KR20220113210A - 3D image generation method using body and clothing data - Google Patents

Abstract

The present invention relates to a method and system for generating a three-dimensional (3D) composite image in which body information and clothing information are combined, and more particularly, to a method and system for generating a 3D composite image obtained by combining information on a user's body, data obtained by scanning clothing, and unique information on a fabric from which the clothing is manufactured. To this end, according to an embodiment of the present invention, a method for generating a 3D composite image by combining data scanned for clothing with data scanned for a user's body comprises the steps of: adjusting a distance of clothing cloud data by combining body cloud data representing the user's body, clothing cloud data representing clothing, unique information on fabric constituting clothing, and unique information on the clothing; generating 3D synthesized data in which the user's body and clothing are synthesized; and generating a 3D composite image by generating an outline and combining colors from the 3D composite data.

Description

{3D image generation method using body and clothing data}

It relates to a method of generating a 3D image using body and clothing data.

It has become common for modern people who value individuality to use the Internet as a means of acquiring information to find the current fashion and fashion that suits them. Due to this trend, various shopping malls have been created on the Internet, and one of the most popular areas is a fashion product mall including clothes. Purchasing fashion products using the Internet

Every user makes full use of the temporal and spatial freedom provided by the Internet to purchase and use the desired product at the desired time and without physical effort.

When the user checks the image provided on the web page of the fashion product mall and is interested in the image of the posted product, selects it to check detailed information, and purchases are made through this.

In the case of fashion products, products that look good in the image often feel different from the image when they are received. , there is a problem that causes financial loss.

To solve this problem, there is a method of providing fashion information through the Internet. The fashion information provision method through the Internet is to provide a coordinating service that provides a database of user information and shows the product and body type by synthesizing or creating a virtual model input by the user to provide image data for clothing products, such as clothes, glasses, shoes, and hats. There is a way to provide a coordinating solution by pre-wearing the product of your choice.

However, since the provision of coordinating services on the Internet uses a virtual model in cyberspace rather than in real life, when wearing fashion products such as clothing and hats on one's body, the overall harmony with one's taste, body characteristics, skin, and hair color It is not possible to check whether the product is correct, and therefore, there were frequent cases of returning products after purchase because they were not satisfied with the product.

In addition, if consumers go to an offline department store or shopping mall and try on clothes, they cannot judge whether they suit them on the spot. There are many cases where clothing is returned or exchanged.

There are cases where consumers try on products offline and return them even when they buy fashion products. It is a natural result that in the case of fashion products purchased online, consumers' satisfaction with the products is much lower.

Due to these problems, the reliability and satisfaction of online shopping providing services are still inevitably lowered from the point of view of consumers.

The problem to be solved by the present invention is to propose a method of generating a 3D composite image using the unique information of the fabric manufactured of the clothing in addition to the scanned clothing scan information.

Another problem to be solved by the present invention is to generate a 3D composite image using clothing point cloud data or mesh data, which has a relatively smaller data capacity than scanned clothing scan data, and synthesize the scan data with the composite image to obtain color (color) We propose a way to express

Another problem to be solved by the present invention is to propose a method of generating a 3D composite image using clothing point cloud data that can be converted according to a user's body point cloud data.

Another problem to be solved by the present invention is to propose a method of generating a 3D composite image using clothing point cloud data that varies according to the number or thickness of clothing worn on the user's body.

To this end, according to an aspect of the present invention, there is provided a method for generating a 3D composite image by combining data scanned on clothes with data scanned on a user's body, body cloud data representing the user's body and clothing cloud data representing clothes; Adjusting the distance between the clothing cloud data by combining the unique information of the fabric constituting the clothing and the unique information of the clothing, and generating 3D composite data in which the user's body and the clothing are synthesized, from the 3D composite data It involves creating an outline and combining colors to create a 3D composite image.

In addition, the 3D composite image generating method further includes generating user point cloud data representing the outer shape of the user's body, and generating clothing point cloud data representing the outer shape of the clothing, wherein the body cloud data and the The clothing cloud data may consist of point cloud data.

In addition, the 3D composite image generating method further comprises the steps of generating user mesh data representing the outer shape of the user's body, and generating the garment mesh data representing the outer shape of the garment, wherein the body cloud data and the The clothing cloud data may be formed of mesh data.

In addition, the generating of the user point cloud data may include generating the user point cloud data by scanning the user's body.

Also, in the generating of the clothing point cloud data, the clothing point cloud data may be generated by scanning the clothing.

Also, the generating of the clothing point cloud data may include generating the clothing point cloud data from the input 3D image file of the clothing.

