KR102650580B1 - Server apparatus and method for recommending cloth thereby - Google Patents

Abstract

Receiving scan data of a user's body from a user terminal or scanning device; determining the user's body type based on the received scan data; Selecting clothing corresponding to the determined body type; and transmitting information about the selected clothing to the user terminal. A clothing recommendation method by a server device according to an embodiment of the present invention is disclosed.

Description

Server device and method of recommending clothing using the same {SERVER APPARATUS AND METHOD FOR RECOMMENDING CLOTH THEREBY}

The present invention relates to a server device and a clothing recommendation method using the same. More specifically, the present invention relates to a server device that recommends customized clothing that may suit a user and a clothing recommendation method using the same.

Recently, the use of online shopping is increasing due to the development of Internet technology. Users can easily purchase desired goods or services through computers, smartphones, etc. In particular, in the case of clothing, because accessibility to offline stores, which are mainly located in department stores, is not as good as for other products, users are purchasing a lot of clothing through online shopping.

However, when purchasing clothing online, there are very low conversion rates and high return rates due to users' dissatisfaction with the fitting. To improve this, virtual fitting technology has emerged, but the clothing purchasing process itself in online shopping is not efficient, and users still have problems finding clothing that suits them.

The purpose of a server device and a clothing recommendation method using the same according to an embodiment of the present invention is to enable users to more easily select clothing that suits them.

Additionally, another purpose of the server device and the clothing recommendation method using the same according to an embodiment of the present invention is to reduce the return rate of users in online shopping and improve the profitability of online servers that sell clothing.

A clothing recommendation method according to an embodiment of the present invention includes receiving 3D scan data of a user's body from a user terminal or scanning device; Obtaining second 2D scan data representing the front of the user from the received 3D scan data, and determining the user's body type based on feature points extracted from the second 2D scan data; selecting clothing corresponding to the determined body type; And transmitting information about the selected clothing to the user terminal, wherein the feature point includes the user's SP (shoulder point) extracted from the outline of the second body image of the second 2D scan data. In the step of determining the user's body type, the second body image is divided into a plurality of closed curves, an AP (Armpit Point) is determined considering the planar shape of the divided closed curve, and the AP is located in the vertical direction of the determined AP. Among the points, the point located on the outline of the second body image may be determined as the SP.

Here, the step of determining the user's body type includes extracting the user's elbow point (EP) and waist point (WP) from the outline of the second body image of the second 2D scan data; And it may include comparing the positions of the user's WP and EP to determine the user's body type.

Here, the clothing recommendation method further includes the step of determining a corresponding body type for each of a plurality of clothing, and the selecting step includes selecting clothing corresponding to the determined body type among the plurality of clothing. Additional steps may be included.

Here, the step of selecting the clothing may include selecting a predetermined number of clothing in order of user preference while corresponding to the determined body type among the plurality of clothing.

Here, the clothing recommendation method may further include transmitting a web page in which clothing categories are classified by body type to the user terminal.

Here, the clothing recommendation method further includes transmitting a message requesting re-scanning to the user terminal or the scanning device when the shape of the user's body image included in the user's scan data is different from a preset shape. can do.

Here, the clothing recommendation method includes obtaining the user's BMI index calculated based on the user's height and weight; and determining the user's degree of obesity according to the calculated BMI, wherein the selecting step may include selecting the clothing by further considering the degree of obesity.

Some of the effects that can be achieved by the server device and the clothing recommendation method according to an embodiment of the present invention are as follows.

i) Users can more easily choose clothing that suits them.

ii) User return rates in online shopping may be reduced.

iii) The profitability of online servers that sell clothing can be improved.

However, the effects that can be achieved by the server device and the clothing recommendation method using the same according to an embodiment of the present invention are not limited to those mentioned above, and other effects not mentioned can be understood from the description below to which the present invention belongs. It will be clearly understandable to those with ordinary knowledge in the technical field.

