WO2025234261A1 - Information processing device, information processing method, and information processing program - Google Patents

Abstract

The present invention enables a poster to determine, before posting, whether a fashion measure is likely to lead to conversion. This information processing device comprises an acquisition unit, a first display unit, and a second display unit. The acquisition unit acquires a captured image of a poster to which a fashion measure is applied. The first display unit extracts at least one thumbnail image of a model, which is a candidate to which the fashion measure is applied, on the basis of a prescribed condition and displays the at least one thumbnail image. When the poster designates a thumbnail image, the second display unit displays an image obtained by applying the fashion measure to the model.

Description

Information processing device, information processing method, and information processing program

The present invention relates to an information processing device, an information processing method, and an information processing program.

Technology for displaying an image to which a poster's fashion measures, such as makeup, have been applied is known. For example, a technology is known in which a user can specify an image taken by the poster, and an image of the user to which the poster's fashion measures have been applied is displayed.

Patent No. 7308317

W. Jiang, S. Liu, C. Gao, J. Cao, R. He, J. Feng, S. Yan “PSGAN: Pose and Expressio n　Robust　Spatial-Aware　CAN　for Customizable　Makeup　Transfer”, [online], [searched on April 5, 2020] , Internet <https://openaccess.thecvf.com/content_CVPR_2020/html/Jiang_PSGAN_Pose_and_Expression_Robust_Spatial-Aware_GAN_for_Customizable_Makeup_CVPR_2020_paper.html>

However, while conventional technology can promote improved usability for users, there is room for further improvement to promote improved usability for contributors. For example, conventional technology has room for further improvement to make it easier for contributors to satisfy their desire for financial or psychological recognition, such as wanting to spread their fashion initiatives to others. Also, conventional technology has room for further improvement to enable contributors to determine, before posting, whether a fashion initiative is likely to lead to conversions.

This application was made in light of the above, and aims to enable posters to determine before posting whether a fashion initiative is likely to lead to conversions.

The information processing device according to the present application is characterized by having an acquisition unit that acquires images taken by a poster to which a fashion measure has been applied, a first display unit that extracts and displays at least one thumbnail image of a model that is a candidate for applying the fashion measure based on predetermined conditions, and a second display unit that, when the poster specifies the thumbnail image, displays an image in which the fashion measure has been applied to the model.

One aspect of this embodiment has the effect of enabling posters to determine, before posting, whether a fashion initiative is likely to lead to conversions.

FIG. 1 is a diagram illustrating an example of the configuration of an information processing system according to an embodiment. FIG. 2A is a diagram showing an example of the overall flow of the user interface on the contributor side. FIG. 2B is a diagram showing an example of the overall flow of the user interface on the user side. FIG. 3 is a diagram illustrating an example of information processing according to the embodiment. FIG. 4 is a diagram illustrating an example of a preview screen according to the embodiment. FIG. 5 is a diagram illustrating an example of the configuration of a terminal device according to the embodiment. FIG. 6 is a diagram illustrating an example of the configuration of an information processing apparatus according to the embodiment. FIG. 7 is a diagram illustrating an example of a model information storage unit according to the embodiment. FIG. 8 is a diagram illustrating an example of an evaluation information storage unit according to the embodiment. FIG. 9 is a flowchart (1) illustrating an example of information processing according to the embodiment. FIG. 10 is a flowchart (2) illustrating an example of information processing according to the embodiment. FIG. 11 is a hardware configuration diagram illustrating an example of a computer that realizes the functions of the information processing device.

Below, the information processing device, information processing method, and information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail with reference to the drawings. Note that the information processing device, information processing method, and information processing program according to the present application are not limited to these embodiments. Furthermore, identical components in the following embodiments will be designated by the same reference numerals, and duplicate explanations will be omitted.

(Embodiment)
1. Configuration of the information processing system
An information processing system 1 shown in Fig. 1 will be described. As shown in Fig. 1, the information processing system 1 includes a terminal device 10 and an information processing device 100. The terminal device 10 and the information processing device 100 are connected to each other via a predetermined communication network (network N) so as to be able to communicate with each other via wired or wireless communication. Fig. 1 is a diagram showing an example of the configuration of the information processing system 1 according to an embodiment.

The terminal device 10 is an information processing device used by a poster who wishes to spread their own fashion initiatives (makeup, etc.) to others via SNS or the like. A poster who uses the terminal device 10 may be, for example, an influencer who disseminates their own fashion initiatives over the Internet. For example, an influencer who distributes videos related to the fashion initiatives they undertake. The terminal device 10 may be any device that can implement the processing in the embodiment. The terminal device 10 may also be a device such as a smartphone, tablet device, notebook PC, desktop PC, mobile phone, or PDA. Figure 3 shows a case where the terminal device 10 is a smartphone.

The terminal device 10 is, for example, a smart device such as a smartphone or tablet, and is a portable terminal device that can communicate with any server device via a wireless communication network such as 3G to 5G (Generation) or LTE (Long Term Evolution). The terminal device 10 also has a screen such as an LCD display with touch panel functionality, and may accept various operations on displayed data such as content, such as tapping, sliding, and scrolling, performed by the contributor using a finger or stylus. In Figure 3, the terminal device 10 is used by contributor U1.

The information processing device 100 is an information processing device that aims to make it easier for posters to satisfy their desire for financial or psychological recognition, such as wanting to spread their fashion initiatives to others, and to enable posters to determine before posting whether a fashion initiative is likely to lead to conversions, thereby promoting improved usability for posters. The information processing device 100 may be any device that can implement the processing in the embodiments. For example, the information processing device 100 is implemented by a server device, cloud system, or the like that provides a predetermined service (which may be a web service or an app service) that enables fashion initiatives to be posted (registered) and tried on. In the following embodiments, service W1 will be used as an example of such a service. That is, service W1 is a predetermined service that enables fashion initiatives to be posted and tried on.

[2. An example of information processing]
There are cases where a user wants to spread their own fashion initiatives to others. Also, in order to spread their own fashion initiatives to others, they may want to determine before posting what kind of fashion initiative will lead to conversions (for example, whether it will lead to a purchase or whether it will encourage people to try on the item). However, with conventional technology, it has not been possible to determine, for example, what kind of fashion initiative will lead to conversions among their followers, etc., before posting.

This application was made in light of the above, and aims to make it easier for posters to satisfy their desire for financial or psychological recognition, such as wanting to spread their own fashion initiatives to others, and to enable posters to determine before posting whether their fashion initiatives are likely to lead to conversions.

In the following embodiments, the application of fashion measures is not limited to actual actions, but may also include virtual actions. In other words, it may be an action that the poster actually performs in the real world, or an action that they perform virtually via an avatar, etc.

