauty consultation information manager 150 can perform learning in conjunction with the controller 160 or receive learning results from the controller 160. In this embodiment, the beauty consultation information manager 150 can also be located outside the controller 160 (e.g., Figure 2 (As shown), it can also be set inside the controller 160 to operate like the controller 160, and can also be set in Figure 1 The internal server 300. See below for reference. Figure 3 Detailed description of Beauty Consultation Information Manager 150.

[0090] The controller 160 can control the overall operation of the beauty consultation information providing device 100 as a central processing unit by driving control software installed in the program memory 130. The controller 160 may include any type of device capable of processing data, such as a processor. Here, the term "processor" can refer to an embedded hardware data processing device, such as one having physical circuitry for executing instructions or code included in a program. Examples of embedded hardware data processing devices may include microprocessors, central processing units (CPUs), processor cores, multiprocessors, application-specific integrated circuits (ASICs), and field-programmable gate arrays (FPGAs), but the scope of this disclosure is not limited thereto.

[0091] In this embodiment, the controller 160 can perform machine learning, such as deep learning, on images collected within a predetermined time period, so that the beauty consultation information providing device 100 provides the best beauty consultation information, and the storage medium 120 can store data for machine learning, result data, etc.

[0092] Deep learning is a subfield of machine learning that allows for data-driven learning through multiple layers. As the number of layers in a deep learning network increases, it can acquire a set of machine learning algorithms that extract core data from multiple datasets.

[0093] Deep learning architectures can include artificial neural networks (ANNs), and can include convolutional neural networks (CNNs), recurrent neural networks (RNNs), and deep belief networks (DBNs), etc. The deep learning architectures according to this embodiment can use various structures well-known in the art. For example, the deep learning architectures according to this disclosure can include CNNs, RNNs, DBNs, etc. An RNN is an artificial neural network architecture formed by building layers at each instance; it is widely used in natural language processing and is effective for processing temporal data that varies over a series of time periods. A DBN comprises a deep learning architecture formed by stacking multiple layers of a deep learning scheme (Restricted Boltzmann Machine (RBM)). A DBN has a number of layers formed by repeatedly training an RBM. A CNN contains a model that simulates the function of the human brain, based on the assumption that when a person recognizes an object, the brain extracts the most basic features of that object and recognizes the object based on the results of complex processing within the brain.

[0094] Furthermore, artificial neural networks can be trained to produce the desired output from a given input by adjusting the connection weights between nodes (and, if necessary, the bias values). Moreover, artificial neural networks can continuously update their weight values ​​through learning. Additionally, methods such as backpropagation can be used for training artificial neural networks.

[0095] Meanwhile, the controller 160 can be equipped with an artificial neural network and can perform calculations of body characteristics based on machine learning and beauty consultation information by using user-collected images as input data.

[0096] Controller 160 may include an artificial neural network, such as a deep neural network (DNN) like a CNN, RNN, or DBN, and may learn the deep neural network. Machine learning paradigms (in which the ANN operates) may include unsupervised and supervised learning. Controller 160 may control the artificial neural network structure after learning, based on settings.

[0097] Figure 3 It is an illustrative illustration. Figure 1 A detailed diagram illustrating the structure of the beauty consultation information manager for the beauty consultation information providing device. In the following description, [the diagram is used in conjunction with...] Figure 1 and Figure 2 Repeated descriptions will be omitted. (Reference) Figure 3 The beauty consultation information manager 150 may include a first generator 151, a second generator 152, an analyzer 153, a provider 154, and a recommender 155.

[0098] The first generator 151 can generate a first image set in which a plurality of images stored in the storage medium 120 have been classified, based on shooting information for each predetermined time period. Here, the shooting information can include shooting mode information set by the user before shooting the images, for example, can include a self-shooting mode, a continuous shooting mode, a moving image shooting mode, etc. In addition, when the images are stored after shooting, the shooting information can include shooting setting information as metadata stored together, for example, the shooting setting information can include one or more of brightness, contrast, saturation, color, gamma, exposure, ISO sensitivity, aperture, and shutter speed of the shot images.