1 is an exemplary diagram showing a user terminal, a server device, and a scanning device according to an embodiment of the present invention.
Figure 2 is a flowchart showing a clothing recommendation method according to an embodiment of the present invention.
Figure 3 is an exemplary diagram showing the types of body types of users.
Figure 4 is a flowchart showing a method for determining a user's first body type.
Figures 5(a) and 5(b) are diagrams to explain a method of extracting a user's BP, WP, and HP.
Figure 6 is a flowchart showing a method of determining a user's first body type through comparison of WHR and WCR.
Figure 7 is a diagram for explaining another method of determining a user's first body type.
FIGS. 8(a) to 8(d) are diagrams for explaining a method of determining the AP of a second body image.
Figure 9 is a diagram for explaining a method of determining a user's second body type.
Figure 10 is a diagram for explaining another method of determining a user's second body type.
Figure 11 is a block diagram showing the configuration of a server device according to another embodiment of the present invention.

Since the present invention can make various changes and have various embodiments, specific embodiments will be illustrated in the drawings and described in detail through detailed description. However, this is not intended to limit the present invention to specific embodiments, and the present invention should be understood to include all changes, equivalents, and substitutes included in the spirit and technical scope of the present invention.

In describing the present invention, if it is determined that a detailed description of related known technologies may unnecessarily obscure the gist of the present invention, the detailed description will be omitted. In addition, numbers (eg, first, second, etc.) used in the description of this specification are merely identifiers to distinguish one component from another component.

In addition, in this specification, when a component is referred to as "connected" or "connected" to another component, the component may be directly connected or directly connected to the other component, but specifically Unless there is a contrary description, it should be understood that it may be connected or connected through another component in the middle.

Additionally, in this specification, components expressed as '~unit', 'module', etc. refer to hardware components such as software, FPGA, or ASIC, and these components perform certain roles. However, a component is not limited to software or hardware. A component may be configured to reside on an addressable storage medium. Additionally, two or more components may be combined into one component, or one component may be differentiated into two or more components according to more detailed functions. In addition, each of the components described below may additionally perform some or all of the functions of other components in addition to the main functions that each component is responsible for, and some of the main functions of each component may be different from other components. Of course, it can also be performed exclusively by a component.

Meanwhile, in this specification, 'clothing' refers to something worn on the body by humans and may include, but is not limited to, outerwear, underwear, socks, hats, gloves, scarves, etc.

Hereinafter, exemplary embodiments according to the technical spirit of the present invention will be described with reference to the drawings.

Figure 1 is an exemplary diagram showing a user terminal 100, a server device 200, and a scanning device 300 according to an embodiment of the present invention.

The user terminal 100 is a device that wishes to purchase clothing through the server device 200. The user terminal 100 is a smartphone, desktop computer, laptop computer, PDA, web pad, tablet PC, or wearable device. Any device that can communicate with the server device 200 through a predetermined network may include various types of terminal devices.

The server device 200 may include a web server. For example, the server device 200 is a device used to sell clothing online or broker sales. The server device 200 may transmit clothing information to the user terminal 100 in the form of a web page.

The user terminal 100 and the server device 200 shown in FIG. 1 are connected to each other through a network. Networks may include wired networks and wireless networks, and specifically, various networks such as local area networks (LANs), metropolitan area networks (MANs), and wide area networks (WANs). It can be included. Additionally, the network may include the known World Wide Web (WWW). However, the network according to the present invention is not limited to the networks listed above, and may include at least some of a known wireless data network, a known telephone network, or a known wired or wireless television network.

The scanning device 300 can scan the body of the user 10. Scan data generated by the scan device 300 may be transmitted to the server device 200 through a network. If the scanning device 300 does not have a network communication function, the scan data generated by the scanning device 300 is transmitted to the user terminal 100 through a separate storage medium, and the user terminal 100 receives the scan data. It can be transmitted to the server device 200 through a network. The scanning device 300 may have a voice output function or an image output function to guide the scanning posture of the user 10.

The server device 200 recommends customized clothing to the user 10 through scan data transmitted from the user terminal 100, which will be described with reference to FIGS. 2 and 3.

FIG. 2 is a flowchart showing a clothing recommendation method according to an embodiment of the present invention, and FIG. 3 is an exemplary diagram showing types of body types of the user 10.

