A digital fabric management method and system for clothing design

Abstract

The present invention is applicable to the technical field of fabric management, and provides a digital fabric management method and system for clothing design, including the following steps: collecting fabric images and texture information through a scanner, entering fabric data into the Style3D system, and establishing a fabric database; importing clothing patterns and pattern parameters based on Style3D, initializing the correspondence between fabrics and patterns, and ensuring that fabrics can be correctly mapped to the patterns; combining fabrics with clothing patterns based on a flexible simulation algorithm to generate 3D samples, and rendering the 3D samples realistically; and retrieving different types of 3D samples for VR display according to the layout and style of a VR fabric exhibition hall. The present invention reduces the management cost of physical samples by digitally collecting and storing fabric images and texture information. The Style3D system and VR technology are used to generate realistic 3D samples, and the fabrics are quickly combined with clothing patterns based on a flexible simulation algorithm to generate 3D samples.

Description

Technical Field

[0001] The present invention relates to the technical field of fabric management, and specifically relates to a digital fabric management method and system for clothing design. Background Art

[0002] In the process of clothing design and production, the selection and management of fabrics have always been crucial links. Traditionally, the selection of fabrics relies on the display of physical samples. Designers and purchasers need to touch and observe the texture, color, and texture of the fabrics in person to determine whether they are suitable for specific design requirements. However, this method has many inconveniences. Physical fabric samples require a large amount of storage space, and as the types of fabrics increase, the management cost also rises. Physical displays are limited by space and time and cannot fully display all the details and characteristics of the fabrics, especially in remote collaboration and online sales scenarios. When designers apply fabrics to clothing designs, they usually need to go through multiple trials and errors and adjustments, which not only takes time and effort but also may affect the innovation of the design. Therefore, it is necessary to provide a digital fabric management method and system for clothing design to solve the above problems. Summary of the Invention

[0003] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide a digital fabric management method and system for clothing design to solve the problems in the above background art.

[0004] The present invention is implemented as follows. A digital fabric management method for clothing design, the method includes the following steps:

[0005] Collect fabric images and texture information through a scanner, enter the fabric data into the Style3D system, and establish a fabric database. The fabric data includes material, color, texture, pattern, and physical properties;

[0006] Based on Style3D, import the clothing pattern and pattern parameters, and initialize the correspondence between the fabric and the pattern to ensure that the fabric can be correctly mapped to the pattern;

[0007] Combine the fabric with the clothing pattern based on a flexible simulation algorithm to generate a 3D sample garment, and perform photorealistic rendering on the 3D sample garment based on the rendering engine of Style3D;

[0008] Retrieve different types of 3D sample garments according to the layout and style of the VR fabric exhibition hall for VR display;

[0009] Real-time monitor the behavioral trajectory data of users in the VR fabric exhibition hall. The behavioral trajectory data includes browsing paths, interaction data, stay time, and click times;

[0010] Determine the fabrics of interest to users based on the behavioral trajectory data, and send recommended fabric information to users.

[0011] As a further solution of the present invention: the step of combining the fabric with the clothing pattern based on the flexible simulation algorithm to generate a 3D sample garment specifically includes:

[0012] Physically model the fabric according to the physical properties of the fabric data, and the physical properties include elastic modulus, Poisson's ratio and thickness;

[0013] Establish a spatial mapping relationship between the fabric and the clothing pattern. When mapping, based on the nearest neighbor search algorithm, determine the points on the corresponding fabric for each pattern point;

[0014] Apply the particle spring system to simulate the natural draping and wrinkling effects of the fabric on the pattern;

[0015] Perform iterative calculations until the system reaches a static equilibrium state to form the final 3D sample garment model.

[0016] As a further solution of the present invention: the step of performing realistic rendering on the 3D sample garment specifically includes:

[0017] Based on the UV mapping technology, map the fabric image and texture information onto the 3D sample garment model to ensure that the texture coordinates correspond one-to-one with the surface of the 3D model;

[0018] According to the light source position, color and intensity in the virtual environment, calculate the light distribution on the surface of the 3D sample garment, and apply the Phong lighting model to calculate the reflection, refraction and specular highlights;

[0019] Apply anti-aliasing, depth of field, and ambient occlusion technologies to enhance the realism and detail performance of the 3D sample garment.

[0020] As a further solution of the present invention: the step of real-time monitoring of the user's behavior trajectory data in the VR fabric exhibition hall specifically includes:

[0021] Based on the sensors built into the VR headset, record the user's movement path in the exhibition hall in real time to determine the browsing path;

[0022] Capture the user's interaction behaviors with the 3D sample garment. The interaction behaviors include clicking, dragging, and zooming in and out, and record the interaction type and timestamp to obtain interaction data;

[0023] Statistically analyze the user's stay time in front of different 3D sample garments and the number of clicks on different 3D sample garments.

[0024] As a further solution of the present invention: the step of determining the fabrics of interest to the user based on the behavior trajectory data and sending recommended fabric information to the user specifically includes:

[0025] Determine the user's interest in each 3D sample garment based on interaction data, dwell time, and click count;

[0026] Retrieve the fabric corresponding to each 3D sample garment, calculate the comprehensive interest score of the user for each fabric according to the interest level, and determine the fabrics that the user is interested in;

[0027] Generate a personalized fabric recommendation list based on the fabrics that the user is interested in, and send the recommended fabric information to the user, where the recommended fabric information includes pictures, names, and brief descriptions.