In the following embodiments, a case where a poster posts facial makeup is described as an example of a fashion measure, but fashion measures do not have to be limited to facial makeup. Fashion measures can be, for example, hair makeup (hair makeup) such as hairstyle and hair color (hair color), or can be not limited to makeup but also trying on (trying on in the real world or virtually) and coordinating clothes (clothing is not limited to one-piece dresses and can be, for example, shoes, socks, accessories, watches, jewelry, etc.). In the following embodiments, the processing on the poster's side who posts the fashion measure is described, rather than the processing on the user's side who applies the fashion measure. Note that the poster who posts the fashion measure, for example, photographs (scans) the face after the fashion measure and registers the items used. Furthermore, the user who applies the fashion measure, for example, specifies the poster's post information, tries on the fashion measure (full makeup, etc.), and if they like it, purchases the items used (the items used in that full makeup).

Figure 2A is a diagram showing an example of the overall flow of the user interface on the poster's side. When poster U1 clicks "Register" at the bottom of the first screen from the left, they will be redirected to the second screen from the left. After reading the notes and agreeing to the terms of use (if it is their first time), they will be redirected to the third screen from the left. After taking photos of their face from multiple angles on the makeup photo shoot screen, they will be redirected to the fourth screen from the left. After checking the preview screen to see how the captured makeup will look when tried on, they will be redirected to the fifth screen from the left. Then, on this screen, they can enter a thumbnail image and text to post, link the items used, and post, and the posted information will be made public.

Figure 2B is a diagram showing an example of the overall flow of the user interface on the user side. When user P1 selects the makeup they are interested in on the first screen from the left, the screen transitions to the second screen from the left. When user P1 operates "Try Makeup" on this screen, the screen transitions to the third screen from the left. On this screen, user P1 can try on the registered makeup on their own face and see the items used. Furthermore, when user P1 operates "HOW TO" in the second scene from the left, the screen transitions to the fourth screen from the left. On this screen, it is possible to view an explanatory video on the makeup. For example, a web view is launched within the app and the video is played.

3 is a diagram showing an example of information processing in the information processing system 1 according to an embodiment. FIG. 3 illustrates an example of information processing on the side of a poster who posts a fashion campaign. Poster U1 uploads his/her makeup information to a predetermined service (service W1) provided by the information processing device 100 (step S11). The makeup information may be, for example, information captured of the poster's makeup (such as a still image), or information explaining how to apply makeup, such as the order and volume of the makeup (such as a video). The makeup information may also be, for example, mask information, which is the makeup applied to the poster's face, or cosmetic information linked to the posted information. The mask information may be information about the poster's face after makeup has been applied, or information about the makeup itself obtained from the difference between the poster's face after makeup and the poster's bare face. Poster U1, for example, uploads a facial image of his/her face with makeup applied to service W1. At this time, poster U1 may, for example, register the items used for makeup in association with his/her makeup information. For example, the information processing device 100 may cause the poster U1 to register the items used in the makeup so that the items are linked to the makeup information applied by the poster U1. In this case, for example, the information processing device 100 may identify the makeup information by extracting mask information from the posted information.

When a user specifies the posted information of poster U1, the information processing device 100 may, for example, perform processing to apply makeup information linked to the posted information to the user's facial image, or may perform processing to enable the purchase of items used in the makeup. Below, a description will be given using a captured image G1 (which may be a still image or a moving image) as an example of posted information. For example, when user P1 (such as a follower of poster U1) who has viewed (watched) captured image G1 specifies captured image G1, the information processing device 100 may enable the application of makeup information used in capturing captured image G1, or may provide a link to a website where the items used can be purchased. Below, a description will be given of the preview screen (pre-post preview screen) that is displayed when poster U1 uploads captured image G1 of their own makeup to service W1. Note that if poster U1 allows (accepts) the posting (registration) on the preview screen (screen C1), the image will be made public and available for viewing. The preview screen is a screen where, for example, after a poster has finished photographing their own makeup and before posting it, they can check how the makeup will look by applying it to multiple face types (fresh, cute, feminine, cool, and androgynous men, etc.).

Figure 4 is a diagram showing an example of a preview screen according to an embodiment. Screen C1 is a preview screen before the photographed image G1 is posted. In other words, it is a preview screen displayed on the poster's side before posting. Screen C1 displays, at the top (main), a photographed image (photographed image G1) of poster U1 taken after applying makeup. Screen C1 also includes a button B1 that allows the poster U1 to retake the photograph if they want to change the photographed image, and a button B2 that allows the photographed image to be posted. When button B1 is operated (clicked, tapped, etc.), the preview screen returns to the photographing screen. If the poster U1 takes another photograph here, the preview screen returns and the newly taken photographed image is displayed at the top. When button B2 is operated, photographed image G1 is posted. In this case, photographed image G1 is made public and can be viewed by followers of poster U1, etc. Here, the posted captured image G1 may become viewable, or information posted along with the captured image G1 (such as the items used) may become viewable, or information registered in association with the poster U1 (such as a separately registered thumbnail image) may become viewable.

Screen C1 also includes thumbnail images showing at least one face type. In Figure 4, from left to right, it includes thumbnail image SG1 with a "Fresh" face type, thumbnail image SG2 with a "Cute" face type, thumbnail image SG3 with a "Feminine" face type, thumbnail image SG4 with a "Cool" face type, and thumbnail image SG5 with a "male with androgynous features" face type. In Figure 4, these thumbnail images SG1 to SG5 are displayed superimposed on the captured image G1. This displays four female face images according to the four types and one male face image with androgynous features, allowing the user to try on the captured makeup on each image to see how it looks.

Furthermore, these thumbnail images SG1 to SG5 are selectable. For example, when thumbnail image SG1 is operated, thumbnail image SG1 is selected. At this time, the makeup information of poster U1 (the makeup information used in captured image G1) is applied to the facial image of thumbnail image SG1. Then, the facial image with the makeup information of poster U1 applied to the facial image of thumbnail image SG1 is displayed at the top. As a result, poster U1 can check on the preview screen what kind of makeup will actually look like (whether it suits them, etc.) on their own face type of "Fresh." Similarly, for example, when thumbnail image SG2 is operated, thumbnail image SG2 is selected. At this time, the makeup information of poster U1 is applied to the facial image of thumbnail image SG2. Then, the facial image with the makeup information of poster U1 applied to the facial image of thumbnail image SG2 is displayed at the top. As a result, poster U1 can check on the preview screen what kind of makeup will actually look like on their own face type of "Cute." By displaying the preview screen in this way, users can check, for example, what kind of makeup suits what kind of face type, and what kind of face type their own makeup actually suits, before posting. Users can also check, for example, whether their post will appeal to users with the face type they are targeting, and whether their post will appeal to their followers, before posting. The facial images of the models in thumbnail images SG1 to SG5 are selection candidates to which poster U1 can apply makeup information, and the facial image of the model to which poster U1 has selected a thumbnail image and applied makeup information is displayed at the top of screen C1 (step S12).

Note that the number of thumbnail images and face types that can be displayed on screen C1 do not have to be limited to this example. They do not have to be limited to the five images of thumbnail images SG1 to SG5 shown in FIG. 4. For example, a further thumbnail image may be hidden to the right of thumbnail image SG5 and be visible by scrolling. Furthermore, the display format of these thumbnail images does not have to be limited to the example shown in FIG. 4, and they may be displayed in any display format. Furthermore, they do not have to be limited to face types such as "Fresh," "Cute," "Feminine," "Cool," and "Androgynous Male." For example, the face type of the thumbnail images displayed on screen C1 may be different each time depending on the face type and makeup information of poster U1. For example, the face type of the thumbnail images displayed on screen C1 may be different each time the user slightly changes their makeup and retakes the photo.