[0099] The first generator 151 can generate a first image set in which a plurality of images stored in the storage medium 120 have been classified for each predetermined time period, based on a self-shooting mode in which the user directly shoots his or her own. That is, the first generator 151 can generate images shot in a self-shooting mode in which the user directly shoots himself or herself in a plurality of images as a first image set. The images shot in the self-shooting mode can have similar shooting compositions, shooting distances, and shooting setting information, thereby improving the reliability of calculating body features.

[0100] In addition, the first generator 151 can generate a first image set in which a plurality of images stored in the storage medium 120 are classified as a plurality of images having the same shooting setting information including one or more of brightness, contrast, saturation, color, gamma, exposure, ISO sensitivity, aperture, and shutter speed for each predetermined time period. That is, the first generator 151 can generate images having the same shooting setting information as the first image set in a plurality of images.

[0101] In addition, the first generator 151 can convert a plurality of images stored in the storage medium 120 into a plurality of images having the same shooting setting information including one or more of brightness, contrast, saturation, color, gamma, exposure, ISO sensitivity, and in each predetermined time period, the shooting setting information is converted equally to the first image set, and a plurality of images are generated.

[0102] The plurality of images stored in the storage medium 120 can have the same photographing setting information or different photographing setting information. When the photographing setting information is different, reliability can decrease in calculating the body feature on the image to provide the beauty consultation information. Accordingly, the first generator 151 can convert the plurality of images having different photographing setting information into the plurality of images having the same photographing setting information at each predetermined time period and generate the plurality of images having the same photographing setting information as the first image set. To this end, the first generator 151 can further include an image processor capable of changing the photographing setting information. The image processor can convert and process each image so that one or more of luminance, contrast, saturation, color, gamma, exposure, ISO sensitivity, aperture, and shutter speed are the same.

[0103] As an optional embodiment, the image processor can reduce noise on the image stored in the storage medium 120 and perform gamma correction, color filter array interpolation, color matrix, color correction, color enhancement, etc. In addition, the image processor can perform functions such as color processing, blur processing, edge emphasis processing, image analysis processing, image recognition, and image effect processing. Face recognition, scene recognition, etc. can be performed to perform image recognition. For example, luminance level adjustment, color correction, contrast adjustment, contour enhancement adjustment, screen division processing, character image generation, and image synthesis processing can be performed. The image processor can be provided in the camera of the user terminal 200, provided in the first generator 151, provided in the analyzer 153, provided in the controller 160, or provided as a separate device.

[0104] The second generator 152 can generate a second image set in which the plurality of images included in the first image set have been classified based on a purpose of providing consultation information. That is, the second generator 152 can generate different second image sets according to the purpose of providing consultation information. Here, the purpose of providing consultation information can include one or more of obesity degree and skin aging degree.

[0105] In the case of the purpose of providing consultation information about the obesity degree, the second generator 152 can generate a second image set in which the plurality of images included in the first image set have been classified as images including at least partially exposed body parts. Here, the body can include a face, a neck, a shoulder, a chest, a waist, a hip, an arm, a leg, etc., and the second generator 152 can include images including the at least partially exposed body parts among the plurality of images included in the first image set in the second image set.

[0106] In the case of providing consultation information about the degree of skin aging, the second generator 152 can generate a second image set in which the plurality of images included in the first image set have been classified as images including faces. That is, the second generator 152 can include, in the second image set, images including faces among the plurality of images included in the first image set.

[0107] The analyzer 153 can calculate a body feature by performing comparative analysis on the plurality of images included in the second image set. In the present embodiment, the analyzer 153 can include a first analyzer 153-1 and a second analyzer 153-2 according to the purpose of providing consultation information.

[0108] In the case of providing consultation information about the degree of obesity, the first analyzer 153-1 can calculate a curvature variation amount of a body by performing comparative analysis on the plurality of images included in the second image set. In the present embodiment, the first analyzer 153-1 can include a first processor 153-11 and a first calculator 153-12.