[0028] Another object of the present invention is to provide a digital fabric management system for clothing design, and the system includes:

[0029] A fabric data determination module, which is used to collect fabric images and texture information through a scanner, input the fabric data into the Style3D system, and establish a fabric database, where the fabric data includes material, color, texture, pattern, and physical properties;

[0030] A pattern parameter determination module, which is used to import the clothing pattern and pattern parameters based on Style3D, initialize the corresponding relationship between the fabric and the pattern, and ensure that the fabric can be correctly mapped to the pattern;

[0031] A fabric flexible simulation module, which is used to combine the fabric with the clothing pattern based on a flexible simulation algorithm to generate a 3D sample garment, and perform realistic rendering on the 3D sample garment based on the rendering engine of Style3D;

[0032] A fabric VR display module, which is used to retrieve different types of 3D sample garments for VR display according to the layout and style of the VR fabric exhibition hall;

[0033] A behavior trajectory collection module, which is used to monitor the behavior trajectory data of the user in the VR fabric exhibition hall in real time, and the behavior trajectory data includes browsing path, interaction data, dwell time, and click count;

[0034] A fabric recommendation information module, which is used to determine the fabrics that the user is interested in based on the behavior trajectory data and send the recommended fabric information to the user.

[0035] As a further solution of the present invention: the fabric flexible simulation module includes:

[0036] A fabric physical modeling unit, which is used to perform physical modeling on the fabric according to the physical properties of the fabric data, and the physical properties include elastic modulus, Poisson's ratio, and thickness;

[0037] A fabric pattern mapping unit, which is used to establish a spatial mapping relationship between the fabric and the clothing pattern. When mapping, based on the nearest neighbor search algorithm, the points on the corresponding fabric are determined based on each pattern point;

[0038] A draping fold simulation unit for simulating the natural draping and folding effects of fabrics on patterns using a particle spring system;

[0039] An iterative calculation unit for performing iterative calculations until the system reaches a static equilibrium state to form a final 3D sample garment model.

[0040] As a further solution of the present invention: the fabric flexible simulation module further includes:

[0041] An image texture mapping unit for mapping fabric images and texture information onto the 3D sample garment model based on UV mapping technology to ensure a one-to-one correspondence between texture coordinates and the 3D model surface;

[0042] A light effect simulation unit for calculating the light distribution on the surface of the 3D sample garment according to the position, color, and intensity of the light source in the virtual environment, and applying the Phong lighting model to calculate reflection, refraction, and specular effects;

[0043] A post-processing unit for enhancing the realism and detail performance of the 3D sample garment using anti-aliasing, depth of field, and ambient occlusion techniques.

[0044] As a further solution of the present invention: the behavior trajectory acquisition module includes:

[0045] A browsing path determination unit for real-time recording of the user's movement path in the exhibition hall based on the sensors built into the VR headset to determine the browsing path;

[0046] An interaction data determination unit for capturing the user's interaction behaviors with the 3D sample garment, where the interaction behaviors include clicking, dragging, and zooming in and out, and recording the interaction type and timestamp to obtain interaction data;

[0047] A stay and click count unit for counting the user's stay time in front of different 3D sample garments and the number of clicks on different 3D sample garments.

[0048] As a further solution of the present invention: the fabric recommendation information module includes:

[0049] An interest degree calculation unit for determining the user's interest degree in each 3D sample garment based on interaction data, stay time, and click count;

[0050] An interested fabric determination unit for retrieving the fabrics corresponding to each 3D sample garment, calculating the comprehensive interest degree score of the user for each fabric according to the interest degree, and determining the user's interested fabrics;

[0051] A recommended fabric information unit for generating a personalized fabric recommendation list according to the user's interested fabrics and sending the recommended fabric information to the user, where the recommended fabric information includes pictures, names, and brief descriptions.

[0052] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0053] By digitally collecting and storing fabric images and texture information, the present invention establishes a fabric database, reducing the management cost of physical samples. Using the Style3D system and VR technology, it generates realistic 3D sample clothes and displays them in a virtual environment, breaking through the limitations of physical display and providing a more diverse way to display fabrics and clothes. Based on a flexible simulation algorithm, it quickly combines fabrics with clothing patterns to generate 3D sample clothes, greatly shortening the design cycle and improving design efficiency. Through the VR fabric exhibition hall, users can freely browse and select fabrics in a virtual environment, obtaining a more intuitive and real fabric experience. At the same time, by combining big data analysis technology, it can monitor the user behavior trajectory in real time and accurately push fabric information that the user is interested in, enhancing the user experience and purchase intention. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a flowchart of a digital fabric management method for clothing design.

[0055] Figure 2 It is a flowchart of generating 3D sample clothes in a digital fabric management method for clothing design.

[0056] Figure 3 It is a flowchart of rendering 3D sample clothes in a digital fabric management method for clothing design.