The process for extracting the face type of the thumbnail images displayed on screen C1 will now be explained. In Figure 4, thumbnail images of five face types are displayed: "Fresh," "Cute," "Feminine," "Cool," and "Androgynous Male." We will now explain how these five face types are extracted.

The information processing device 100 acquires the captured image to be displayed on screen C1 (pre-post preview screen) (step S101). In the examples of FIGS. 3 and 4, captured image G1 is acquired. The information processing device 100 then extracts at least one thumbnail image of a model who is a candidate for applying makeup information based on predetermined conditions (step S102). In the examples of FIGS. 3 and 4, thumbnail images SG1 to SG5 are extracted. The information processing device 100 then displays the extracted thumbnail image in a predetermined area of screen C1 (so as to be superimposed on the captured image) (step S103). In the examples of FIGS. 3 and 4, the information processing device 100 displays the extracted thumbnail image in area R1. When a thumbnail image is selected, the information processing device 100 generates a facial image of the model with makeup information applied from the facial image of the model in the thumbnail image (step S104). The information processing device 100 then displays the generated facial image of the model at the top of screen C1 (step S105).

In step S104, an example of a method for generating a facial image of a model with makeup information applied is a method called PSGAN (Pose and Expression Robust Spatial-Aware Generative Adversarial Network), which is disclosed in the above-mentioned non-patent document 1 and which transfers only makeup information from a facial image to another face. This method uses deep learning and can transfer only makeup information to another face regardless of facial expression or pose. Using a method such as PSGAN, the information processing device 100 applies makeup similar to the makeup used by poster U1 in the posted information of poster U1 to the facial image of the model. Specifically, the information processing device 100 generates makeup information for applying makeup similar to the makeup used by poster U1, and applies the generated makeup information to the facial image of the model. Then, in step S105, the information processing device 100 generates a facial image of the model with makeup information applied in this way, and displays the generated facial image of the model at the top of the screen C1.

Here, the process of extracting at least one item based on predetermined conditions in step S102 will be described. The information processing device 100 performs the extraction process in step S102 based on various conditions. As examples of the extraction process, three patterns will be described: using the degree to which makeup suits the subject, using the poster's follower information, and using the model's login information; however, the process is not limited to the following examples.

(Using the degree to which makeup suits you)
The information processing device 100 may perform the extraction process based on, for example, the degree to which makeup suits the face type of the model in the thumbnail image. For example, the information processing device 100 may extract thumbnail images in descending order of the model's rating (score) indicating the degree to which the makeup applied by the poster U1 suits them. For example, the information processing device 100 may extract thumbnail images by estimating the degree to which makeup suits the model using machine learning of the poster U1's rating of the model's face image to which makeup information has been applied. For example, the information processing device 100 may extract thumbnail images by estimating the degree to which makeup suits the model using a learning model trained on machine learning, using a case where the poster U1 has rated the model's face image to which makeup information has been applied as "suitable" as a positive example and a case where the poster U1 has rated the model's face image to which makeup information has been applied as "unsuitable" as a negative example.

For example, the information processing device 100 may have the poster U1 select (or specify) on screen C1 the face type of a model that they judge would suit their makeup, and then learn the selected face type in combination with makeup information to evaluate how well the makeup suits them. For example, the information processing device 100 may perform machine learning on a combination of the selected face type and makeup information as a positive example, or on a combination of a face type and makeup information that was not selected as a negative example. The information processing device 100 may then estimate a suitable face type by inputting makeup information into a learning model machine-learned in this way. Furthermore, the information processing device 100 may perform machine learning on information registered on screen C1 after trying on makeup as a positive example, without having the poster U1 select a face type of a model, for example.

The information processing device 100 may extract thumbnail images in the order of models whose face type is similar to that of the poster U1. For example, if the face type of the poster U1 is "Cute," the information processing device 100 may prioritize and extract thumbnail images of models whose face type is "Cute."

(When using the poster's follower information)
The information processing device 100 may perform the extraction process based on, for example, the follower information of the poster U1. For example, the information processing device 100 may prioritize extracting thumbnail images of models with the same or similar facial type as the poster U1's followers. Furthermore, for example, the information processing device 100 may prioritize extracting thumbnail images of models with facial types that are of interest to the poster U1's followers. Furthermore, for example, the information processing device 100 may perform the extraction process limited to followers estimated to lead to conversions such as purchases or viewings. In this case, for example, the information processing device 100 may estimate the likelihood of conversions such as purchases or viewings using a model that has learned the relationship between a user's try-on history, purchase history, viewing history, etc. and whether the user has achieved a predetermined conversion, such as making a purchase or viewing a predetermined content, and then estimate followers who will lead to conversions based on the estimated likelihood of conversions.

Furthermore, the information processing device 100 may perform the extraction process based on, for example, the facial image of a follower rather than the model. The information processing device 100 may perform the extraction process based on, for example, a facial image of a model generated based on the facial image of a follower (such as a facial image of a model generated based on generation AI). In this case, the information processing device 100 may use, for example, the facial image of the follower who has made the most purchases, viewed the most, tried on the most items, or had the most followers, or may use the average facial image of multiple followers. This makes it possible to effectively encourage people to try on items by using, for example, the facial image of a follower with a large number of followers.

(When using the model's login information)
The information processing device 100 may perform the extraction process based on, for example, login information (such as the number of logins and whether the user is a new registrant) of candidate models displayed on the screen C1. For example, the information processing device 100 may prioritize extracting thumbnail images of models with a higher number of logins. The model may be, for example, a model that is identical or similar to the facial type of a user with a higher number of logins, a model that is identical or similar to the facial type that the user with a higher number of logins is interested in, or the user himself/herself. Furthermore, a high number of logins does not necessarily mean a high number of logins, but may also include a large number of users. Furthermore, for example, the information processing device 100 may prioritize extracting thumbnail images of models that are estimated to be more likely to have makeup information applied by the poster U1 if the poster U1 posts a content. Furthermore, for example, the information processing device 100 may prioritize extracting thumbnail images of models that are estimated to be more likely to have the poster U1's makeup information applied ... newly registrants to the service W1. Furthermore, for example, the information processing device 100 may preferentially extract thumbnail images of models who have logged in within a predetermined period (e.g., recently).

The above describes the process for extracting thumbnail images of models who are candidates for applying makeup information. For example, the specified conditions for extracting thumbnail images have been described. Below, we will explain the process for determining the display mode of thumbnail images after such extraction process (display order (sort order), highlighting, display of positive information such as face type and follower information, etc.). Specifically, we will explain the process for determining the display mode of thumbnail images when displaying them in a specified area of screen C1 in step S103. The information processing device 100 determines the display mode of thumbnail images for step S103 based on various conditions. As an example of the display mode determination process, we will explain three patterns using the degree to which makeup suits the model, the poster's follower information, and the model's login information, as in the extraction process described above. However, the present invention is not limited to these examples. Furthermore, explanations similar to those for the extraction process described above will be omitted as appropriate.