In step S210, the server device 200 receives scan data of a body image of the user 10 from the user terminal 100 or the scanning device 300. Scan data may include, for example, 3D scan data. When the user terminal 100 accesses the server device 200 and registers as a member through a web page, the server device 200 may request the user terminal 100 to transmit scan data.

If the shape of the body image of the user 10 included in the scan data of the user 10 is different from the preset shape, the server device 200 sends a message requesting rephotography to the user terminal 100 or the scanning device ( 300). For example, the user 10 should be scanned while standing in an upright position with both arms and torso separated to some extent, but if the user 10 is scanned with both arms raised above the head, the server The device 200 requests a rescan from the user terminal 100 or the scanning device 300.

In step S220, the server device 200 determines the body type of the user 10 based on scan data received from the user terminal 100.

Figure 3 shows the types of body types of the user 10. For example, the body type of the user 10 is divided into a first type of body type, a second type of body type, and a third type of body type. It can be. Body types determined based on the same data (for example, characteristic points) all belong to the same type.

The first type of body type may include a rectangular type, a triangular type, an inverted triangle type, an oval type, and an hourglass type. The first type of body type can be determined based on BP (breast point), HP (hip point), and WP (waist point).

The second type of body type may include short leg type, balance type, and long leg type, and the second type of body type is based on WP and the height of the user (10), or EP (elbow point) and WP. can be decided.

The third type of body type may include an underweight type, an average weight type, an overweight type, and an obese type, and the third type of body type may be determined based on the height and weight of the user 10. Type 3 body type can indicate a degree of obesity.

The first type of body type, the second type of body type, and the third type of body type are just examples, and the server device 200 uses the first type of body type and the second type as the body type of the user 10. At least one of the tangible body type and the third type of body type can be determined.

In step S230, the server device 200 selects clothing corresponding to the body type of the user 10.

The server device 200 may store in advance body information that matches each piece of clothing as information about a plurality of pieces of clothing. For example, information about the silhouette of each clothing may be specified by a clothing manufacturer, and information about which silhouette of clothing suits each body type may be specified by a fashion expert. Specifically, when the clothing manufacturer designates the silhouette of the dress he produced as 'sheath' and the fashion expert designates that the dress with the 'sheath' silhouette is suitable for the user 10 with an inverted triangle body type, the server device 200 If the body type of the user 10 is determined to be an inverted triangle, a dress with a 'sheath' silhouette can be selected as clothing that suits the user 10.

The server device 200 may select clothing corresponding to the body type determined in step S220 from among a plurality of clothing, or, among a plurality of clothing, corresponding to the body type determined in step S220, in the order of high preference of the users 10. You can also select a certain number of clothes. Several users 10 may input their preferences for clothing recommended by the server device 200 through their user terminal 100 .

In step S240, the server device 200 may transmit information about the clothing selected in step S230, for example, a clothing image and price information of the clothing, to the user terminal 100.

The server device 200 may generate a 3D avatar of the user 10 using the scan data of the user 10. In step S240, the server device 200 virtually fits the 3D image of the selected clothing to the 3D avatar. It can also be transmitted to the user terminal 100. Since the method of creating a 3D image of the user 10's 3D avatar and clothing and performing virtual fitting is well known to those skilled in the art, a detailed description thereof will be omitted in this specification.

The user terminal 100 may determine whether to purchase the corresponding clothing by referring to the clothing image virtually fitted to the user's 3D avatar and the price information of the clothing. When the user terminal 100 requests the purchase of clothing, the server device 200 performs a payment process for the user terminal 100 or forwards the connection of the user terminal 100 to a separate sales server. , you can proceed with the payment process on the server.

Meanwhile, when the server device 200 transmits a web page containing a plurality of clothing information to the user terminal 100, the server device 200 may classify the plurality of clothing information by body type and include them in the web page. For example, the server device 200 includes clothing that matches body type A in the category of body type A, clothing that matches body type B in the category of body type B, and clothing that matches body type C in the category of body type C. It can be included in the category of body type.