[0057] Figure 4 It is a flowchart of monitoring the behavior trajectory data of users in a digital fabric management method for clothing design.

[0058] Figure 5 It is a flowchart of sending recommended fabric information to users in a digital fabric management method for clothing design.

[0059] Figure 6 It is a schematic structural diagram of a digital fabric management system for clothing design. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0060] In order to make the objectives, technical solutions and advantages of the present invention clearer, the following further details the present invention in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0061] The following details the specific implementation of the present invention in conjunction with specific embodiments.

[0062] As Figure 1 shown, the embodiments of the present invention provide a digital fabric management method for clothing design, and the method includes the following steps:

[0063] S100. Collect fabric images and texture information through a scanner, input the fabric data into the Style3D system, and establish a fabric database. The fabric data includes material, color, texture, pattern, and physical properties.

[0064] S200. Import the clothing pattern and pattern parameters based on Style3D, initialize the correspondence between the fabric and the pattern to ensure that the fabric can be correctly mapped onto the pattern.

[0065] S300. Combine the fabric with the clothing pattern based on a flexible simulation algorithm to generate a 3D sample garment, and perform photorealistic rendering on the 3D sample garment based on the rendering engine of Style3D.

[0066] S400. Retrieve different types of 3D sample garments according to the layout and style of the VR fabric exhibition hall for VR display.

[0067] S500. Real-time monitor the behavioral trajectory data of users in the VR fabric exhibition hall. The behavioral trajectory data includes browsing path, interaction data, stay time, and click times.

[0068] S600. Determine the fabrics of interest to the user based on the behavioral trajectory data, and send recommended fabric information to the user.

[0069] It should be noted that physical fabric samples require a large amount of storage space, and with the increase in the types of fabrics, the management cost also rises. Physical display is limited by space and time and cannot comprehensively display all the details and characteristics of the fabrics, especially in scenarios of remote collaboration and online sales. The embodiments of the present invention aim to solve the above problems.

[0070] In the embodiments of the present invention, relying on the Style3D system, first, it is necessary to use a high-precision scanner to collect fabric images and texture information, input the fabric data into the Style3D system, and establish a fabric database. The fabric data includes material, color, texture, pattern, and physical properties. It is also necessary to import various clothing patterns and pattern parameters in Style3D, initialize the correspondence between the fabric and the pattern, and ensure that the fabric can be correctly mapped onto the pattern. Then, it is necessary to introduce a fabric flexibility simulation algorithm, such as the finite element method (FEM) or the mass-spring model, to simulate the flexible deformation of the fabric in three-dimensional space. Using the intelligent optimization function of Style3D, according to the physical properties of the fabric and the geometric characteristics of the pattern, automatically adjust the matching relationship between the fabric and the pattern to ensure that the fabric can naturally fit the pattern during the simulation process, generate a 3D sample garment, and based on the rendering engine of Style3D, perform realistic rendering on the 3D sample garment, including effects such as lighting, shadows, and textures. In the virtual environment of Style3D, display all-round views of the 3D sample garment, including the front, side, back, etc., and provide intelligent interaction functions, such as rotation, zoom, drag, etc., to facilitate users to view the details of the 3D sample garment. In the embodiments of the present invention, VR fabric exhibition halls of various styles will also be designed, and different types of 3D sample garments will be retrieved for VR display according to the layout and style of the VR fabric exhibition hall. Users can access the VR fabric exhibition hall through a VR headset. The embodiments of the present invention will real-time monitor the behavioral trajectory data of users in the VR fabric exhibition hall, and determine the fabrics of interest to users according to the behavioral trajectory data, and send recommended fabric information to users, improving the user experience and purchase intention.

[0071] As Figure 2 shown, as a preferred embodiment of the present invention, the steps of combining the fabric with the clothing pattern based on the flexible simulation algorithm to generate a 3D sample garment specifically include:

[0072] S301, perform physical modeling on the fabric according to the physical properties of the fabric data;

[0073] S302, establish a spatial mapping relationship between the fabric and the clothing pattern. When mapping, based on each pattern point, determine the corresponding point on the fabric through the nearest neighbor search algorithm;

[0074] S303, apply the mass-spring system to simulate the natural draping and wrinkling effects of the fabric on the pattern. The relationship existing in the corresponding process is:

[0075] ;

[0076] wherein, represents the spring force, represents the spring stiffness coefficient, represents the spring elongation, represents the damping coefficient, represents the velocity;

[0077] S304, perform iterative calculations until the system reaches a static equilibrium state to form the final 3D garment model.

[0078] In the embodiments of the present invention, first, physical modeling of the fabric is performed according to the physical properties of the fabric data, and the physical properties include elastic modulus, Poisson's ratio, and thickness; import the geometric data (such as contour lines, seam lines) of the garment pattern (such as garment pieces, sleeves, etc.) into Style3D to establish a spatial mapping relationship between the fabric and the garment pattern. When mapping, for each pattern point, determine the corresponding point on the fabric, which is achieved through the nearest neighbor search algorithm. Here, the particle spring system is applied to simulate the natural draping and wrinkling effects of the fabric on the pattern; perform iterative calculations until the system reaches a static equilibrium state to form the final 3D garment model.