[0109] The first processor 153-11 can separate a region including a body and a region not including a body from the plurality of images included in the second image set. Here, the region including a body can correspond to a foreground region in an image, and the region not including a body can correspond to a background region in an image. The first processor 153-11 can apply a Gaussian model to an image to determine whether a pixel thereof is a pixel of a foreground image or a pixel of a background image, thereby separating a region including a body and a region not including a body from the image.

[0110] The first processor 153-11 can detect an edge of the region including a body. Here, edge (contour) detection basically shows a contour at a boundary between two regions having different contrasts, and can detect a portion in which a luminance change of a pixel is greater than a threshold value by an operation. As an operation for detecting an edge, a Laplacian operation method or a Canny operation method can be applied. Since the Laplacian operation method uses a second derivative and shows only a point that recognizes a local maximum as a feature of a contour, only a contour present at a center of the contour can be shown, thereby showing a contour position. In the Canny operation method, a noise removal mask is used before detecting a contour, and various types of contour detection masks can be used so that only a strong contour can be effectively detected.

[0111] To calculate the curvature of the edge (contour), the first calculator 153-12 can extract a line forming the curvature and a curvature center point of the curvature for determining the curvature, and calculate the curvature by using a length (radius) and an angle from the center point of the curvature to the line forming the curvature.

[0112] Here, the first calculator 153-12 can calculate different curvatures according to body parts, and apply different weights when calculating the curvatures according to the body parts. For example, if body parts included in 10 images of the second image set include 10 faces, 3 chests, and 1 leg, the highest weight can be applied when calculating the curvature of the face, and the lowest weight can be applied when calculating the curvature of the leg. That is, different weights can be applied according to the exposure frequency of the body parts shown in the images. Later, the provider 154 can provide consultation information on the degree of obesity in response to the curvatures calculated by the first calculator 153-12, and provide a value on the degree of obesity for each body part of the user's full-body image so that the user can confirm the total change thereof.

[0113] In the case of providing consultation information on the degree of skin aging, the second analyzer 153-2 can generate skin condition information of a face by performing comparative analysis on the plurality of images included in the second image set. In the present embodiment, the second analyzer 153-2 can include a second processor 153-21 and a second calculator 153-22.

[0114] The second processor 153-21 can detect a face region from the plurality of images included in the second image set. The second processor 153-21 can remove a background region from the plurality of images included in the second image set, detect specific components (eyes, nose, mouth, etc.) in the face, and detect the specific components based on the specific components in the face region. The second processor 153-21 can extract face information including a face region from an image by using an Adaboost algorithm as a representative face detection algorithm.

[0115] The second processor 153-21 can generate skin condition information including one or more of shine, pores, wrinkles, fine wrinkles, pigmentation, skin redness, and sebum from the face region.

[0116] The second processor 153-21 can identify a shiny area compared to a surrounding gray value by using a cross mask method on a face region image, and can select the identified shiny area as a higher 2% brightness pixel value. The shiny area selected as the higher 2% brightness pixel value can be included in the user's skin condition information.

[0117] The second processor 153-21 can generate skin condition information of a user including pores by using the face region image. Since pores are relatively dark compared to the surrounding environment and have a circular shape, the second processor 153-21 can first detect dark regions from the face region image, and respectively detect and remove similar dark hair. The second processor 153-21 can separate pores having a small size or sparsely connected and detected using a morphological technique, and since the value of the pores is important in size and depth, the second processor 153-21 can calculate the value of the pores by multiplying the size and depth of each pixel, and dividing by the value of the face region image size.

[0118] The second processor 153-21 can generate skin condition information of a user including wrinkles and fine wrinkles by using the face region image. Since wrinkles and fine wrinkles are also shown to be relatively dark compared to the surrounding environment, like pores, the second processor 153-21 can first detect dark regions from the face region image, respectively detect and remove similar dark hair. Since the important factors of wrinkles are length and depth, the second processor 153-21 can regard a region having a length equal to or less than a certain value or a depth shallower than the average value as a fine wrinkle. The second processor 153-21 can calculate the length and depth of wrinkles by multiplying the length and average depth value of each region finally determined as a wrinkle using an S (saturation) channel of a hue-lightness-saturation (HLS) color model, which has a value similar to the actual depth related to the depth of the wrinkle, and then dividing by the value of the face image size.