In addition, the adjusting the distance between the clothing cloud data includes setting a plurality of reference points in the clothing point cloud data, adjusting the distance between the reference points, and a distance between each point cloud data from the reference point. It may include a detailed interval adjustment step of adjusting the .

In addition, the step of adjusting the detailed interval may include calculating the volume of the parts of the user's body, calculating the stress applied to each part of the clothing, and calculating the expandable distance according to the characteristics of the fabric. can

Also, the adjusting the distance between the clothing cloud data may include setting a movement direction of the clothing point cloud data.

Also, the adjusting the distance between the clothing cloud data may include extracting a plurality of inflection points in contact with the body from the clothing point cloud data, and calculating a shape change of the clothing point cloud data from the inflection points.

In addition, the unique information of the fabric includes the type of fiber, elasticity, the thickness of the fabric, the weight per unit area of the fabric, the breathability of the fabric, tensile strength, tear strength, abrasion strength, heat resistance, moisture mobility, stiffness, drape ( drapability), peeling, bagging properties, yarn strength, spinning properties, yarn uniformity, bending and bending properties, and filling properties.

In addition, the generating of the 3D composite image may include synthesizing first clothing point cloud data representing an appearance of the first clothing with the user's point cloud data, and synthesizing the first clothing point cloud data and then the appearance of the second clothing and synthesizing second clothing point cloud data representing can be

In addition, the 3D composite image generating method may further include rotating the 3D composite image at a set rotation speed after the step of generating the 3D composite image, wherein the rotating step is synthesized with the user's point cloud data The movement of the clothes constituting the 3D composite image may be expressed according to the unique information of the clothes corresponding to the acquired clothes point cloud data.

In addition, the method for generating a 3D composite image further includes the step of receiving the user's unique information, and the user's unique information may consist of at least one of the user's age, gender, hair color, and weight.

In addition, if at least two pieces of clothing corresponding to the clothing point cloud data to be synthesized with the user point cloud data are selected in the generating of the 3D composite image, the clothing point groups corresponding to the two pieces of clothing selected according to the unique information of the clothing Data may be sequentially synthesized into the user point cloud data.

A 3D composite image generating system according to another aspect of the present invention generates user point cloud data representing the appearance of a body from data scanned on a user's body, and a user scanner that transmits the generated user point cloud data and the user's unique information , by combining the user point cloud data, the clothing point cloud data, the input unique information of the fabric constituting the clothing, and the unique information of the clothing, a system operator server for generating a 3D composite image in which the user's body and clothing are synthesized. .

In addition, the system operator server may include a clothing store cloud data generator that generates clothing point cloud data representing the appearance of clothing from the scanned clothing data.

In addition, the system operator server includes a reference point setting unit for setting a plurality of reference points in the clothing point cloud data, a reference point adjusting unit for adjusting the distance between the reference points, and a point group for adjusting the distance between each point cloud data from the reference point It may include a data detail control unit.

In addition, the point cloud data detailed control unit includes a body analyzer that calculates the volume of parts of the user's body, a stress calculator that calculates the stress applied to each part of the clothing, and an elasticity calculator that calculates the stretchable distance of the clothes can do.

In addition, the system operator server may further include a shape control unit, and the shape control unit may extract a plurality of inflection points in contact with the body from the clothing point group data, and calculate a shape change of the clothing point group data from the inflection points.

The method and system for generating a 3D composite image combining body information and clothing information according to the present invention create a 3D composite image by combining scan data scanned on a user's body, scan data scanned on clothing, and unique information of clothing to generate a 3D composite image. It is possible to create a 3D composite image that reflects the unique characteristics of

In addition, the present invention generates a 3D composite image by reflecting the number or thickness of clothes worn in scan data (or user point cloud data) of a user's body. As described above, according to the present invention, it is possible to generate an image having the same effect as when an actual user wears the clothes by generating a 3D composite image using the unique information of the clothes.

In addition, the system operator server may conveniently manage unique information about clothes when information on clothes is provided to a clothes manufacturer.

In addition, data obtained by partially transforming scanned data of clothes in consideration of 3D synthetic data may be provided to a clothing manufacturer to produce customized clothing for the user.

1 is a diagram schematically illustrating a configuration for generating a 3D composite image according to an embodiment of the present invention.
2 shows the configuration of a user scanner according to an embodiment of the present invention.
3 is a block diagram illustrating the configuration of a system operator server according to an embodiment of the present invention.
Figure 4 shows an example of synthesizing clothes made of fabrics having different elasticity to the body according to an embodiment of the present invention.
All.
5 illustrates an example of transforming clothing point cloud data by reflecting body point cloud data according to an embodiment of the present invention.
6 is a flowchart illustrating a method for generating a 3D composite image according to an embodiment of the present invention.
7 is a flowchart illustrating a process of adjusting a distance between clothing cloud data according to an embodiment of the present invention.