[0079] Specifically, the steps for performing physical modeling of the fabric according to the physical properties of the fabric data are as follows:

[0080] Obtain the physical properties of the fabric, and the physical properties of the fabric include elastic modulus, Poisson's ratio, and thickness;

[0081] Based on the elastic modulus and Poisson's ratio, use the elastic mechanics calculation formula under plane stress conditions to calculate the elastic stiffness parameters describing the main directions;

[0082] Based on Poisson's ratio, use the elastic mechanics calculation formula under plane stress conditions to calculate the coupling stiffness parameters describing different directions;

[0083] Construct a stiffness matrix based on the elastic stiffness parameters describing the main directions, the coupling stiffness parameters describing different directions, and the thickness. The construction method is as follows:

[0084] Take the elastic stiffness parameters describing the main directions as the first parameter in the first row of the stiffness matrix, take the coupling stiffness parameters describing different directions as the second parameter in the first row of the stiffness matrix, and take zero as the third parameter in the first row of the stiffness matrix;

[0085] Take the coupling stiffness parameters describing different directions as the first parameter in the second row of the stiffness matrix, take the elastic stiffness parameters describing the main directions as the second parameter in the second row of the stiffness matrix, and take zero as the third parameter in the second row of the stiffness matrix;

[0086] Take zero as the first and second parameters in the third row of the stiffness matrix respectively, and take the thickness as the third parameter in the third row of the stiffness matrix;

[0087] Output the constructed stiffness matrix and use the stiffness matrix to implement physical modeling.

[0088] Furthermore, the present invention calculates the stiffness matrix step by step from the input fabric physical properties to clarify the physical meaning and the logic of the calculation method. At the same time, the elastic modulus, Poisson's ratio, and thickness jointly determine the properties of the fabric, and the stiffness matrix ultimately reflects the performance of these properties in mechanical behavior.

[0089] Specifically, a spatial mapping relationship between the fabric and the garment pattern is established. When mapping, through the nearest neighbor search algorithm, based on each pattern point, the corresponding point on the fabric is determined. The specific steps are as follows:

[0090] Obtain the set of garment pattern points and the set of fabric points, where the set of garment pattern points and the set of fabric points contain the spatial coordinates of all garment pattern points and the spatial coordinates of fabric points;

[0091] Derive the spatial coordinates of the fabric points from the set of fabric points, and use the spatial coordinates of all fabric points as input to construct a KD tree;

[0092] For each garment pattern point, use the spatial coordinates of the current garment pattern point as the input to the KD tree;

[0093] Based on the KD tree, find the fabric point closest to the current garment pattern point among all fabric points through Euclidean distance calculation and hierarchical query, and then output the search result;

[0094] In the obtained search results, each garment pattern point corresponds to an index of a fabric point;

[0095] After traversing all garment pattern points and completing the nearest neighbor search for all garment pattern points, generate a result list; wherein, the result list records the fabric point index mapped by each garment pattern point in the order of the garment pattern points;

[0096] Output the result list to represent the spatial mapping relationship between the garment pattern points and the fabric points.

[0097] Furthermore, the present invention uses a KD tree to achieve fast nearest neighbor search, and when the KD tree establishes a spatial index, it utilizes the distribution characteristics of the point cloud data, reducing repeated and redundant distance calculations, thereby further improving the search efficiency.

[0098] As Figure 3 shown, as a preferred embodiment of the present invention, the steps of performing photorealistic rendering on the 3D sample garment specifically include:

[0099] S305, Map the fabric image and texture information onto the 3D sample garment model based on the UV mapping technology to ensure that the texture coordinates correspond one-to-one with the surface of the 3D model;

[0100] S306. Calculate the light distribution on the surface of the 3D garment sample according to the light source position, color, and intensity in the virtual environment, and apply the Phong lighting model to calculate the reflection, refraction, and specular effects.

[0101] S307. Apply anti-aliasing, depth of field, and ambient occlusion techniques to enhance the realism and detail performance of the 3D garment sample.

[0102] Specifically, to calculate the light distribution on the surface of the 3D garment sample according to the light source position, color, and intensity in the virtual environment, and apply the Phong lighting model to calculate the reflection, refraction, and specular effects, the specific steps are as follows:

[0103] Obtain the diffuse coefficient, specular coefficient, specular reflection coefficient, the position of the light source point, the position of the target point, the line-of-sight direction vector, the refractive index, and the RGB values from the preset parameters in the virtual environment.

[0104] Traverse each light source in the virtual environment and perform the following processing:

[0105] If the light source is a point light source, calculate the direction vector from the target point to the light source point based on the position of the light source point and the position of the target point, and then normalize the direction vector to obtain the direction vector of the light ray.

[0106] If the light source is a directional light source, directly determine the direction vector of the light ray.

[0107] Calculate the dot product of the surface normal vector of the 3D garment sample and the direction vector of the light ray to obtain the diffuse dot product value.

[0108] If the diffuse dot product value is greater than zero, calculate the diffuse intensity through the Phong lighting model based on the diffuse coefficient, RGB values, and the diffuse dot product value.

[0109] If the diffuse dot product value is less than zero, no calculation is performed.