[0119] The second processor 153-21 can generate skin condition information of a user including pigmentation by using the face region image. When a darkly colored region is detected with a face region image luminance value, and then red pigments are removed by using a color difference value, the second processor 153-21 leaves only black pigments. Before this, hair is detected and removed. Pigments are calculated only by the luminance value of the pigments, and pigmentation can be calculated by first applying a weight to the pigments according to their darkness, then applying a weight to the darkness with respect to their surrounding environment, then summing and dividing by the value of the size of the face region image.

[0120] The second processor 153-21 can generate skin condition information of a user including skin redness by using the face region image. Since the R (red) and G (green) color channels of the face region image are different from the surrounding environment, the second processor 153-21 can calculate skin redness by combining the R color channel, the G color channel, and one constant value, and then dividing by the value of the face region image size.

[0121] The second processor 153-21 can generate skin condition information of a user including sebum by using the face region image. Porphyrin of a face image looks red, and clogged pores look between yellow and green. Both can be analyzed separately, but it is called sebum, and the second processor 153-21 can display porphyrin and clogged pores detected from the face region image and calculate sebum by percentage with respect to the size of the face region image.

[0122] The second processor 153-21 can generate condition information of an object including skin color by using the face region image. The second processor 153-21 can generate skin condition information of a user including skin color on the face region image by converting RGB data of the face region image into CIE LAB color data, mapping the CIE LAB color data to color chart data, and matching the color chart data to Fitzpatrick classification levels or color chart data.

[0123] The second calculator 153-22 can calculate a numerical value of the skin condition information generated by the second processor 153-21. For example, the second calculator 153-22 can calculate the size of pores as a numerical value, and the length and depth of wrinkles as a numerical value.

[0124] The provider 154 can provide beauty consultation information when the amount of change between the calculated body feature and the previously stored existing body feature exceeds a predetermined value (for example, 10%). The provider 154 can provide consultation information on the degree of obesity when the amount of change between the calculated curvature and the previously stored existing curvature exceeds a predetermined value. And the provider 154 can provide consultation information on the degree of skin aging when the amount of change between the generated skin condition information and the previously stored existing skin condition information exceeds a predetermined value.

[0125] In the case of providing consultation information on the degree of obesity, the provider 154 can provide a value of the degree of obesity (for example, including xx kg more obese than in the past), a warning text, and a future body image with respect to the current body image. Here, the future body image can include an image that is more obese than the current body image.

[0126] In the case of providing consultation information on the degree of skin aging, the provider 154 can provide a value of the degree of skin aging (for example, including XX years older than in the past), a warning text, and a future face image with respect to the current face image. Here, the future face image can include an image that is more aged than the current face image.

[0127] When the degree of obesity consultation is provided, the recommender 155 can provide exercise information and / or diet information as recommendation information to address obesity. Also, the recommender 155 can provide skin care information and / or diet information and / or program information that can alleviate skin aging as recommendation information when providing the degree of skin aging consultation information.

[0128] Figure 4 is a diagram for schematically explaining a beauty consultation information providing system according to still another embodiment of the present disclosure. In the following description, a repeated description of the same part as that of Figures 1 to 3 will be omitted.

[0129] Referring to Figure 4 , the beauty consultation information providing apparatus 100 can be included in the user terminal 200. There are various methods of including the beauty consultation information providing apparatus 100 in the user terminal 200. As a specific embodiment, the beauty consultation information providing apparatus 100 can be installed in the user terminal 200 through the network 400, for example, the beauty consultation information providing apparatus 100 can be installed in the user terminal 200 in the form of an application. As another specific embodiment, the beauty consultation information providing apparatus 100 can also be installed in the user terminal 200 offline. However, this is an exemplary form, and the present disclosure is not limited thereto, and can include a case in which the beauty consultation information providing apparatus 100 can be installed in the user terminal 200 in various forms.