(Using the degree to which makeup suits you)
The information processing device 100 may perform a display mode determination process based on, for example, the degree to which makeup suits the face type of the model in the thumbnail image. For example, the information processing device 100 may determine a display mode such that thumbnail images of models with higher ratings indicating the degree to which the makeup applied by the poster U1 suits them are displayed preferentially (e.g., displayed at the top, displayed at the beginning, or highlighted). Furthermore, for example, the information processing device 100 may determine a display mode such that thumbnail images of models with a face type similar to that of the poster U1 are displayed preferentially. Furthermore, the information processing device 100 may perform a display mode determination process by subdividing face types (e.g., subdividing the face into features such as eyes and lips). In this way, processing may be performed using subtypes of face features rather than overall face types such as cute or cool. The information processing device 100 may determine a display mode such that thumbnail images of models with higher ratings for each subtype of face type are displayed preferentially. In this case, the information processing device 100 may determine a display mode such that thumbnail images of models with higher ratings for each subtype of face type are displayed preferentially. In this case, the information processing device 100 may determine a display mode such that thumbnail images of models with higher ratings are displayed preferentially, for example, by highlighting the model to indicate that the model suits the model, using a pop-up or other display. For example, type determination may be performed using only specific facial features rather than the entire face, and evaluation may be performed using the specific facial features for preferential display. For example, if the specific facial features are the eyes, thumbnail images of models with cute eyes may be displayed on the preview screen along with thumbnail images of models with cool eyes, and if the specific facial features are the lips, thumbnail images of models with cute lips and thumbnail images of models with cool lips may be displayed on the preview screen. In this case, for example, in order to display thumbnail images of models with cute eyes on the preview screen, only thumbnail images of models with cute eyes may be extracted and displayed, and in order to display thumbnail images of models with cool eyes on the preview screen, only thumbnail images of models with cool eyes may be extracted and displayed.

(When using the poster's follower information)
The information processing device 100 may perform a display mode determination process based on, for example, follower information of poster U1. For example, the information processing device 100 may perform a display mode determination process based on the facial types of poster U1's followers. For example, the information processing device 100 may determine a display mode such that thumbnail images of models with the same or similar facial types as poster U1's followers are preferentially displayed. Furthermore, for example, the information processing device 100 may perform a display mode determination process based on the proportion of facial types of poster U1's followers. For example, if a high proportion of poster U1's followers have the "Cute" facial type, the information processing device 100 may determine a display mode such that thumbnail images of "Cute" models are preferentially displayed. Furthermore, for example, if a high proportion of poster U1's followers have the "Cute" facial type, the information processing device 100 may determine a display mode such that thumbnail images of "Cute" models are preferentially displayed. Furthermore, for example, if a high proportion of poster U1's followers have the "Cute" facial type, the information processing device 100 may determine a display mode such that thumbnail images of "Cute" models are preferentially displayed. Furthermore, for example, when there are multiple face types with a high proportion, the information processing device 100 may subdivide the face types and perform the process of determining the display mode.

At this time, the information processing device 100 may, for example, determine to highlight the follower type by displaying it in a pop-up or the like. For example, the information processing device 100 may determine to highlight the follower's face type (indicating that it is the follower's face type) by displaying it in a pop-up or the like, or may determine to highlight the number of followers for each face type. For example, the information processing device 100 may determine to highlight the thumbnail image by changing the color or thickness of the frame. At this time, the information processing device 100 may also, for example, determine to prioritize the display so that face types with high conversion (likelihood of trying on clothes, etc.) are displayed at the top. This allows the poster U1 to check followers who are highly engaged. The information processing device 100 may, for example, determine to notify followers who match the face type selected by the poster U1 that new makeup information has been posted when the poster U1 posts makeup information.

Furthermore, the information processing device 100 may decide to highlight the follower's face image instead of the model's, for example. The information processing device 100 may decide to highlight the follower's face image by displaying a model's face image generated based on the follower's face image (such as a model's face image generated based on generation AI). In this case, the information processing device 100 may use the face image of the follower who has made the most purchases, viewed the most, tried on the most clothes, or had the most followers, or may use the average face image of multiple followers. This makes it possible to effectively encourage followers to try on clothes, for example, by using the face image of a follower with a large number of followers.

(When using the model's login information)
The information processing device 100 may perform a display mode determination process based on, for example, login information of a candidate model displayed on the screen C1. For example, the information processing device 100 may perform a display mode determination process based on the number of logins of the model. As in the case of the extraction process described above, the model may be, for example, a model with the same or similar face type as a user with a high number of logins, a model with the same or similar face type as a face type that is of interest to a user with a high number of logins, or the user himself/herself with a high number of logins. Furthermore, a high number of logins does not necessarily mean a high number of logins, but may also include a large number of users. For example, the information processing device 100 may determine a display mode such that thumbnail images of models with a face type that has a high proportion of logins for the model are displayed preferentially. Furthermore, for example, if there are multiple face types with a high proportion of logins for the model (e.g., multiple face types exceeding a predetermined threshold), the information processing device 100 may perform a display mode determination process by subdividing the face types. In this case, the information processing device 100 may determine to highlight the model, for example, by displaying a message such as "High likelihood of trying on makeup!" in a pop-up or the like. Furthermore, for example, the information processing device 100 may determine the display mode so that thumbnail images of models who are new registrants to the service W1 are preferentially displayed.

The above describes the process for determining the display mode of thumbnail images. Once the information processing device 100 determines the display mode of the thumbnail images, it displays the thumbnail images in a predetermined area of the screen C1 in the determined display mode.

(Information processing variation 1: Fashion measures)
In the above embodiment, makeup has been described as an example of a fashion measure, but the example is not particularly limited. For example, it may be hair and makeup such as hairstyle and hair color, or trying on and coordinating clothes. This makes it possible to select a model that suits the hair and makeup posted by poster U1, or to select a model by subdividing the hair and makeup posted by poster U1.

(Information processing variation 2: Friend setting)
In the above embodiment, the model for the thumbnail image is described as a follower of the poster U1, but this example is not particularly limited. The model for the thumbnail image may be, for example, only users who have a predetermined relationship with the poster U1. For example, it may be only users who have permitted sharing (e.g., users who have been set as friends). This allows only the faces of users who have permitted sharing to be displayed on the preview screen, making it possible to provide a service that can be enjoyed only by friends. Furthermore, the model for the thumbnail image may be, for example, only followers of the poster U1 who are estimated to lead to purchases or views.

(Information processing variation 3: Models likely to be tried on)
In the above embodiment, an example has been described in which thumbnail images of models who are likely to try on the item are displayed at the top. In this case, the models who are likely to try on the item may be, for example, users who have posted within a predetermined period of time to a predetermined service (social commerce) that allows users to post and view fashion coordinations.