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

Terms including ordinal numbers such as first, second, etc. may be used to describe various elements, but the elements are not limited by the terms. The above terms are used only for the purpose of distinguishing one component from another.

For example, without departing from the scope of the present invention, a first component may be referred to as a second component, and similarly, a second component may also be referred to as a first component. and/or includes a combination of a plurality of related listed items or any of a plurality of related listed items.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related art, and should not be interpreted in an ideal or excessively formal meaning unless explicitly defined in the present application. does not

Hereinafter, the present invention and preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a diagram schematically illustrating a configuration for generating a 3D composite image according to an embodiment of the present invention. Hereinafter, a configuration for generating a 3D composite image will be described with reference to FIG. 1 .

1 , the configuration for generating a 3D composite image includes a system operator server 100 and a user scanner 200, and the system operator server 100 includes a clothing data generator 110 and a 3D composite image generator ( 120 ), a control unit 30 , a storage server 150 , and an input unit 140 . In addition, the user scanner 200 includes a 3D scanner 205 , a communication unit 220 , a control unit 225 ,

It includes an input unit 210 and a storage unit 2015 . Of course, other configurations other than the above-described configuration may be included in the configuration for generating the 3D composite image proposed in the present invention.

The system operator server 100 scans clothes using a 3D scanner. The system operator server 100 puts the scanned clothes on the

Generates scanning data for The system operator server 100 uses the generated scanning data to create a clothing cloud

create data However, the present invention is not limited thereto, and the system operator server 100 is

Another device may be used to generate point cloud data for a clothing design. Accordingly, the system operator server 100 is

Clothing point cloud data can be generated from the 3D image file provided by the manufacturer.

Hereinafter, data capable of generating the shape of clothing is defined as clothing cloud data, and the clothing cloud data may be formed of the aforementioned point cloud data as well as mesh data. However, when the cloud data consists of point cloud data, the capacity is small, so the data processing speed may be significantly increased compared to the mesh data or shape data.

The system operator server 100 generates clothing point cloud data or clothing mesh data capable of generating a shape of clothing. To this end, sensors are attached to clothing at regular intervals, and the attached sensors can measure the relative distance between the sensors through communication between the sensors. The system operator server 100 generates clothing point group data using the relative distance information received from the sensor. However, the present invention is not limited thereto, and the system operator server 100 may generate the clothing store group data in various methods other than the above-described method.

The system operator server 100 receives data on clothes and fabrics through the input unit. That is, unique information about clothes and fabrics is input through the input unit. This will be described later.

As described above, the system operator server 100 of the present invention generates a 3D composite image using not only data on the shape or color of clothing but also unique information on the fabric from which the clothing is manufactured.

The user scanner 200 scans the user's whole body. The user scanner 200 generates user point cloud data or user mesh data capable of generating the user's full body shape by using the generated user's full body scan data. The user scanner 200 receives the user's unique information if necessary. The user's unique information includes the user's name, age (age), height, weight, gender, hair color, hair type, and the like. The user scanner 200 provides user point cloud data and user-specific information to the system operator server 100 .

The system operator server 100 generates a 3D composite image by synthesizing the user point cloud data provided from the user scanner 200 , user-specific information, and the stored clothing point cloud data. Of course, the system operator server 100 uses unique information about the far end in generating the 3D composite image. That is, even if the user point cloud data and the clothing point cloud data are the same, when the unique information of the received fabric is different, the generated 3D composite image is also a different image. Hereinafter, each configuration shown in FIG. 1 will be described in detail.

2 shows the configuration of a user scanner according to an embodiment of the present invention. Hereinafter, the configuration of a user scanner according to an embodiment of the present invention will be described in detail with reference to FIG. 2 .

Referring to FIG. 2 , the user scanner includes a 3D scanner, an input unit, a storage unit, a communication unit, and a control unit. Of course, other configurations other than the above-described configuration may be included in the user scanner proposed by the present invention.

The 3D scanner 205 scans the user's whole body. The 3D scanner 205 provides information about the scanned user's whole body to the controller 225 . As described above, the user scanner may generate user cloud data using a sensor other than the 3D scanner. Here, the cloud data may include point cloud data or mesh data.

The input unit 210 receives user-specific information. As described above, the user-specific information includes the user's age, gender, height, weight, name, and the like. Of course, other information in addition to the above-described information may be included in the user-specific information.

The controller 225 generates user point cloud data by using the scan data provided from the 3D scanner 205 . That is, user point cloud data having a relatively small data size compared to the scan data is generated. Since the user point cloud data is data that can recognize the user's shape, the data size is smaller than that of the scan data.