[0110] Based on the direction vector of the light ray and the surface normal vector of the 3D garment sample, obtain the direction vector of the reflected light ray through the law of reflection.

[0111] Calculate the specular dot product value based on the dot product of the direction vector of the reflected light ray and the line-of-sight direction vector.

[0112] If the specular dot product value is greater than zero, obtain the specular reflection intensity through the Phong lighting model based on the specular reflection coefficient, specular coefficient, and the specular dot product value.

[0113] If the specular dot product value is less than zero, no calculation is performed.

[0114] Based on the direction vector of the light ray and the refractive index, calculate the direction vector of the refracted light ray through Snell's law.

[0115] Perform a dot product calculation on the line-of-sight direction vector and the direction of the refracted light to obtain the refraction dot product value;

[0116] Based on the refraction dot product value and the RGB values, obtain the refraction intensity through the Phong lighting model;

[0117] Add the diffuse reflection intensity, specular reflection intensity, and refraction intensity of the current light source to obtain the total illumination intensity;

[0118] Accumulate the total illumination intensities of all light sources to obtain the comprehensive illumination intensity.

[0119] In the embodiments of the present invention, the fabric image and texture information will be mapped onto the 3D sample clothing model to maintain the continuity and accuracy of the texture. Here, the UV mapping technology is used to ensure that the texture coordinates correspond one-to-one with the surface of the 3D model. Then, according to the position, color, and intensity of the light source in the virtual environment, the illumination distribution on the surface of the 3D sample clothing will be calculated, and the Phong lighting model will be applied to calculate the reflection, refraction, and specular highlight effects. The Phong model formula: I = Ia + Id(N·L) + Is(R·V)^n, where I is the final color, Ia is the ambient light, Id is the diffuse light, Is is the specular light, N is the normal, L is the light source direction, R is the reflection direction, V is the line-of-sight direction, and n is the specular highlight exponent. Finally, anti-aliasing, depth of field, and ambient occlusion (AO) technologies are applied to enhance the realism and detail performance of the 3D sample clothing.

[0120] As Figure 4 shown, as a preferred embodiment of the present invention, the step of real-time monitoring of the user's behavior trajectory data in the VR fabric exhibition hall specifically includes:

[0121] S501, based on the sensors built into the VR headset, record the user's movement path in the exhibition hall in real time to determine the browsing path;

[0122] S502, capture the user's interaction behaviors with the 3D sample clothing. The interaction behaviors include clicking, dragging, and zooming in and out, and record the interaction type and timestamp to obtain the interaction data;

[0123] S503, count the user's stay time in front of different 3D sample clothing and the number of clicks on different 3D sample clothing.

[0124] In an embodiment of the present invention, the VR headset is built with sensors that can record the user's movement path in the exhibition hall in real time (such as position coordinates and direction angles), and then determine the browsing path. Then, it will capture the user's interaction behaviors with the 3D sample clothes. The interaction behaviors include clicking, dragging, and zooming in and out. The interaction type and timestamp are recorded to obtain interaction data. Then, it will count the user's stay time in front of different 3D sample clothes and the number of clicks on different 3D sample clothes. Finally, the collected behavioral trajectory data is stored in a server or a local database for subsequent analysis.

[0125] As Figure 5 shown, as a preferred embodiment of the present invention, the step of determining the user's interested fabrics based on the behavioral trajectory data and sending the recommended fabric information to the user specifically includes:

[0126] S601, determining the user's interest level in each 3D sample clothes based on the interaction data, stay time, and number of clicks;

[0127] S602, retrieving the fabrics corresponding to each 3D sample clothes, calculating the comprehensive interest level score of the user for each fabric according to the interest level, and determining the user's interested fabrics;

[0128] S603, generating a personalized fabric recommendation list according to the user's interested fabrics, and sending the recommended fabric information to the user. The recommended fabric information includes pictures, names, and brief descriptions.

[0129] Specifically, the steps of determining the user's interest level in each 3D sample clothes based on the interaction data, stay time, and number of clicks are as follows:

[0130] Respectively obtain the weight coefficients of the interaction data, the weight coefficients of the stay time, and the weight coefficients of the number of clicks;

[0131] Obtain the maximum values of the interaction data, the stay time, and the number of clicks;

[0132] Divide the interaction data by the maximum value of the interaction data to obtain the normalized interaction data;

[0133] Divide the stay time by the maximum value of the stay time to obtain the normalized stay time;

[0134] Divide the number of clicks by the maximum value of the number of clicks to obtain the normalized number of clicks;

[0135] Multiply the normalized interaction data, the normalized stay time, and the normalized number of clicks by the weight coefficients of the interaction data, the weight coefficients of the stay time, and the weight coefficients of the number of clicks respectively to obtain the weighted interaction data, the weighted stay time, and the weighted number of clicks;

[0136] Add the weighted interaction data, weighted dwell time, and weighted number of clicks to obtain the user's interest level in each 3D clothing sample.

[0137] Furthermore, in this step, normalization is performed to ensure the comparability of data at different scales, weight assignment is used to reflect the importance of each behavioral feature, and weighted summation is used to make the result more intuitively meaningful. Through this process, an accurate quantitative basis is provided for user interest modeling.