According to a conventional clothing web page, clothing is classified based on gender (men, women, children, etc.), type of clothing (jeans, skirts, etc.), and according to this, the user 10 finds clothing that suits him or her. There is a problem that it becomes difficult.

Since the server device 200 according to an embodiment of the present invention classifies clothing categories according to body type, from the user's 10 perspective, as long as he or she knows his or her body type, he or she can easily check information on clothing that suits him or her well. .

Next, referring to FIGS. 4 to 6 , a method for determining the first body type of the user 10 will be described.

Figure 4 is a flowchart showing a method for determining the first body type of the user 10, and Figures 5(a) and 5(b) are for explaining a method for extracting the user's BP, WP, and HP. It is a drawing. Additionally, FIG. 6 is a flowchart showing a method of determining the first body type of the user 10 through comparison of WHR and WCR.

In step S410, the server device 200 obtains first 2D scan data representing the side of the user 10 from the 3D scan data of the user 10. The server device 200 may acquire first 2D scan data by projecting the 3D scan data in the side direction of the user 10. FIG. 5(a) shows a first body image 510 of first 2D scan data obtained from 3D scan data.

In step S420, the server device 200 extracts the feature point of the user 10 from the contour of the first body image of the first 2D scan data. At this time, the feature point of the user 10 is BP (breast point). ), HP (hip point), and WP (waist point).

When explaining how the server device 200 determines BP, HP, and WP with reference to FIG. 5(b), first, the server device 200 determines a reference line (R) passing inside the first body image 510. Then, three areas (520a, 520b, 520c) for extracting BP (532), HP (534), and WP (536) are set in the first body image.

The server device 200 uses various methods used in the 3D body modeling field to create three regions 520a, 520b, and 520c in the first body image 510, namely, the chest region 520a and the waist region 520b. and hip area 520c can be set. For example, the server device 200 may use first 2D scan data representing the side of the user 10 or second 2D scan data representing the front of the user 10, obtained from the 3D scan data of the user 10. By applying the superquadric technique to scan data, three areas 520a, 520b, and 520c can be set in the first body image 510 of the user 10. When three areas are set in the second body image of the second 2D scan data, the first body image 510 is created by mapping the three areas to the first body image 510 of the first 2D scan data. Three areas (520a, 520b, 520c) can also be set. The superquadric technique is described in 'Building Superquadric Men from 3D Whole-Body Scan Data', Yijun Xiao and J. Paul Siebert, etc., so detailed explanation will be omitted.

Next, the server device 200 considers the distance between the outlines 512 and 514 of the first body image 510 and the reference line R, and moves the image in one direction of the reference line R, for example, in the front direction. BP 532 is extracted from the outline 512 of the located first body image 510. Specifically, in the chest area 520a set for the first body image 510, the distance from the reference line (R) among the outlines 512 of the first body image 510 located in one direction of the reference line (R) The farthest point from (d1) can be extracted as BP (532).

The server device 200 considers the distance between the outlines 512 and 514 of the first body image 510 and the reference line R, and determines the first body image located in the other direction, for example, the rear direction, of the reference line R. 1 HP (534) is extracted from the outline (514) of the body image (510). Specifically, in the hip area 520c set for the first body image 510, the distance from the reference line (R) among the outlines 514 of the first body image 510 located in the other direction of the reference line (R) The farthest point from (d2) can be extracted as HP (534).

Finally, the server device 200 considers the outlines 512 and 514 of the first body image 510 and determines the first body image 510 located in the other direction of the reference line R, for example, in the rear direction. WP (536) is extracted from the outline (514) of ). Specifically, in the waist region 536 set for the first body image 510, the point with the greatest curvature among the outlines 514 of the first body image 510 located in the other direction of the reference line (R) is designated as WP. It can be extracted as (536).

In step S430, the server device 200 measures chest circumference including BP, waist circumference including WP, and hip circumference including HP from 3D scan data.

In step S440, the server device 200 configures the user ( 10) Determine the first type of body type.