(Information processing variation 4: Model face image (actual/selected/estimated))
In the above embodiment, an example has been described in which the model of the thumbnail image is a follower of poster U1, i.e., a real model, but this example is not particularly limited. The model of the thumbnail image does not have to be a real model, and may be, for example, a model generated by a generation AI or the like. In other words, the thumbnail image does not have to be a facial image of a real model, and may be, for example, a facial image of a model generated by a generation AI or the like. For example, it may be a facial image of a model generated based on follower information of poster U1. For example, it may be a facial image of a model generated by taking a weighted average based on the number of followers of poster U1.

In addition, there may be cases where there is no facial image of the model that can be used as a candidate for the thumbnail image. For example, there may be followers of poster U1 who have not registered their facial images. In such cases, if users such as followers of poster U1 have registered facial information such as their own face type, the weighting may be changed based on the facial information registered by the user. In other words, the thumbnail image may be, for example, a facial image of the model generated based on weighting changed based on the facial information registered by the user. Furthermore, the facial image of the model may be, for example, a facial image estimated based on user-augmented information based on the user's following relationships, purchasing history, etc. In this way, the facial image of the model may be an actually photographed facial image, a facial image based on facial information selected by the user, or a facial image estimated based on user-augmented information.

(Information Processing Variation 5: Other Functions of the Preview Screen)
In the above embodiment, for example, an operation button that enables the application of a fashion measure to be turned on and off may be displayed on the screen C1. This makes it possible to turn on and off makeup information applied to the poster's facial image with a single operation (such as one click or one tap) via the operation button. In addition, in the above embodiment, for example, an explanatory guide for first-time users may be displayed on the screen C1. In addition, in the above embodiment, for example, it may be possible to enlarge or reduce the facial image in response to an operation by the poster on the screen C1. In addition, in the above embodiment, for example, it may be possible to adjust the density of the facial image in response to an operation by the poster on the screen C1. For example, it may be possible to adjust the density for each part of the face using a user interface such as a slider.

(Information Processing Variation 6: Other Functions of the Preview Screen)
In the above embodiment, for example, a button for automatically generating a description related to the face type of the thumbnail image may be displayed on the preview screen. For example, when an image is selected, a button for automatically generating a description such as "This makeup looks good on your XX type, so please try it on" may be displayed. Also, in the above embodiment, for example, tags related to face types may be linked and automatically registered on the preview screen to make it easier to search for makeup information from the tags.

In the above embodiment, for example, the frame of the thumbnail image on the preview screen may be shaped to correspond to the face type of each model. For example, if there are many round faces, the frame may be round, and if there are many basic faces, the frame may be basic. The shape may also correspond to the characteristics of each model's face type. This makes it possible to determine each model's face type from the frame, reducing the burden of checking the preview when registering.

In the above embodiment, for example, instead of selecting according to face type, the user may be allowed to select according to the purpose of makeup (e.g., date, wedding, girls' night, etc.). For example, the user may be allowed to select from options using different clothing and backgrounds depending on the purpose. In this case, for example, the face type of the thumbnail images may be the same or different depending on the purpose. In other words, the face type may be the same but the clothing and background may be different depending on the purpose, or the clothing and background may be different for each face type depending on the purpose.

In the above embodiment, for example, the density may be adjusted on the preview screen and then registered, and when trying on, the density may be set to the base value.

In the above embodiment, for example, face types for which there is little registration of makeup information that suits them may be extracted or displayed preferentially. It is also possible to display the fact that there are few registrations in an easily understandable manner without prioritizing extraction or display. This makes it easier for even posters with few followers (such as posters who are hard to choose) to try on their registered makeup information, and promotes this function by allowing makeup information that suits a variety of face types to be registered. It is also possible to suggest which face type should be registered as makeup information that suits them, not on the preview screen, but on the screen where a photo of the face with makeup is taken or on the screen prior to that, and also to suggest which face type should be changed as makeup information that suits them on the preview screen if the makeup information is to be changed, and when makeup information is registered, it is also possible to suggest which makeup information is recommended if the next makeup information is to be registered.

In the above embodiment, for example, a case where one preview screen is displayed has been described as an example, but in the above embodiment, multiple preview screens may also be displayed. For example, if multiple thumbnail images are selected, the multiple preview screens may be displayed simultaneously, side by side, or split into left and right halves and displayed separately.

In the above embodiment, for example, if the degree of suitability can be displayed, the degree of suitability may also be displayed. Furthermore, for example, the system may be asked to evaluate which looks better and the results of the comparison may be learned. This makes it possible to achieve highly accurate learning.

(Information Processing Variation 7: Providing Incentives)
In the above embodiment, for example, an incentive may be given to the poster when the post leads to trying on clothes, browsing of the product after trying on clothes, purchase of the product after trying on clothes, or reactivation of a dormant follower. For example, when the post leads to a purchase of a product, electronic money or points that can be used for payment at an online shopping mall selling the product may be given. This makes it possible to encourage the poster to post with conversion in mind.

(Information Processing Variation 8: Display Control)
In the above embodiment, for example, an example was given of a case where display control is performed after extracting a thumbnail image, but in the above embodiment, display control may also be performed by fixing the model without extracting a thumbnail image.

(Information Processing Variation 9: Automatic Display)
In the above embodiment, for example, a case has been described in which the poster specifies a thumbnail image to which the fashion measure is to be applied. However, in the above embodiment, instead of the poster selecting a thumbnail image, the thumbnail image may be automatically applied to a model with the most suitable face type or a model with the face type of a follower, and displayed to the poster.

3. Configuration of terminal device
Next, the configuration of the terminal device 10 according to the embodiment will be described with reference to Fig. 5. Fig. 5 is a diagram showing an example of the configuration of the terminal device 10 according to the embodiment. As shown in Fig. 5, the terminal device 10 includes a communication unit 11, an input unit 12, an output unit 13, and a control unit 14.

(Communication unit 11)
The communication unit 11 is realized by, for example, a network interface card (NIC), etc. The communication unit 11 is connected to a predetermined network N by wire or wirelessly, and transmits and receives information to and from the information processing device 100, etc., via the predetermined network N.

(Input unit 12)
The input unit 12 accepts various operations from posters. In FIG. 3, the input unit 12 accepts various operations from poster U1. For example, the input unit 12 may accept various operations from the poster via a display screen using a touch panel function. The input unit 12 may also accept various operations from buttons provided on the terminal device 10 or a keyboard or mouse connected to the terminal device 10.

(Output unit 13)
The output unit 13 is a display screen of a tablet terminal or the like realized by, for example, a liquid crystal display or an organic EL (Electro-Luminescence) display, and is a display device for displaying various information. For example, the output unit 13 displays information transmitted from the information processing device 100.