[0130] Figure 5 is a diagram for schematically explaining a beauty consultation information providing system according to still another embodiment of the present disclosure. In the following description, a repeated description of the same part as that of Figures 1 to 4 will be omitted.

[0131] Referring to Figure 5 , a part 100A of the beauty consultation information providing apparatus 100 can be included in the server 300, and another part 100B can be connected to the server 300 through the network 400.

[0132] For example, among the constituent elements of the beauty consultation information providing apparatus 100 shown in Figures 1 to 3 , the part 100A including the analyzer 153 and the provider 154 can be included in the server 300. Since a method for including the part 100A of the beauty consultation information providing apparatus 100 in the server 300 is as described in the embodiment of Figure 4 , a detailed description thereof will be omitted. Also, Figures 1 to 3Among the illustrated constituent elements of the beauty consultation information providing apparatus 100, other parts 100B including the first generator 151, the second generator 152, and the recommender 155 can be connected to the server 300 through the network 400.

[0133] In the present embodiment, although the first generator 151, the second generator 152, and the recommender 155 among the constituent elements of the beauty consultation information providing apparatus 100 have been described as the parts 100B connected to the server 300 through the network 400, this is one embodiment, and the present disclosure is not limited thereto. That is, at least any one of the plurality of elements included in the beauty consultation information providing apparatus 100 can be selectively connected to the server 300 through the network 400.

[0134] Figure 6 is an example diagram of beauty consultation information provided by a beauty consultation information providing apparatus according to yet another embodiment of the present disclosure. In the following description, a repeated description of the same part as that of Figures 1 to 5 will be omitted.

[0135] Referring to Figure 6 , the illustrated case is that the beauty consultation information providing apparatus 100 is included in the user terminal 200, the beauty consultation information providing apparatus 100 calculates a curvature of a body from an image included in the second image set among a plurality of images stored in the user terminal 200, and provides beauty consultation information including obesity-related information when a change amount between the calculated curvature and previously stored existing curvature exceeds a predetermined value. Figure 6 In the above, the user can confirm a total change in the obesity degree of each body part by providing a value for the obesity degree of each body part with respect to a full-body image of the user.

[0136] Figure 7 is an example diagram of beauty consultation information provided by a beauty consultation information providing apparatus according to yet another embodiment of the present disclosure. In the following description, a repeated description of the same part as that of Figures 1 to 6 will be omitted.

[0137] Referring to Figure 7 , the illustrated case is that the beauty consultation information providing apparatus 100 is included in the user terminal 200, the beauty consultation information providing apparatus 100 generates skin condition information of a face from an image included in the second image set among a plurality of images stored in the user terminal 200, and provides beauty consultation information including skin aging-related information when a change amount between the generated skin condition information of the face and previously stored existing skin condition information exceeds a predetermined value. Figure 7 In the above, the user can visually confirm a change in the skin condition by providing a current skin condition and a future skin condition with respect to a face image of the user.

[0138] Figure 8 is a flowchart for explaining a beauty consultation information providing method according to an embodiment of the present disclosure. In the following description, a repeated description of the same part as that of Figures 1 to 7 will be omitted.

[0139] Referring to Figure 8 , in operation S810, the beauty consultation information providing apparatus 100 generates a first image set having classified a plurality of images stored based on photographing information for each predetermined time period. Here, the photographing information can include photographing mode information of the user terminal 200 when the images are photographed, for example, a self-photographing mode, a continuous photographing mode, a moving image photographing mode, etc. Further, the photographing information can include photographing setting information as metadata stored together, for example, the photographing setting information can include one or more of brightness, contrast, saturation, color, gamma, exposure, ISO sensitivity, aperture, and shutter speed of the photographed images.