Figure 6 shows a method of determining the first body type of the user 10 through comparison of WHR and WCR. First, in step S605, it is determined whether WHR is greater than WCR plus δ1. In step S610, when the WHR is greater than the value obtained by adding δ1 to the WCR, the server device 200 determines the body type of the user 10 as a triangle type.

In step S615, if the WHR is not greater than the value obtained by adding δ1 to the WCR, the server device 200 determines whether the WCR is greater than the value obtained by adding δ1 to the WHR. In step S620, when the WCR is greater than the value obtained by adding δ1 to the WHR, the server device 200 determines the body type of the user 10 as an inverted triangle type.

In step S625, if the WCR is not greater than the value of adding δ1 to the WHR, the server device 200 determines that the chest circumference (C) is greater than the value of adding δ2 to the waist circumference (W) and the waist circumference (W) Determine whether the hip circumference (H) is larger than the value added by δ2.

If the chest circumference (C) is greater than the waist circumference (W) plus δ2 and the hip circumference (H) is greater than the waist circumference (W) plus δ2, in step S630, the server device 200 determines the body type of the user 10 to be hourglass.

If the chest circumference (C) is not greater than the waist circumference (W) plus δ2, or the hip circumference (H) is not greater than the waist circumference (W) plus δ2, in step S635, the server device ( 200) determines whether the chest circumference is greater than the waist circumference and the hip circumference is greater than the waist circumference.

In step S640, if the chest circumference is greater than the waist circumference and the hip circumference is greater than the waist circumference, the server device 200 determines the body type of the user 10 as rectangular, and in step S645, the server device 200 determines the body type of the user 10 to be rectangular, and in step S645, the server device 200 determines the body type of the user 10 to be rectangular. If it is not large or the hip circumference is not larger than the waist circumference, the body type of the user 10 is determined to be oval.

Meanwhile, δ1 and δ2 in FIG. 6 may vary depending on the nationality information, age information, and gender information of the user 10. The server device 200 can more accurately determine the body type of the user 10 by acquiring the nationality information, age information, and gender information of the user 10, and determining δ1 and δ2 corresponding to the obtained information. For example, δ1 and δ2 of a user 10 of Western nationality may be determined to be larger than δ1 and δ2 of a user 10 of Eastern nationality.

Meanwhile, in order to determine the first body type of the user 10, the waist width and shoulder width of the user 10 may be used. This will be explained with reference to FIGS. 7 and 8.

FIG. 7 is a diagram showing a second body image 710 of second 2D scan data representing the front of the user 10, and FIGS. 8(a) to 8(d) show the second body image 710. This is a diagram to explain how to determine the AP (armpit point) of .

As shown in FIG. 7, the server device 200 selects two WPs 720a from the second body image 710 of the second 2D scan data of the user 10 obtained from the 3D scan data of the user 10. , 720b) and two SPs (730a, 730b), then the user ( 10) The first type of body type can be determined. For example, if the shoulder width (w2) is greater than the waist width (w1) plus a predetermined value, the body type of the user 10 may be determined to be an inverted triangle type.

The server device 200 may determine the first body type of the user by further considering the hip width along with the waist width (w1) and shoulder width (w2). For example, by substituting the ratio between the waist width (w1) and the shoulder width (w2) into the WCR of Figure 6, and the ratio between the waist width (w1) and the hip width (w2) into the WHR of Figure 6, the user The first type of body type can be determined.

The server device 200 may determine the waist area in the second body image 710 of the second 2D scan data and then determine two WPs 720a and 720b based on the curvature of the outline. Depending on the implementation, the server device 200 determines the WP in the first body image of the first 2D scan data in the manner described above with respect to FIG. 5(b), and then draws a line 722 passing through the determined WP. After mapping to the second body image 710 of the second 2D scan data, the point where the mapped line 722 and the outline of the second body image 710 meet is determined as two WPs 720a and 720b. It may be possible.