(Control unit 14)
The control unit 14 is, for example, a controller, and is realized by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like executing various programs stored in a storage device within the terminal device 10 using RAM (Random Access Memory) as a work area. For example, these various programs include application programs installed on the terminal device 10. For example, these various programs include an application program that displays a preview screen of posted information including thumbnail images of models who are candidates for applying a fashion measure, based on information transmitted from the information processing device 100. The control unit 14 is also realized by an integrated circuit, for example, an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

As shown in FIG. 5, the control unit 14 has a receiving unit 141 and a transmitting unit 142, and realizes or executes the information processing functions described below.

(Receiving unit 141)
The receiving unit 141 receives various information from other information processing devices such as the information processing device 100. For example, the receiving unit 141 receives information for displaying a preview screen of posted information including a thumbnail image of a model who is a candidate for applying a fashion measure.

(Transmitter 142)
The transmission unit 142 transmits various types of information to other information processing devices such as the information processing device 100. For example, the transmission unit 142 transmits selection information selected by the poster from among thumbnail images displayed together with the posted information. Furthermore, for example, the transmission unit 142 transmits evaluation information when the poster evaluates how well makeup suits them.

4. Configuration of Information Processing Device
Next, the configuration of the information processing device 100 according to the embodiment will be described with reference to Fig. 6. Fig. 6 is a diagram showing an example of the configuration of the information processing device 100 according to the embodiment. As shown in Fig. 6, the information processing device 100 includes a communication unit 110, a storage unit 120, and a control unit 130. Note that the information processing device 100 may also include an input unit (e.g., a keyboard, a mouse, etc.) that accepts various operations from an administrator of the information processing device 100, and a display unit (e.g., a liquid crystal display, etc.) that displays various information.

(Communication unit 110)
The communication unit 110 is realized by, for example, a NIC etc. The communication unit 110 is connected to a network N by wire or wirelessly, and transmits and receives information to and from the terminal device 10 etc. via the network N.

(Storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory element such as a RAM or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in FIG. 6 , the storage unit 120 has a model information storage unit 121 and an evaluation information storage unit 122.

The model information storage unit 121 stores model information that is a candidate for display on the preview screen (screen C1). Here, Figure 7 shows an example of the model information storage unit 121 according to the embodiment. As shown in Figure 7, the model information storage unit 121 has items such as "Model ID," "Captured Image," "Setting Type Information," and "Model Information."

"Model ID" indicates identification information for identifying the model (user). "Photographed image" indicates a photographed image of the model that has been registered by the model. In the example shown in Figure 7, conceptual information such as "Photographed image #1" and "Photographed image #2" is stored in "Photographed image," but in reality, image data, etc. is stored. For example, the URL (Uniform Resource Locator) where the image data is located, or a file path name indicating the storage location, may be stored. "Setting type information" indicates the type information set by the model. In the example shown in Figure 7, conceptual information such as "Setting type information #1" and "Setting type information #2" is stored in "Setting type information," but in reality, information such as "Face type: Fresh; Hair type: Straight; ..." is stored. "Model information" indicates model information related to the model, such as the model's following relationships and purchase history. In the example shown in Figure 7, conceptual information such as "Model Information #1" and "Model Information #2" is stored in "Model Information," but in reality, information such as "Following: User P111, User P112, ...; Followers: User P211, User P212, ...; Purchase History: Product F1, Product F2, ...; ..." is stored.

The evaluation information storage unit 122 stores evaluation information made by posters (for example, evaluation information indicating how well makeup suits them). Figure 8 shows an example of the evaluation information storage unit 122 according to the embodiment. As shown in Figure 8, the evaluation information storage unit 122 has items such as "Evaluation Information ID," "Contributor ID," "Model ID," and "Evaluation Information."

"Evaluation Information ID" indicates identification information for identifying the evaluation information. "Contributor ID" indicates identification information for identifying the contributor who made the evaluation. "Model ID" indicates identification information for identifying the evaluated model. "Evaluation Information" indicates the evaluation information of the contributor. In the example shown in Figure 8, conceptual information such as "Evaluation Information #1" and "Evaluation Information #2" is stored in "Evaluation Information," but in reality, information such as a combination of makeup information applied to the model and the contributor's evaluation (suits, does not suit, etc.) is stored.

(Control unit 130)
The control unit 130 is a controller, and is realized, for example, by a CPU, an MPU, or the like, executing various programs stored in a storage device inside the information processing device 100 using RAM as a work area. The control unit 130 is also realized, for example, by an integrated circuit such as an ASIC or an FPGA.

As shown in FIG. 6, the control unit 130 has an acquisition unit 131, an identification unit 132, an extraction unit 133, a first display unit 134, a generation unit 135, a second display unit 136, and a determination unit 137, and realizes or executes the information processing functions described below. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in FIG. 6, and may be any other configuration that performs the information processing described below.

(Acquisition unit 131)
The acquisition unit 131 acquires various types of information from an external information processing device, such as the terminal device 10.

The acquisition unit 131 acquires various types of information from the storage unit 120. The acquisition unit 131 also stores the acquired various types of information in the storage unit 120.

The acquisition unit 131 acquires images taken by the poster to which the fashion measure has been applied. The acquisition unit 131 also acquires thumbnail images of models who are candidates for applying the fashion measure. The acquisition unit 131 also acquires selection information selected by the poster from among the thumbnail images. The acquisition unit 131 also acquires evaluation information if the poster has made an evaluation.

(Specific unit 132)
The identification unit 132 identifies the makeup information of the poster by extracting mask information from the photographed image of the poster. For example, the identification unit 132 identifies the makeup information by extracting mask information from the photographed image acquired by the acquisition unit 131.

(Extraction unit 133)
The extraction unit 133 extracts at least one thumbnail image of a model who is a candidate for applying a fashion measure based on a predetermined condition. For example, the extraction unit 133 extracts at least one thumbnail image of a model who is a candidate for applying a fashion measure based on a predetermined condition from among the thumbnail images of models who are candidates for applying a fashion measure and acquired by the acquisition unit 131. For example, the extraction unit 133 extracts at least one thumbnail image of a model who is a candidate for applying a fashion measure in order of the model's highest rating indicating how well makeup suits them (the higher the rating indicating how well makeup suits them, the more priority is given to extracting at least one thumbnail image). Furthermore, for example, the extraction unit 133 extracts at least one thumbnail image of a model who is a candidate for applying a fashion measure in order of the model's facial type similar to that of followers (the more similar the facial type of a model is to followers, the more priority is given to extracting at least one thumbnail image). Furthermore, for example, the extraction unit 133 extracts at least one thumbnail image of a model who is a candidate for applying a fashion measure in order of the model's highest number of logins (the more priority is given to extracting at least one thumbnail image of a model with a highest number of logins).

(First display section 134)
The first display unit 134 displays thumbnail images of models who are candidates for applying the fashion measure. For example, the first display unit 134 displays thumbnail images extracted by the extraction unit 133 (at least one thumbnail image extracted based on a predetermined condition). The first display unit 134 may also perform the extraction process of the extraction unit 133.