The control unit 225 divides the intersection distance measured between each sensor provided from the sensor into vertical and horizontal components, calculates the user's body size by combining the positional relationship between the vertical and horizontal components, and calculates the calculated user's body Create custom point cloud data using dimensions.

The control unit 225 determines that the central intersection is the mesh based on the diagonal distance, which is the measured distance from the sensor located at the outer intersection, which is the eight intersections located on the outside of the four adjacent meshes, to the central intersection, which is the central intersection of the four meshes. Calculate the protrusion distance, which is the distance protruded from the forming plane.

Also, when the protrusion distance is equal to or greater than a predetermined threshold value, the controller 225 increases the measured body size by a predetermined amount and outputs it. The control unit 225 increases and outputs the measured body size by a predetermined amount when the protruding distance continuously occurs a predetermined number of times as the protrusion distance progresses in the horizontal and vertical directions. In addition, it is preferable to use an ultrasonic distance sensor as the sensor.

The storage unit 215 stores the received user-specific information, scan data, and user point cloud data. In addition, the storage unit 215 stores data necessary to drive the user scanner.

The communication unit 220 communicates with the external system operator server 100 . The communication unit 220 transmits data about the user's whole body scanned by the 3D scanner 205 to the external system operator server 100 . Of course, the communication unit 220 may transmit user point cloud data in addition to the scan data. In addition, the communication unit 220 transmits user-specific information to the external system operator server 100 .

The communication unit 220 receives the 3D composite image from the external system operator server 100 . In addition, the communication unit 220 transmits various information to the system operator server 100 .

2 illustrates that the input unit 210 is included in the user scanner 200, but is not limited thereto. That is, the input unit 210 may be included in a separate device other than the user scanner.

The input unit 210 may select a plurality of clothes displayed on the display unit (not shown). That is, the display unit displays the clothes to be synthesized with the user's body scanned by the 3D scanner. To this end, the display unit may divide and display the clothing into a plurality of groups. That is, clothing may be divided into upper and lower garments, or may be displayed in various forms such as underwear and outerwear.

The input unit 210 selects clothes to be synthesized with the user's body from among a plurality of clothes displayed on the display unit. Of course, if necessary, the display unit may display detailed information about the clothes selected by the user.

The clothes (or clothes information) selected by the input unit 210 are transmitted to the external system operator server 100 through the communication unit 220 . In more detail, when at least two clothes are selected through the input unit 210, information on the selected clothes is transmitted to the system operator server 100 whenever clothes are selected, or when all clothes are selected, it is added to the selected clothes. information may be transmitted to the system operator server 100 . In this way, the user may transmit information about the selected clothes to the system operator server in various ways as needed.

3 is a block diagram illustrating the configuration of a system operator server according to an embodiment of the present invention. Hereinafter, the configuration of the system operator server according to an embodiment of the present invention will be described in detail with reference to FIG. 3 .

Referring to FIG. 3 , the system operator server 100 includes a clothing data generation unit 110 , a 3D composite image generation unit 120 , a control unit 130 , an input unit 140 , and a storage server 150 . Of course, other configurations other than the above-described configuration may be included in the system operator server proposed in the present invention.

The clothes data generator 110 may scan clothes with a scanner to generate clothes cloud data. The clothing data generator 110 may generate point cloud data or mesh data. Also, the clothing data generator 110 may generate point cloud data from the 3D image.

The storage server 150 stores information about the clothes scanned by the clothes data generating unit 110 . The storage server 150 stores clothing point cloud data, which is point cloud data for the scanned clothing. In addition, the storage server 150 stores various information.

That is, the storage server 150 stores the unique information on the fabric from which the clothes are manufactured, input through the input unit 140 . The specific information on the fabric will be described later.

The input unit 140 receives the unique information on the fabric constituting the clothing and the unique information on the clothing. Here, the unique information about the fabric includes the type of fiber, elasticity, thickness of fabric, weight per unit area of fabric, breathability of fabric, tensile strength, tear strength, abrasion strength, heat resistance, moisture mobility, stiffness, drape, and peeling. , bag properties, yarn strength, spinnability, yarn uniformity, bending and bending properties, and filling properties. In addition, the unique information of the clothing may include the type, use, wear part, and the like of the clothing. The input unit 140 receives various information about clothes. In addition, the input unit 140 may receive various information such as a price, a country of origin, and a manufacturing date for the clothes.

The controller 130 controls the operation of the system operator server 100 . Also, the control unit 130 may include a reference point setting unit 131 , a reference point control unit 132 , a point cloud data detailed control unit 133 , a direction calculation unit 134 , and a shape control unit 135 .

The reference point setting unit 131 sets a plurality of reference points among the clothing point group data. The reference point may be set at a preset interval, or may be set at a joint portion according to the shape of the clothing.