[0138] In the embodiments of the present invention, the collected behavioral trajectory data will be cleaned and denoised to ensure the accuracy and integrity of the data, and interest weights will be assigned to the interaction data, dwell time, and number of clicks. In this way, the user's interest level in each 3D clothing sample can be determined based on the interaction data, dwell time, number of clicks, and their weights. Then, the fabric corresponding to each 3D clothing sample is retrieved, and the comprehensive interest level score of the user for each type of fabric is calculated according to the corresponding interest level, the user's interested fabrics are determined, and a personalized fabric recommendation list is generated. The recommended fabric information, including pictures, names, and brief descriptions, is sent to the user. Links or buttons can also be provided to facilitate the user to directly view more details or make a purchase. Finally, it also supports collecting user feedback on the recommended information (such as click-through rate, purchase rate) for continuously optimizing the recommendation algorithm and improving the recommendation accuracy.

[0139] As Figure 6 shown, the embodiments of the present invention also provide a digital fabric management system for clothing design, and the system includes:

[0140] A fabric data determination module 100, which is used to collect fabric images and texture information through a scanner, input the fabric data into the Style3D system, and establish a fabric database. The fabric data includes material, color, texture, pattern, and physical properties;

[0141] A pattern parameter determination module 200, which is used to import the clothing pattern and pattern parameters based on Style3D, initialize the correspondence between the fabric and the pattern, and ensure that the fabric can be correctly mapped to the pattern;

[0142] A fabric flexible simulation module 300, which is used to combine the fabric with the clothing pattern based on a flexible simulation algorithm to generate a 3D clothing sample, and perform realistic rendering on the 3D clothing sample based on the rendering engine of Style3D;

[0143] A fabric VR display module 400, which is used to retrieve different types of 3D clothing samples for VR display according to the layout and style of the VR fabric exhibition hall;

[0144] The behavior trajectory acquisition module 500 is used to monitor the behavior trajectory data of the user in the VR fabric exhibition hall in real time. The behavior trajectory data includes the browsing path, interaction data, stay time, and click times.

[0145] The fabric recommendation information module 600 is used to determine the fabrics of interest to the user based on the behavior trajectory data and send the recommended fabric information to the user.

[0146] As a preferred embodiment of the present invention, the fabric flexible simulation module 300 includes:

[0147] The fabric physical modeling unit is used to perform physical modeling on the fabric according to the physical properties of the fabric data. The physical properties include elastic modulus, Poisson's ratio, and thickness.

[0148] The fabric pattern mapping unit is used to establish a spatial mapping relationship between the fabric and the clothing pattern. When mapping, for each pattern point, the corresponding point on the fabric is determined through the nearest neighbor search algorithm.

[0149] The draping and wrinkling simulation unit is used to simulate the natural draping and wrinkling effects of the fabric on the pattern by applying the particle spring system.

[0150] The iterative calculation unit is used to perform iterative calculations until the system reaches a static equilibrium state to form the final 3D sample clothing model.

[0151] As a preferred embodiment of the present invention, the fabric flexible simulation module 300 further includes:

[0152] The image texture mapping unit is used to map the fabric image and texture information onto the 3D sample clothing model based on the UV mapping technology to ensure that the texture coordinates correspond one-to-one with the surface of the 3D model.

[0153] The light effect simulation unit is used to calculate the light distribution on the surface of the 3D sample clothing according to the light source position, color, and intensity in the virtual environment, and apply the Phong lighting model to calculate the reflection, refraction, and specular highlight effects.

[0154] The post-processing unit is used to enhance the realism and detail performance of the 3D sample clothing by applying anti-aliasing, depth of field, and ambient occlusion technologies.

[0155] As a preferred embodiment of the present invention, the behavior trajectory acquisition module 500 includes:

[0156] The browsing path determination unit is used to record the movement path of the user in the exhibition hall in real time based on the sensors built into the VR headset and determine the browsing path.

[0157] An interaction data determination unit, configured to capture a user's interaction behavior with a 3D virtual garment, where the interaction behavior includes clicking, dragging, and zooming in and out, and record the interaction type and timestamp to obtain interaction data;

[0158] A stay and click count unit, configured to count the stay time of the user in front of different 3D virtual garments and the click times on different 3D virtual garments.

[0159] As a preferred embodiment of the present invention, the fabric recommendation information module 600 includes:

[0160] An interest degree calculation unit, configured to determine the interest degree of the user in each 3D virtual garment based on the interaction data, stay time, and click times;

[0161] An interested fabric determination unit, configured to retrieve the fabric corresponding to each 3D virtual garment, calculate the comprehensive interest degree score of the user for each fabric according to the interest degree, and determine the interested fabric of the user;

[0162] A recommended fabric information unit, configured to generate a personalized fabric recommendation list according to the interested fabric of the user, and send the recommended fabric information to the user, where the recommended fabric information includes pictures, names, and brief descriptions.