The first display unit 134 preferentially displays thumbnail images on the preview screen in a predetermined display format (for example, in a predetermined display format determined by the determination unit 137 described below). The first display unit 134 may also perform the determination process of the determination unit 137 described below. The first display unit 134, for example, preferentially displays thumbnail images of models highly rated for how well makeup suits them. For example, the first display unit 134 preferentially displays thumbnail images of models highly rated for how well makeup suits them from among the thumbnail images extracted by the extraction unit 133. For example, the first display unit 134 preferentially displays thumbnail images of models highly rated for how well makeup suits them by sorting the thumbnail images extracted by the extraction unit 133 in descending order of the ratings indicating how well makeup suits them. The first display unit 134 also preferentially displays thumbnail images of models highly rated for how well makeup suits them, for example, for each of the subdivided face types.

The first display unit 134, for example, preferentially displays thumbnail images of models whose facial type is similar to that of the poster. For example, the first display unit 134 preferentially displays thumbnail images of models whose facial type is similar to that of the poster from among the thumbnail images extracted by the extraction unit 133. For example, the first display unit 134 preferentially displays thumbnail images of models whose facial type is similar to that of the poster by sorting the thumbnail images extracted by the extraction unit 133 in order of similarity of facial type to that of the poster.

The first display unit 134, for example, based on the poster's follower information, preferentially displays thumbnail images of models with a high proportion of followers who have a specific face type. For example, if a specific face type is prevalent among the face types of followers, the first display unit 134 preferentially displays thumbnail images of models with the specific face type. Furthermore, the first display unit 134, for example, based on the model's login information, preferentially displays thumbnail images of models with a specific face type and a high proportion of logins. For example, if a specific face type is prevalent among the face types of models with a high proportion of logins, the first display unit 134 preferentially displays thumbnail images of models with the specific face type. Furthermore, for example, if there are multiple specific face types prevalent among the face types of models with a high proportion of logins, the first display unit 134 preferentially displays thumbnail images of models with the specific face type for each of the subdivisions of the face type.

(Generation unit 135)
The generation unit 135 generates an image to which a fashion measure has been applied. For example, the generation unit 135 generates an image to which a fashion measure has been applied to a thumbnail image selected by a poster, based on the selection information acquired by the acquisition unit 131. For example, the generation unit 135 generates fashion measure information for generating an image to which a fashion measure similar to the fashion measure of the poster has been applied, using a method such as PSGAN. For example, the generation unit 135 generates an image to which the generated fashion measure information has been applied to a model.

(Second display section 136)
The second display unit 136 displays an image to which the fashion measure has been applied. For example, the second display unit 136 displays an image (an image to which the fashion measure has been applied) generated by the generation unit 135. The second display unit 136 may also perform the generation process of the generation unit 135.

(Determination unit 137)
The determination unit 137 determines a predetermined display mode for displaying thumbnail images on the preview screen (for example, determines a predetermined display mode for preferential display by the first display unit 134). For example, the determination unit 137 determines the display mode of thumbnail images when displaying them in a predetermined area (area R1) on the screen C1. That is, for example, the determination unit 137 determines thumbnail images to be displayed on the preview screen. For example, the determination unit 137 determines that thumbnail images of models with high ratings indicating how well makeup suits them are to be preferentially displayed. For example, the determination unit 137 determines thumbnail images to be preferentially displayed by sorting the thumbnail images in descending order of ratings indicating how well makeup suits them. For example, the determination unit 137 determines a display mode of thumbnail images in which models with higher ratings indicating how well makeup suits them are preferentially displayed by sorting the thumbnail images in descending order of ratings indicating how well makeup suits them.

The determination unit 137 determines, for example, to preferentially display thumbnail images of models whose facial type is similar to the poster. For example, the determination unit 137 determines thumbnail images to be preferentially displayed by sorting the images in order of similarity of facial type to the poster. For example, the determination unit 137 determines a display mode of thumbnail images such that the more similar the facial type to the poster is, the more preferentially displayed the thumbnail images are, by sorting the images in order of similarity of facial type to the poster. Furthermore, the determination unit 137 determines, for example, to preferentially display thumbnail images of models who have a higher proportion of followers with a specific facial type. For example, the determination unit 137 determines thumbnail images to be preferentially displayed by sorting the images in order of the highest proportion of followers with a specific facial type. For example, the determination unit 137 determines a display mode of thumbnail images such that the higher the proportion of followers with a specific facial type is, the more preferentially displayed the thumbnail images are, by sorting the images in order of the highest proportion of followers with a specific facial type. Furthermore, the determination unit 137 determines to preferentially display thumbnail images of models who have a higher proportion of logins with a specific facial type. For example, the determination unit 137 determines thumbnail images to be preferentially displayed by sorting them in descending order of the proportion of logins of models with a specific face type. For example, the determination unit 137 determines a display mode for thumbnail images in which models with a specific face type have a higher proportion of logins, by sorting them in descending order of the proportion of logins of models with a specific face type.

5. Information Processing Flow
Next, the procedure of information processing by the information processing system 1 according to the embodiment will be described with reference to Fig. 9 and Fig. 10. Fig. 9 and Fig. 10 are flowcharts showing the procedure of information processing by the information processing system 1 according to the embodiment. Fig. 9 is a flowchart showing the procedure of information processing including processing for extracting thumbnail images of models based on predetermined conditions, and Fig. 10 is a flowchart showing the procedure of information processing including processing for preferentially displaying thumbnail images of models (rearranging them to the top) based on a predetermined display mode.

As shown in FIG. 9, the information processing device 100 acquires an image taken by a poster to which a fashion measure has been applied (step S201). The information processing device 100 extracts at least one thumbnail image of a model that is a candidate for applying the fashion measure based on predetermined conditions (step S202). The information processing device 100 displays the extracted thumbnail image on a preview screen (step S203).

The information processing device 100 determines whether the poster has selected a thumbnail image (step S204). If the poster has selected a thumbnail image (step S204; YES), the information processing device 100 generates an image to which the fashion measure has been applied (step S205). The information processing device 100 displays the generated image on the preview screen (step S206). On the other hand, if the poster has not selected a thumbnail image (step S204; NO), the information processing device 100 ends information processing. In this case, the poster may post without confirming the application of the fashion measure.

As shown in FIG. 10, the information processing device 100 acquires an image taken by the poster to which the fashion measure has been applied (step S301). The information processing device 100 extracts at least one thumbnail image of a model who is a candidate for applying the fashion measure (step S302). The information processing device 100 preferentially displays the extracted thumbnail image on the preview screen in a predetermined display format (step S303).

The information processing device 100 determines whether the poster has selected a thumbnail image (step S304). If the poster has selected a thumbnail image (step S304; YES), the information processing device 100 generates an image to which the fashion measure has been applied (step S305). The information processing device 100 displays the generated image on the preview screen (step S306). On the other hand, if the poster has not selected a thumbnail image (step S304; NO), the information processing device 100 ends information processing. In this case, the poster may post without confirming the application of the fashion measure.

6. Effects
As described above, the information processing device 100 according to the embodiment includes an acquisition unit 131, a first display unit 134, and a second display unit 136. The acquisition unit 131 acquires images taken by the poster to which a fashion measure has been applied. The first display unit 134 extracts and displays at least one thumbnail image of a model who is a candidate to apply the fashion measure based on predetermined conditions. When the poster specifies a thumbnail image, the second display unit 136 displays an image in which the fashion measure has been applied to the model.