The reference point adjusting unit 132 calculates the distance between the reference points and moves the reference points. The reference point adjusting unit 132 calculates the distance between the reference points by combining the user point cloud data and the body point cloud data, and moves the reference point according to the calculated distance.

The point cloud data detailed control unit 133 adjusts the distance between each point cloud data from the reference point. The point cloud data detailed control unit 133 not only adjusts the distance between each point cloud data from the reference point, but also adjusts the distance between the point cloud data.

The point cloud data detailed control unit 133 includes a body analysis unit, a clothing analysis unit, a stress calculation unit, and an elasticity calculation unit. The body analyzer calculates the volume of the parts of the user's body. The body analyzer analyzes the volume by dividing the user's body into each part. For example, the body analyzer may analyze the volume by dividing the user's body into arms, chest, shoulders, and stomach.

The stress calculator calculates the stress applied to each part of the garment. The stress calculator calculates an acceptable space for the clothes, thereby calculating and storing the stress applied to each part of the clothes when the body is inserted into the clothes. The stress calculator may calculate a stress applied to each point cloud data. The elastic calculating unit calculates an extendable distance for each part of the garment in consideration of the fabric's unique information and the shape of the garment.

The direction calculating unit 134 calculates the movement direction of the clothing point cloud data in consideration of the stress applied to the clothing and the shape of the clothing when setting the movement direction of the clothing point cloud data. The movement direction of the clothing point cloud data may be determined by stress and elasticity.

The shape controller 135 extracts a plurality of inflection points in contact with the body from the clothing point cloud data, and calculates a shape change of the clothing point cloud data at the inflection points. For example, although stress is not applied to the clothing by the body in the portion in contact with the shoulder, the clothing is swayed down by gravity, and thus the clothing shape changes. The shape control unit 135 compares the length of the clothing with the length of the body. to calculate the shape change of the clothing.

As described above, since the data capacity of the clothing point cloud data is relatively smaller than that of the clothing scan data, it can be used much more efficiently than using the scan data. That is, the controller 130 may generate data on clothes having different shapes by using clothes point cloud data having a relatively small data capacity.

The 3D composite image generating unit 120 generates a 3D composite image by using user point cloud data, clothing point cloud data, and unique information about clothing according to a control command from the controller 130 . The 3D composite image generator 120 generates 3D composite data in which a user's body and clothes are synthesized, generates an outline from the 3D composite data, and combines colors to generate a 3D composite image.

As described above, the clothing point cloud data converted from the scanned data simply represents the shape of the clothing, and cannot express the color or material of the clothing. Accordingly, the 3D composite image generating unit 120 generates a 3D composite image by reflecting the scan data representing the color or material of the clothing in the clothing point cloud data. The reason for separating and 3D synthesizing the scan data is that the scan data has a larger capacity than the point cloud data, so if the fitting process is performed using the point cloud data with a smaller capacity, clothing can be fitted to the body at a faster speed.

The storage server 150 digitizes and stores unique information on fabrics and clothing. The storage server 150 of the present invention stores unique information about various fabrics, and generates a 3D composite image using the stored unique information.

That is, the existing 3D composite image could not represent the unique characteristics of clothing by simply synthesizing clothing on the body, but the present invention creates a 3D composite image by reflecting the unique characteristics of clothing and fabric to create the same shape or Even with colored clothing, a 3D composite image with a different feeling can be generated according to the unique characteristics of the clothing. That is, in the case of clothes having a relatively thin fabric, the weight of the clothes is light compared to clothes having a relatively thick fabric.

The generated 3D composite image can be rotated at a constant speed so that the user can know this feeling. When the 3D composite image is rotated at a constant speed, clothing that is relatively light in weight moves (shakes) more by the wind than clothing that is relatively heavy. As described above, by rotating the 3D composite image at a constant speed, it is possible to have a state that is relatively close to that of a real user wearing clothes.

Also, the 3D composite image generating unit 120 generates a 3D composite image by using elastic information of the fabric. That is, even if the clothes have the same shape, the 3D composite image generated according to the elasticity of the fabric is different. In other words, in the case of clothing with high elasticity (i.e., high elasticity), the garment adheres to all sides of the body, whereas in the case of clothing with low elasticity (i.e., weak elasticity), the garment is only worn on a part of the body. is closely attached to the body. More specifically, in the case of underwear, since clothing is manufactured from a fabric with good elasticity, when a 3D composite image is generated, all surfaces of the clothing are in close contact with the body.

On the other hand, in the case of an outerwear, since it is made of a fabric with relatively low elasticity, when a 3D composite image is generated, a portion of the clothing is in close contact with the body. As described above, the present invention creates a 3D composite image by using various characteristics of fabrics for manufacturing clothes.