In order to obtain two SPs 730a and 730b from the second body image 710, armpit points (APs) 740a and 740b of the second body image 710 must first be extracted. The second body image 710 shown in FIG. 8(a) can be divided into a plurality of closed curves as shown in FIG. 8(b), and APs 740a and 740b can be determined by considering the planar shape of these divided closed curves. there is. As shown in FIG. 8(c), the fact that the planar shape is made up of three closed curves means that the planar shape represents both arms and torso of the user 10, so the highest among the planar shapes made up of three closed curves is APs 740a and 740b can be determined from portions corresponding to the plane shape in which they are located.

Referring again to FIG. 7, the server device 200 divides the points located on the outline of the second body image 710 among the points located in the vertical direction of the two determined APs 740a and 740b into two SPs 730a and 730b. ) can be determined.

FIG. 9 is a diagram for explaining a method of determining the second body type of the user 10.

The server device 200 extracts the HP 920 from the first body image 910 in the first 2D scan data through the method described with reference to FIG. 5(b). Next, the server device 200 calculates the distance H1 between the top 930 and the bottom 940 of the first body image 910, and the HP 920 and the bottom 940 of the first body image 910. ) The second body type of the user 10 is determined by comparing the distance H2 between them.

For example, if (H1/2) is greater than H2, the server device 200 determines the body type of the user 10 to be a short leg type, and if (H1/2) is equal to H2, the user 10 )'s body type may be determined as a balance type, and if (H1/2) is smaller than H2, the body type of the user 10 may be determined as a long leg type.

FIG. 10 is a diagram for explaining another method of determining the second body type of the user 10.

For another method to determine the second body type of the user 10, the user 10 must be scanned in a straight posture with both arms bent, as shown in FIG. 10.

The server device 200 extracts the WP 1030 of the user 10 from the second body image 1010 of the second 2D scan data representing the front of the user 10. The method of extracting the WP 1030 from 2D scan data representing the user's front view has been described with reference to FIG. 7, and detailed description will be omitted.

Additionally, the server device 200 extracts the elbow point (EP) 1020 of the user 10 from the second body image 1010 of the second 2D scan data showing the front of the user 10. As described with reference to FIG. 8, the server device 200 divides the second body image 1010 shown in FIG. 10 into a plurality of closed curves and extracts EP 1020 by considering the planar shape of the divided closed curves. can do. Below the point where EP (1020) exists, the number of closed curves will be reduced from three to one, so EP (1020) can be extracted according to the positions of the closed curves on both sides of the three closed curves when the closed curve is reduced from three to one. You can.

The server device 200 may determine the body type of the user 10 by comparing the positions of the WP 1030 and the EP 1020, for example, the server device 200 may determine the body type of the user 10 by comparing the positions of the WP 1030 and the EP 1020. By comparing the distance (H3) between the lowest end (1040) and EP (1020) and the distance (H4) between the lowest end (1040) and WP (1030), if H3 is greater than H4, it is a short leg type, and H3 and H4 are the same. If H3 is smaller than H4, you can decide on the balance type and long gray type.

Meanwhile, the server device 200 can obtain the height and weight of the user 10 and determine the third body type of the user 10 using the BMI index calculated from the height and weight of the user 10. there is. For example, the server device 200 compares the BMI index of the user 10 with preset values to determine whether the user 10 is underweight, average weight, overweight, or obese. Since the method of determining the degree of obesity of the user 10 using the BMI index is self-evident, detailed explanation will be omitted.

Figure 11 is a block diagram showing the configuration of a server device 1100 according to another embodiment of the present invention.

Referring to FIG. 11, a server device 1100 according to another embodiment of the present invention may include a communication unit 1110, a storage unit 1130, and a control unit 1150.

The communication unit 1110 communicates with the user terminal 100 through a network. The communication unit 1110 may transmit a web page in which a plurality of clothing information is classified by body type to the user terminal 100. The communication unit 1110 receives scan data of the user 10's body from the user terminal 100 or the scanning device 300. Additionally, the communication unit 1110 may transmit information about clothing selected as suitable for the body type of the user 10 to the user terminal 100 by the control unit 1150.

The storage unit 1130 may store information about a plurality of clothes, for example, at least one of the price of each of the plurality of clothes, the silhouette, information about which body type it suits, and a 3D image. In addition, the storage unit 1130 may further store preference information of users 10 for each body type mapped to suit each of the plurality of clothes.