[0163] The above only describes the preferred embodiments of the present invention in detail and is not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0164] It should be understood that although the steps in the flowcharts of the embodiments of the present invention are shown in sequence according to the arrows, these steps do not necessarily have to be executed in the order indicated by the arrows. Unless otherwise clearly stated in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in each embodiment may include multiple sub-steps or multiple stages. These sub-steps or stages do not necessarily have to be executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages does not necessarily have to be sequential, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0165] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0166] After considering the specification and the disclosure of the embodiments, those skilled in the art will readily conceive of other embodiments of the present disclosure. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include known common knowledge or conventional technical means in the technical field not disclosed in the present disclosure. The specification and the embodiments are only regarded as exemplary, and the true scope and spirit of the present disclosure are pointed out by the claims.

Claims

1. A digital fabric management method for clothing design, characterized in that, The method comprises the following steps: Collect fabric images and texture information through a scanner, enter fabric data into the Style3D system, and establish a fabric database. The fabric data includes material, color, texture, pattern and physical properties; Import clothing patterns and pattern parameters based on Style3D, initialize the correspondence between fabrics and patterns, and ensure that fabrics can be correctly mapped to the patterns; Combine fabrics and clothing patterns based on flexible simulation algorithms to generate 3D samples, and render the 3D samples realistically based on the Style3D rendering engine; According to the layout and style of the VR fabric showroom, different types of 3D samples are selected for VR display; Real-time monitoring of user behavior trajectory data in the VR fabric exhibition hall, including browsing path, interaction data, dwell time and number of clicks; Determine the user's interested fabrics based on the behavior trajectory data and send recommended fabric information to the user; The step of combining fabrics with clothing patterns based on a flexible simulation algorithm to generate 3D clothing samples specifically includes: Physically modeling the fabric according to the physical properties of the fabric data, wherein the physical properties include elastic modulus, Poisson's ratio and thickness; Establish a spatial mapping relationship between fabric and garment pattern. During mapping, the nearest neighbor search algorithm is used to determine the corresponding point on the fabric based on each pattern point. The mass spring system is used to simulate the natural drape and wrinkle effects of fabrics on the pattern. The corresponding relationship is: ； Among them, represents the spring force, represents the spring stiffness coefficient, represents the spring elongation, represents the damping coefficient, represents the velocity; Perform iterative calculations until the system reaches a static equilibrium state to form the final 3D garment model; Among them, physical modeling of fabrics is carried out according to the physical properties of fabric data. The specific steps are as follows: Obtain the physical properties of the fabric, including elastic modulus, Poisson's ratio and thickness; Based on the elastic modulus and Poisson's ratio, the elastic stiffness parameters describing the main direction are calculated using the elastic mechanics calculation formula under plane stress conditions. Based on Poisson's ratio, the elastic mechanics calculation formula under plane stress conditions is used to calculate the coupling stiffness parameters describing different directions; The stiffness matrix is ​​constructed based on the elastic stiffness parameters describing the main direction, the coupling stiffness parameters describing different directions, and the thickness. The construction method is as follows: The elastic stiffness parameter describing the main direction is used as the first parameter of the first row in the stiffness matrix, the coupling stiffness parameter describing different directions is used as the second parameter of the first row in the stiffness matrix, and zero is used as the third parameter of the first row in the stiffness matrix; The coupling stiffness parameter describing different directions is used as the first parameter of the second row in the stiffness matrix, the elastic stiffness parameter describing the main direction is used as the second parameter of the second row in the stiffness matrix, and zero is used as the third parameter of the second row in the stiffness matrix; Use zero as the first and second parameters of the third row in the stiffness matrix, and use thickness as the third parameter of the third row in the stiffness matrix; Output the constructed stiffness matrix and use the stiffness matrix to realize physical modeling; Among them, a spatial mapping relationship between fabric and clothing pattern is established. During the mapping, the nearest neighbor search algorithm is used to determine the corresponding point on the fabric based on each pattern point. The specific steps are as follows: Obtain the set of garment pattern points and the set of fabric points, where the set of garment pattern points and the set of fabric points contain the spatial coordinates of all garment pattern points and the spatial coordinates of fabric points; Derive the spatial coordinates of fabric points from the set of fabric points, and use the spatial coordinates of all fabric points as input to construct a KD tree; For each garment pattern point, use the spatial coordinates of the current garment pattern point as the input to the KD tree; Based on the KD tree, find the fabric point closest to the current garment pattern point among all fabric points through Euclidean distance calculation and hierarchical query, and then output the search result; In the obtained search results, each garment pattern point corresponds to an index of a fabric point respectively; After traversing all garment pattern points and completing the nearest neighbor search for all garment pattern points, generate a result list; wherein, the result list records the fabric point index mapped by each garment pattern point in the order of garment pattern points; Output the result list to represent the spatial mapping relationship between garment pattern points and fabric points; Among them, the steps of performing realistic rendering on the 3D sample garment specifically include: Based on the UV mapping technology, map the fabric image and texture information onto the 3D sample garment model to ensure that the texture coordinates correspond one-to-one with the surface of the 3D model; According to the position, color, and intensity of the light source in the virtual environment, calculate the light distribution on the surface of the 3D sample garment, and apply the Phong lighting model to calculate the reflection, refraction, and specular highlight effects; Apply anti-aliasing, depth of field, and ambient occlusion technologies to enhance the realism and detail performance of the 3D sample garment; According to the position, color, and intensity of the light source in the virtual environment, calculate the light distribution on the surface of the 3D sample garment, and apply the Phong lighting model to calculate the reflection, refraction, and specular highlight effects. The specific steps are as follows: Obtain the diffuse coefficient, specular coefficient, specular reflection coefficient, the position of the light source point, the position of the target point, the viewing direction vector, the refractive index, and the RGB value from the preset parameters in the virtual environment; Traverse each light source in the virtual environment and perform the following processing: If the light source is a point light source, based on the position of the light source point and the position of the target point, calculate the direction vector pointing from the target point to the light source point, and then normalize the direction vector to obtain the direction vector of the light ray; If the light source is a directional light source, directly determine the direction vector of the light ray; Calculate the dot product of the surface normal vector of the 3D sample garment and the direction vector of the light ray to obtain the diffuse dot product value; If the diffuse dot product value is greater than zero, calculate the diffuse intensity through the Phong lighting model based on the diffuse coefficient, RGB value, and diffuse dot product value; If the diffuse dot product value is less than zero, no calculation is performed; Based on the direction vector of the light ray and the surface normal vector of the 3D sample garment, obtain the direction vector of the reflected light ray through the law of reflection; Calculate the specular dot product value based on the dot product of the direction vector of the reflected light ray and the viewing direction vector; If the specular dot product value is greater than zero, obtain the specular reflection intensity through the Phong lighting model based on the specular reflection coefficient, specular coefficient, and specular dot product value; If the specular dot product value is less than zero, no calculation is performed; Based on the direction vector of the light ray and the refractive index, the direction vector of the refracted light ray is calculated through Snell's law; Perform a dot product calculation on the line-of-sight direction vector and the direction of the refracted light ray to obtain the refraction dot product value; Based on the refraction dot product value and the RGB values, obtain the refraction intensity through the Phong illumination model; Add the diffuse reflection intensity, specular reflection intensity, and refraction intensity of the current light source to obtain the total illumination intensity; Accumulate the total illumination intensities of all light sources to obtain the comprehensive illumination intensity; Among them, the step of determining the user's interested fabrics based on the behavioral trajectory data and sending recommended fabric information to the user specifically includes: Determine the user's interest level in each 3D sample garment based on interaction data, dwell time, and click count; Retrieve the fabrics corresponding to each 3D sample garment, calculate the comprehensive interest score of the user for each fabric according to the interest level, and determine the user's interested fabrics; Generate a personalized fabric recommendation list based on the user's interested fabrics, and send the recommended fabric information to the user, where the recommended fabric information includes pictures, names, and brief descriptions; Determine the user's interest level in each 3D sample garment based on interaction data, dwell time, and click count. The specific steps are as follows: Obtain the weight coefficients of the interaction data, dwell time, and click count respectively; Obtain the maximum values of the interaction data, dwell time, and click count; Divide the interaction data by the maximum value of the interaction data to obtain the normalized interaction data; Divide the dwell time by the maximum value of the dwell time to obtain the normalized dwell time; Divide the click count by the maximum value of the click count to obtain the normalized click count; Multiply the normalized interaction data, normalized dwell time, and normalized click count by the weight coefficients of the interaction data, dwell time, and click count respectively to obtain the weighted interaction data, weighted dwell time, and weighted click count; Add the weighted interaction data, weighted dwell time, and weighted click count to obtain the user's interest level in each 3D sample garment.