4 shows an example in which clothes made of fabrics having different elasticity according to an embodiment of the present invention are synthesized on the body. That is, referring to FIG. 4 , the body is wearing two clothes. In particular, the clothes located inside show an example of synthesizing clothes made of a fabric with relatively high elasticity to the body, and the clothes positioned outside are An example of synthesizing clothing made of a fabric with relatively low elasticity is shown on the body.

As described above, it can be seen that the clothes made of the fabric with high elasticity are in close contact with the body, whereas the clothes made of the fabric with the low elasticity are in close contact with a part of the body.

Also, FIG. 5 shows an example of transforming the clothing point cloud data reflecting the body point cloud data. As shown in FIG. 5 , a 3D composite image is generated by transforming the clothing point cloud data CP according to the body point cloud data BP and unique information of clothes and fabrics. That is, it can be seen that the distance between the coordinates (point clouds) constituting the clothing point cloud data (CP) increases by reflecting the body point cloud data (BP) and the unique information of clothing and fabrics. 3D composite data is generated by synthesizing scan data with the generated 3D composite point cloud data.

6 is a flowchart illustrating a method for generating a 3D composite image according to an embodiment of the present invention.

Hereinafter, a method for generating a 3D composite image according to an embodiment of the present invention will be described in detail with reference to FIG. 6 .

The 3D composite image generation method according to this embodiment includes a user cloud data generation step (S100), a step of generating the clothing cloud data (S200), the step of adjusting the distance between the clothing cloud data (S300), and the 3D composite data generation and generating a 3D composite image (S500).

The user cloud data generation step S100 generates user point cloud data or user mesh data representing the appearance of the user's body, and the body cloud data may be formed of point cloud data or mesh data. The generating of the user point cloud data may include scanning the user's body using the user scanner 200 to generate the user point cloud data.

The user cloud data generation step ( S100 ) generates user point cloud data or user mesh data capable of generating the user's full body shape by using the user's full body scan data generated using the user scanner 200 .

The user cloud data generation step (S100) is based on the diagonal distance, which is the measured distance from the sensor located at the outer intersection, which is the eight intersections located on the outskirts of the four adjacent meshes, to the central intersection, which is the central intersection of the four meshes. Calculate the extrusion distance, which is the distance at which the intersection protrudes from the plane formed by the mesh.

In addition, in the user cloud data generation step ( S100 ), when the protrusion distance is equal to or greater than a predetermined threshold value, the measured body size is increased and outputted by a predetermined amount. In the user cloud data generation step ( S100 ), when the protrusion distance continuously occurs a predetermined number of times as the protrusion distance progresses in the horizontal and vertical directions, the measured body size is increased by a predetermined amount and output.

The user cloud data generation step (S100) stores the received user unique information, scan data, and user point cloud data, and transmits data about the user's whole body scanned by the 3D scanner 205 to the external system operator server 100 . .

The 3D composite image creation method may further include the step of receiving the user's unique information, and the user's unique information includes the user's name, age (age), height, weight, gender, hair color, hair shape, etc. may include

In the step of generating the clothing cloud data ( S200 ), clothing cloud data representing the appearance of the body of the clothing is generated, and the clothing cloud data may be formed of point cloud data or mesh data.

In the step of generating the clothing cloud data ( S200 ), scanning data for the clothing may be generated by scanning the clothing with a scanner, and the clothing cloud data may be generated using the generated scanning data. However, the present invention is not limited thereto, and the system operator server 100 may generate point cloud data for the clothing design using a device other than the 3D scanner. Accordingly, the system operator server 100 may generate clothing point cloud data from the 3D image file provided by the clothing manufacturer.

Hereinafter, data capable of generating the shape of clothing is defined as clothing cloud data, and the clothing cloud data may be formed of the aforementioned point cloud data as well as mesh data. However, when the cloud data consists of point cloud data, the capacity is small, so the data processing speed may be significantly increased compared to the mesh data or shape data.

In the step of generating the clothing cloud data ( S200 ), the clothing data generating unit 110 stores information on the scanned clothing, and stores clothing point cloud data, which is point cloud data for the scanned clothing.

In the step of adjusting the distance between the clothing cloud data (S300), the clothing cloud data is obtained by combining the body cloud data representing the user's body, the clothing cloud data representing the clothing, the unique information of the fabric constituting the clothing, and the unique information of the clothing. Adjust the distance between

Here, the unique information of the fabric includes the type of fiber, elasticity, thickness of fabric, weight per unit area of fabric, breathability of fabric, tensile strength, tear strength, abrasion strength, heat resistance, moisture mobility, stiffness, drape, peeling, bag properties, yarn strength, spinnability, yarn uniformity, flex and flex properties, and fillability. In addition, the unique information of the clothing includes the type, use,

a wear site, and the like.