[0140] In operation S820, the beauty consultation information providing apparatus 100 generates a second image set having classified a plurality of images contained in the first image set based on a purpose of providing consultation information. Here, the purpose of providing consultation information can include one or more of a degree of obesity and a degree of skin aging, and at least one of them can be set through a selection of a user. In the case of the purpose of providing consultation information about the degree of obesity, the beauty consultation information providing apparatus 100 can include an image containing at least a part of a body part exposed in the plurality of images contained in the first image set into the second image set. In addition, in the case of the purpose of providing consultation information about the degree of skin aging, the beauty consultation information providing apparatus 100 can include an image containing a face in the plurality of images contained in the first image set into the second image set.

[0141] In operation S830, the beauty consultation information providing apparatus 100 calculates body features by performing comparative analysis on the plurality of images contained in the second image set. In the case of the purpose of providing consultation information about the degree of obesity, the body features can separate a region including a body and a region not including a body from the plurality of images contained in the second image set, detect an edge of the region including the body, and include a result of calculating a curvature of the edge. In the case of the purpose of providing consultation information about the degree of skin aging, the body features can detect a face region from the plurality of images contained in the second image set, and include a result of generating skin condition information including one or more of gloss, pores, wrinkles, fine wrinkles, pigmentation, skin redness, and sebum from the face region information.

[0142] In operation S840, the beauty consultation information providing apparatus 100 provides beauty consultation information when the calculated body feature exceeds a predetermined ratio. When the amount of change between the calculated curvature and the previously stored existing curvature exceeds a predetermined value, the beauty consultation information providing apparatus 100 can provide beauty consultation information including information related to obesity; when the amount of change between the generated skin condition information and the previously stored existing skin condition information exceeds a predetermined value, the beauty consultation information providing apparatus 100 provides consultation information about the degree of aging. In the case of providing consultation information about the degree of obesity, the beauty consultation information providing apparatus 100 can provide a value of the degree of obesity (e.g., including that xx Kg has been fatter than in the past), a warning text, and a future body image with respect to a current body image. In the case of providing consultation information about the degree of skin aging, the beauty consultation information providing apparatus 100 can provide a value of the degree of skin aging (e.g., including that it has aged XX years older than in the past), a warning text, and a future face image with respect to a current face image.

[0143] As an optional embodiment, the beauty consultation information providing apparatus 100 can provide exercise information and / or diet information for solving obesity as recommendation information when providing the degree of obesity consultation information. In addition, the beauty consultation information providing apparatus 100 can provide skin care information and / or diet information and / or program information that can alleviate skin aging as recommendation information when providing the degree of skin aging consultation information.

[0144] Embodiments of the present disclosure can be implemented by a computer program executed using various components on a computer, and such a computer program can be recorded in a computer readable medium. Examples of the computer readable medium can include magnetic media such as a hard disk drive (HDD), a floppy disk, and a magnetic tape, optical media such as a CD-ROM and a DVD, magneto-optical media such as a floptical disk, or the like hardware devices, and a ROM, a RAM, and a flash memory specially configured to store and execute program commands.

[0145] Meanwhile, the computer program can be those specially designed and constructed for the purpose of the present disclosure, or can be a kind of computer program well known and available to those skilled in the computer software field. Examples of program codes include machine codes (e.g., machine codes generated by a compiler) and high-level codes that can be executed by a computer using an interpreter.

[0146] As used in this application (and particularly in the appended claims), the terms "a" and "an" and "the" include both the singular and the plural, unless the context clearly dictates otherwise. Also, it is to be understood that the use of any of the following terms "comprising", "having", "including", or "containing" shall be taken to mean the inclusion of one or more of the recited elements, but not the exclusion of any other elements. Moreover, it is to be understood that the use of the term "or" in referring to a list of items shall be taken to mean any one item in the list, but not necessarily all of the items in the list.

[0147] Unless otherwise explicitly stated, the above steps constituting the method disclosed in the present disclosure can be performed in an appropriate order. However, the scope or spirit of the present disclosure is not limited thereto. All examples described herein or terms used therein indicating the same (e.g., "for example," etc.) are only for a more detailed description of the present disclosure. Therefore, it should be understood that the scope of the present disclosure is not limited to the above-described example embodiments or by the use of such terms unless limited by the appended claims.