2. The digital fabric management method for clothing design according to claim 1, wherein The step of real-time monitoring of the user's behavioral trajectory data in the VR fabric exhibition hall specifically includes: Based on the sensors built into the VR headset, record the user's movement path in the exhibition hall in real time to determine the browsing path; Capture the user's interaction behaviors with the 3D sample garments. The interaction behaviors include clicking, dragging, and zooming in and out, and record the interaction type and timestamp to obtain the interaction data; Statistical analysis of the dwell time of the user in front of different 3D sample garments and the click count on different 3D sample garments.

3. A digital fabric management system for clothing design, characterized in that, The system applies the digital fabric management method for clothing design described in any one of claims 1 to 2 below. The system includes: A fabric data determination module for collecting fabric images and texture information through a scanner, entering the fabric data into the Style3D system, and establishing a fabric database. The fabric data includes material, color, texture, pattern, and physical properties; A pattern parameter determination module for importing the clothing pattern and pattern parameters based on Style3D, initializing the corresponding relationship between the fabric and the pattern, and ensuring that the fabric can be correctly mapped to the pattern; The fabric flexibility simulation module is used to combine the fabric with the clothing pattern based on the flexibility simulation algorithm to generate a 3D sample garment, and perform realistic rendering on the 3D sample garment based on the rendering engine of Style3D; The fabric VR display module is used to retrieve different types of 3D sample garments for VR display according to the layout and style of the VR fabric exhibition hall; The behavior trajectory collection module is used to monitor the behavior trajectory data of the user in the VR fabric exhibition hall in real time, and the behavior trajectory data includes browsing path, interaction data, stay time, and click times; The fabric recommendation information module is used to determine the fabrics of interest to the user based on the behavior trajectory data and send recommendation fabric information to the user.

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