Also, as shown in FIG. 7 , the step (S300) of adjusting the distance between the clothing cloud data includes the step of setting a reference point (S301), the step of adjusting the distance between the reference points (S302), and the detailed interval adjustment step (S303), setting the moving direction (S304), and calculating the shape change (S305).

In the step of setting the reference point ( S301 ), a plurality of reference points are set among the clothing point group data. The reference point may be set at a preset interval, or may be set at a joint portion according to the shape of the clothing.

In the step of adjusting the distance between the reference points ( S302 ), the distance between the reference points is calculated and the reference point is moved. In the step of adjusting the distance between the reference points ( S302 ), the distance between the reference points is calculated based on the combination of the user point cloud data and the body point cloud data, and the reference point is moved according to the calculated distance.

The detailed interval adjustment step S303 adjusts the distance between each point cloud data from the reference point. The detailed interval adjustment step S303 not only adjusts the distance between each point cloud data from the reference point, but also adjusts the distance between the point cloud data.

The detailed spacing adjustment step ( S303 ) may include calculating the volume of the parts of the user's body, calculating the stress applied to each part of the clothing, and calculating the extendable distance according to the characteristics of the fabric.

Calculating the volume of the parts of the user's body analyzes the volume by dividing the user's body into each part. For example, the volume can be analyzed by dividing the user's body into arms, chest, shoulders, and stomach.

The step of calculating the stress calculates the stress applied to each part of the garment. The step of calculating the stress calculates an acceptable space for the clothes, thereby calculating and storing the stress applied to each part of the clothes when the body is inserted into the clothes. In the calculating of the stress, the stress applied to each point cloud data may be calculated. In the step of calculating the extendable distance according to the characteristics of the fabric, the extendable distance for each part of the garment is calculated in consideration of the specific information of the fabric and the shape of the garment.

In the step of setting the movement direction ( S304 ), the movement direction of the clothing point cloud data is calculated in consideration of the stress applied to the clothing and the shape of the clothing in setting the movement direction of the clothing point cloud data. The movement direction of the clothing point cloud data may be determined by stress and elasticity.

In the calculating the shape change ( S305 ), a plurality of inflection points in contact with the body are extracted from the clothing point cloud data, and the shape change of the clothing point group data is calculated from the inflection points. For example, in the portion in contact with the shoulder, no stress is applied to the clothes by the body, but the clothes are swayed down by gravity, so a change occurs in the shape of the clothes. Comparing the length, calculate the shape change of the clothes.

In the step of generating 3D composite data ( S400 ), 3D composite data in which the user's body and clothes are synthesized is generated. In the step of generating the 3D composite image ( S500 ), a 3D composite image is generated by generating an outline from the 3D composite data and combining colors.

The generating of the 3D composite image may include synthesizing the first clothing point cloud data representing the appearance of the first clothing with the user's point cloud data, and synthesizing the first clothing point cloud data and then synthesizing the second clothing indicating the appearance of the second clothing. It may include synthesizing the point cloud data. Also, the size of the clothing corresponding to the second clothing point cloud data may be calculated according to the size of the clothing corresponding to the first clothing point cloud data and the thickness of the first clothing.

Also, in the generating of the 3D composite image, when at least two pieces of clothing corresponding to the clothing point cloud data to be synthesized with the user point cloud data are selected, the clothing point cloud data corresponding to the two pieces of clothing selected according to the unique information of the clothing are sequentially generated. It can be automatically synthesized into user point cloud data.

The 3D composite image generating method may further include rotating the 3D composite image at a set rotation speed after generating the 3D composite image. The movement of the clothes constituting the 3D composite image may be expressed according to the unique information of the clothes corresponding to the clothes point cloud data synthesized with the user's point cloud data.

The 3D composite image wearing clothing can be rotated by dragging the mouse or the touch screen of the user terminal. In addition, as described above, the clothes selected using the unique information of the clothes are automatically synthesized at the corresponding position in the user point cloud data.

In addition, the 3D composite image may be produced in various ways. For example, when clothes are selected and worn on the user's point cloud data, the first selected clothes are automatically combined and synthesized. Thereafter, when the second selection of clothing is worn, the first selected clothing is worn on the user point cloud data, and the selected secondary clothing is synthesized with the user point cloud data in consideration of the increased thickness. In this way, the 3D composite image may implement an image in the form of externally wearing the selected clothing on the previously selected clothing. By applying this method, the same effect as when wearing actual clothes can be realized. In addition, since the size of clothes worn outside the previously selected clothes is worn taking the thickness of the previously selected clothes into consideration, it is preferable that the clothes point group data can be changed in various forms as described above.