The control unit 1150 determines the body type of the user 10 based on the received scan data and selects clothing corresponding to the determined body type. As the method of determining the body type of the user 10 and selecting clothing corresponding to the body type has been described above, detailed description will be omitted.

Meanwhile, so far, it has been described that the server devices 200 and 1000 according to an embodiment of the present invention determine the user's body type in order to recommend clothing to the user. However, depending on the implementation, the server devices 200 and 1000 determine the user's body type using feature points extracted from scan data and body dimensions related thereto (e.g., waist circumference, waist width, etc.) , it can be used for other purposes, such as medical diagnosis or transmission to a medical server, and the purposes for which the server devices 200 and 1000 determine the body type may vary.

The server device and clothing recommendation method according to an embodiment of the present invention enable the user 10 to more easily select clothing that suits him or her. Additionally, the server device according to an embodiment of the present invention and the method for recommending clothing using the same can reduce the return rate of users 10 in online shopping and improve the profitability of online servers that sell clothing.

Meanwhile, the above-described embodiments of the present invention can be written as a program that can be executed on a computer, and the written program can be stored in a medium.

The media may include, but is not limited to, magnetic storage media (eg, ROM, floppy disk, hard disk, etc.) and optical read media (eg, CD-ROM, DVD, etc.).

Although embodiments of the present invention have been described with reference to the attached drawings, those skilled in the art will recognize that the present invention can be implemented in other specific forms without changing its technical idea or essential features. You will understand. Therefore, the embodiments described above should be understood in all respects as illustrative and not restrictive.

100: user terminal
200, 1100: Server device
300: scanning device
1110: Ministry of Communications
1130: storage unit
1150: Control unit

Claims (8)

In the clothing recommendation method of the server device,
Receiving 3D scan data of a user's body from a user terminal or scanning device;
Obtaining second 2D scan data representing the front of the user from the received 3D scan data, and determining the user's body type based on feature points extracted from the second 2D scan data;
selecting clothing corresponding to the determined body type; and
Including transmitting information about the selected clothing to the user terminal,
The feature point includes the user's SP (shoulder point) extracted from the outline of the second body image of the second 2D scan data, and
The step of determining the user's body type is
The second body image is divided into a plurality of closed curves, an AP (Armpit Point) is determined considering the planar shape of the divided closed curve, and among the points located in the vertical direction of the determined AP, it is located on the outline of the second body image. A clothing recommendation method characterized in that the point is determined by the SP.
According to paragraph 1,
The step of determining the user's body type is,
extracting the user's elbow point (EP) and waist point (WP) from the outline of the second body image of the second 2D scan data; and
A clothing recommendation method comprising comparing the positions of the user's WP and EP to determine the user's body type.
According to paragraph 1,
The clothing recommendation method is,
For each of the plurality of garments, further comprising determining a corresponding body type,
The selection step is,
A clothing recommendation method further comprising selecting clothing corresponding to the determined body type among the plurality of clothing.
According to paragraph 3,
The step of selecting the clothing is,
A clothing recommendation method comprising the step of selecting a predetermined number of clothes from among the plurality of clothes in order of user preference while corresponding to the determined body type.
According to paragraph 1,
The clothing recommendation method is,
A clothing recommendation method further comprising transmitting a web page classified into clothing categories by body type to the user terminal.
According to paragraph 1,
The clothing recommendation method of the server device is:
When the shape of the user's body image included in the user's scan data is different from the preset shape, the step of transmitting a message requesting re-scanning to the user terminal or the scanning device. method.
According to paragraph 1,
The clothing recommendation method of the server device is:
Obtaining the user's BMI index calculated based on the user's height and weight; and
Further comprising determining the degree of obesity of the user according to the calculated BMI,
The selection step is,
A clothing recommendation method comprising selecting the clothing by further considering the degree of obesity.
A program stored in a storage medium in combination with hardware to execute the clothing recommendation method of any one of claims 1 to 7.