[0148] Also, it will be obvious to those skilled in the art that various changes, substitutions and modifications can be made therein without departing from the scope of the appended claims or their equivalents.

[0149] Therefore, the technical idea of the present disclosure is not limited to the above-described embodiments, and it is intended that all changes falling within the scope of the present disclosure should be considered to fall within the scope of the present disclosure.

Claims

1.A method of providing beauty consultation information, the method comprising: generating a first image set based on image information periodically taken, the first image set including a plurality of first images previously stored; generating a second image set including a plurality of second images included in the first image set, the second image set being divided based on one or more conditions for providing consultation information; calculating a current state of a body feature of a user based on comparative analysis of the plurality of second images included in the second image set; and in response to an amount of change between the current state of the body feature and a previous state of the body feature exceeding a predetermined value, generating beauty consultation information, wherein the generating of the second image set includes identifying an image in the first image set including at least a part of a body exposed for providing consultation information based on a degree of obesity, and setting the second image set to include the image including the body part, wherein the calculating of the current state of the body feature includes separating an area corresponding to a body of the user and an area not corresponding to the body of the user from the plurality of second images in the second image set, detecting an edge of the area corresponding to the body of the user, and calculating a curvature of the edge. 2.The method of claim 1, wherein the generating of the beauty consultation information includes: when an amount of change between the curvature and an existing curvature previously stored exceeds a predetermined value, providing beauty consultation information including obesity-related information. 3.The method of claim 1, wherein the generating of the second image set includes: identifying an image in the first image set including a face of the user for providing consultation information based on a degree of skin aging, and setting the second image set to include the image including the face of the user. 4.The method of claim 3, wherein the calculating of the current state of the body feature includes: detecting a face area in the plurality of second images in the second image set, and generating skin condition information based on the face area, the skin condition information including at least one of shine, pores, wrinkles, fine wrinkles, pigmentation, skin redness, or sebum. 5.The method of claim 4, wherein the generating of the beauty consultation information includes: when an amount of change between the skin condition information and existing skin condition information previously stored exceeds a predetermined value, providing beauty consultation information including skin aging-related information. 6.A beauty consultation information providing apparatus comprising: a memory configured to store image information, and a controller configured to: generate a first image set based on image information periodically taken, the first image set including a plurality of first images previously stored, generate a second image set including a plurality of second images included in the first image set, the second image set being divided based on one or more conditions for providing consultation information, calculate a current state of a body feature of a user based on comparative analysis of the plurality of second images included in the second image set, and ​ ​ ​ ​ generate the beauty consultation information including obesity-related information in response to an amount of change between the current state of the body feature and a previous state of the body feature exceeding a predetermined value, wherein the controller is further configured to identify an image of the first image set including at least a part of a body portion for providing consultation information based on a degree of obesity, and set the second image set to include an image including the body portion, wherein the controller is further configured to separate an area corresponding to a user's body and an area not corresponding to the user's body from the plurality of second images of the second image set, detect an edge of the area corresponding to the user's body, and calculate a curvature of the edge. 7.The device of claim 6, wherein the controller is further configured to: provide the beauty consultation information including obesity-related information when an amount of change between the curvature and a previously stored existing curvature exceeds a predetermined value. 8.The device of claim 6, wherein the controller is further configured to: identify an image of the first image set including a face of the user for providing consultation information based on a degree of skin aging, and set the second image set to include an image including the face of the user. 9.The device of claim 8, wherein the controller is further configured to: detect a face area in the plurality of second images of the second image set, and generate skin condition information based on the face area, the skin condition information including at least one of shine, pores, wrinkles, fine wrinkles, pigmentation, skin redness, or sebum. 10.The device of claim 9, wherein the controller is further configured to: provide the beauty consultation information including skin aging-related information when an amount of change between the skin condition information and a previously stored existing skin condition information exceeds a predetermined value.

Images