In other words, if the thickness of the previously selected clothing (clothes acting on the inside) is thin, the clothing is partially stretched due to elasticity, so it is necessary to synthesize clothing of one size larger. there is no However, since clothes made of low-elasticity fabrics do not stretch even if the previously selected clothes are thin, clothes having a larger size by one (or two or more steps) must be synthesized. As described above, the present invention creates a 3D image using the unique characteristics of clothes and fabrics.

Clothing may be worn on the user point cloud data by dragging, and if necessary, if the clothing is clicked by the mouse, the clothing may be automatically synthesized at a corresponding position in the user point cloud data using unique information of the clothing.

The method for generating a 3D composite image may include storing the generated 3D composite image. In the storing step, the 3D composite image may be stored in a separate storage space. That is, after the plurality of 3D composite images are stored in the storage space, if necessary, the 3D composite image may be retrieved or provided to a third party. In addition, the present invention allows a selected 3D composite image to be sent to a garment manufacturer so that the selected garment is requested to be made.

As described above, the 3D composite image synthesized by the user may be stored in a separate storage space, and if necessary, the 3D composite image stored in the storage space of another person may be retrieved with the permission of the other person. In other words, a composite image is generated by extracting clothing point cloud data from a clothing image registered by another person, and synthesizing the extracted clothing point cloud data with the user point cloud data. Of course, in this case, a composite image is generated by reflecting the clothing specific information.

As described above, even when the clothing point cloud data and the user point cloud data are the same, when the unique information of the clothing is different, different 3D composite images are generated. In addition, if necessary, the clothing point cloud data may be transformed based on the user point cloud data. That is, when the user desires to manufacture clothes in which the ready-to-wear is partially modified, the clothes point cloud data is transformed based on the user point cloud data. As described above, when the clothing point cloud data is partially modified, it is preferable to use the clothing point cloud data having a relatively small data capacity rather than using the scan data. To elaborate, a 3D composite image is generated by partially transforming the clothing point cloud data based on the user point cloud data.

Although the present invention has been described with reference to one embodiment shown in the drawings, this is merely exemplary, and it will be understood by those skilled in the art that various modifications and equivalent other embodiments are possible therefrom. .

100: system operator server 110: clothing data generation unit
140: input unit 120: 3D composite image generation unit
130: control unit 131: reference point setting unit
132: reference point control unit 133: data detailed control unit
134: direction calculation unit 135: shape control unit
140: input unit 150: storage server
200: user scanner 205: 3D scanner
210: input unit 215: storage unit
220: communication unit 225: control unit

Claims (10)

A method of generating a 3D composite image by combining clothing image data with a user's body image data, the method comprising:
adjusting a distance between the clothes cloud data by combining body cloud data representing the user's body, clothes cloud data representing clothes, unique information of fabrics constituting clothes, and unique information of the clothes; and
generating 3D composite data in which the user's body and clothing are synthesized;
and generating a 3D composite image by generating an outline from the 3D composite data and combining colors. According to claim 1,
generating user point cloud data representing the appearance of the user's body, and generating clothing point cloud data representing the outer shape of the clothing, wherein the body cloud data and the clothing cloud data are formed of point cloud data A method for generating a 3D composite image characterized. According to claim 1,
Generating user mesh data representing the appearance of the user's body, and generating clothing mesh data representing the outer shape of the clothing, wherein the body cloud data and the clothing cloud data are made of mesh data A method for generating a 3D composite image characterized. 3. The method of claim 2,
The generating of the user point cloud data comprises generating the user point cloud data by scanning the user's body. 5. The method of claim 4,
The generating of the clothing point cloud data comprises generating the clothing point cloud data by scanning the clothing. 3. The method of claim 2,
The generating of the clothing point cloud data comprises generating the clothing point cloud data from the input 3D image file of the clothing. 3. The method of claim 2,
The step of adjusting the distance between the clothing cloud data includes:
setting a plurality of reference points in the clothing point cloud data;
adjusting the distance between the reference points, and
and a detailed interval adjustment step of adjusting a distance between each point cloud data from the reference point. 8. The method of claim 7,
The detailed interval adjustment step is
calculating the volumes of parts of the user's body;
calculating the stress applied to each part of the garment;
3D composite image generation method comprising the step of calculating an expandable distance according to the characteristics of the fabric. 8. The method of claim 7,
The adjusting the distance between the clothing cloud data includes setting a movement direction of the clothing point cloud data. 8. The method of claim 7,
The adjusting the distance between the clothing cloud data comprises extracting a plurality of inflection points in contact with the body from the clothing point cloud data and calculating a shape change of the clothing point cloud data at the inflection points.

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