As a result, the information processing device 100 according to the embodiment can, for example, check before posting whether a fashion campaign is likely to lead to conversions.

In addition, the first display unit 134 extracts and displays thumbnail images based on an evaluation indicating the degree to which a fashion measure suits a specific type of part of the model's appearance.

As a result, the information processing device 100 according to the embodiment can, for example, take into account the degree to which a fashion campaign suits the model and check the type of model that is likely to lead to conversions before posting.

In addition, the first display unit 134 extracts and displays thumbnail images of models whose appearances are similar to those of the poster.

As a result, the information processing device 100 according to the embodiment can, for example, take into account the degree of similarity in style with the poster and check before posting whether the fashion campaign is likely to lead to conversions.

In addition, the first display unit 134 extracts and displays thumbnail images of the model based on the poster's follower information.

As a result, the information processing device 100 according to the embodiment can, for example, take into account the poster's follower information and check before posting whether the fashion campaign is likely to lead to conversions.

In addition, the first display unit 134 extracts and displays thumbnail images of models whose specific features are similar to those of the poster's followers.

As a result, the information processing device 100 according to the embodiment can, for example, take into account the degree of similarity in style between the poster and their followers, and check before posting whether the fashion campaign is likely to lead to conversions.

In addition, the first display unit 134 extracts and displays a thumbnail image of the model based on the model's login information.

As a result, the information processing device 100 according to the embodiment can, for example, take into account the model's login information and check before posting whether the fashion campaign is likely to lead to conversions.

In addition, the first display unit 134 extracts and displays thumbnail images of models estimated to be highly likely to try on the fashion campaign.

As a result, the information processing device 100 according to the embodiment can, for example, take into account the possibility of trying on clothes and check before posting whether the fashion initiative is likely to lead to conversions.

7. Hardware Configuration
The terminal device 10 and the information processing device 100 according to the above-described embodiments are realized, for example, by a computer 1000 configured as shown in Fig. 11. Fig. 11 is a hardware configuration diagram showing an example of a computer that realizes the functions of the terminal device 10 and the information processing device 100. The computer 1000 has a CPU 1100, a RAM 1200, a ROM 1300, a HDD 1400, a communication interface (I/F) 1500, an input/output interface (I/F) 1600, and a media interface (I/F) 1700.

The CPU 1100 operates based on programs stored in the ROM 1300 or HDD 1400, and controls each component. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 starts up, as well as programs that depend on the computer 1000's hardware.

The HDD 1400 stores programs executed by the CPU 1100 and data used by such programs. The communication interface 1500 acquires data from other devices via a specified communication network and sends it to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via a specified communication network.

The CPU 1100 controls output devices such as displays and printers, and input devices such as keyboards and mice, via the input/output interface 1600. The CPU 1100 acquires data from input devices via the input/output interface 1600. The CPU 1100 also outputs generated data to output devices via the input/output interface 1600.

Media interface 1700 reads programs or data stored on recording medium 1800 and provides them to CPU 1100 via RAM 1200. CPU 1100 loads the programs from recording medium 1800 onto RAM 1200 via media interface 1700 and executes the loaded programs. Recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase Change Rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical Disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

For example, when the computer 1000 functions as the terminal device 10 and information processing device 100 according to the embodiment, the CPU 1100 of the computer 1000 executes programs loaded onto the RAM 1200 to realize the functions of the control units 14 and 130. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, the CPU 1100 may obtain these programs from another device via a specified communications network.

[8. Other]
Furthermore, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically using known methods. In addition, the information including the processing procedures, specific names, various data, and parameters shown in the above documents and drawings can be changed as desired unless otherwise specified. For example, the various information shown in each drawing is not limited to the information shown in the drawings.

Furthermore, the components of each device shown in the figure are functional concepts and do not necessarily have to be physically configured as shown. In other words, the specific form of distribution and integration of each device is not limited to that shown, and all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc.

Furthermore, the above-described embodiments can be combined as appropriate to the extent that the processing content is not contradictory.

The above describes in detail some of the embodiments of the present application based on the drawings, but these are merely examples, and the present invention can be implemented in other forms that incorporate various modifications and improvements based on the knowledge of those skilled in the art, including the aspects described in the Disclosure of the Invention section.

Furthermore, the "parts" (section, module, unit) mentioned above can be read as "means" or "circuit." For example, an acquisition unit can be read as an acquisition means or an acquisition circuit.

REFERENCE SIGNS LIST 1 Information processing system 10 Terminal device 11 Communication unit 12 Input unit 13 Output unit 14 Control unit 100 Information processing device 110 Communication unit 120 Storage unit 121 Model information storage unit 122 Evaluation information storage unit 130 Control unit 131 Acquisition unit 132 Identification unit 133 Extraction unit 134 First display unit 135 Generation unit 136 Second display unit 137 Determination unit 141 Reception unit 142 Transmission unit N Network

Claims (9)

an acquisition unit that acquires a photographed image of a poster to which the fashion measure has been applied;
a first display unit that extracts and displays at least one thumbnail image of a model that is a candidate for applying the fashion measure based on a predetermined condition;
a second display unit that displays an image in which the fashion measure is applied to the model when the contributor designates the thumbnail image;
An information processing device comprising: The first display unit
The information processing device according to claim 1 , wherein the thumbnail images are extracted and displayed based on an evaluation indicating a degree to which the fashion measure suits a type of a predetermined part of the model's appearance. The first display unit
The information processing device according to claim 1 , wherein the thumbnail images of the models similar in type to the poster in a predetermined part of their appearance are extracted and displayed. The first display unit
The information processing device according to claim 1 , wherein the thumbnail image of the model is extracted and displayed based on follower information of the poster. The first display unit
The information processing device according to claim 3 , wherein the thumbnail images of the models whose types of the predetermined features are similar to those of the followers of the poster are extracted and displayed. The first display unit
The information processing apparatus according to claim 1 , wherein the thumbnail image of the model is extracted and displayed based on login information of the model. The first display unit
The information processing device according to claim 5 , wherein the thumbnail image of the model estimated to be highly likely to try on the fashion campaign is extracted and displayed. 1. A computer-implemented information processing method, comprising:
an acquisition step of acquiring an image taken by the poster to which the fashion measure has been applied;
a first display step of extracting and displaying at least one thumbnail image of a model that is a candidate for applying the fashion measure based on a predetermined condition;
a second display step of displaying an image in which the fashion measure is applied to the model when the contributor designates the thumbnail image;
An information processing method comprising: A procedure for acquiring images taken by a poster to which the fashion campaign has been applied;
a first display step of extracting and displaying at least one thumbnail image of a model that is a candidate for applying the fashion measure based on a predetermined condition;
a second display step of displaying an image in which the fashion measure is applied to the model when the contributor designates the thumbnail image;
An information processing program characterized by causing a computer to execute the above.