Garment design method, device and equipment based on human body three-dimensional modeling and medium

Abstract

The invention relates to the technical field of costume design, and discloses a costume design method and device based on human body three-dimensional modeling, equipment and a medium, and the method comprises the steps: obtaining human body three-dimensional data; generating a three-dimensional human body model based on the three-dimensional data; preprocessing the three-dimensional human body model to obtain an optimized three-dimensional human body model; and performing costume design by using the optimized three-dimensional human body model, and generating a costume effect picture and animation of the target costume. According to the method, advanced technologies such as computer vision, laser scanning and depth camera shooting are used for capturing human body three-dimensional data, and an accurate three-dimensional human body model is generated. Through design in a three-dimensional environment, try-on and adjustment design can be directly carried out on the three-dimensional human body model. And by combining 3D modeling, simulation and rendering technologies, virtual fitting and dynamic display are realized, and the authenticity and interactivity of the design are greatly improved. By providing a high-precision three-dimensional human body model, the authenticity of the design is enhanced, and the accuracy and integrity of data capture are improved.

Description

Technical Field

[0001] This invention relates to the field of clothing design technology, specifically to clothing design methods, devices, equipment, and media based on three-dimensional human body modeling. Background Technology

[0002] With the advancement of science and civilization, human artistic design methods are constantly evolving. In the information age, the ways in which human culture is disseminated have changed significantly compared to the past, and the strict boundaries between industries are blurring. Fashion design belongs to the category of arts and crafts, and is an art form that combines practicality and artistry. Fashion design is a creative act of planning and creating solutions to various problems in people's clothing and daily life.

[0003] In related technologies, traditional clothing design systems currently rely primarily on graphic design software such as Adobe Illustrator and Photoshop for clothing design. This largely depends on two-dimensional graphics and paper pattern design, requiring designers to conceive and draw designs on a flat surface. Clothing pattern making and adjustments are typically done manually, which is time-consuming. Summary of the Invention

[0004] In view of this, the present invention provides a clothing design method, device, equipment and medium based on three-dimensional human body modeling to solve the problem of high labor costs in traditional clothing design.

[0005] In a first aspect, the present invention provides a clothing design method based on three-dimensional human body modeling, the method comprising:

[0006] Acquire human body 3D data;

[0007] Generate a 3D human body model based on 3D data;

[0008] The 3D human body model is preprocessed to obtain an optimized 3D human body model;

[0009] The optimized 3D human body model is used for clothing design, generating clothing renderings and animations of the target garment.

[0010] This invention utilizes advanced technologies such as computer vision, laser scanning, and depth photography to capture three-dimensional human body data, generating accurate three-dimensional human body models. Designing within a three-dimensional environment allows for direct try-on and adjustments on the 3D human body model. Combining 3D modeling, simulation, and rendering technologies enables virtual try-on and dynamic display, significantly enhancing the realism and interactivity of the designs. Providing high-precision three-dimensional human body models enhances the realism of the designs. The integration of multiple technologies also contributes to improving the accuracy and completeness of data capture.

[0011] In one optional implementation, the human body 3D data includes 2D image data, 3D point cloud data, RGB images of the human body surface, and depth information of the human body surface. Acquiring the human body 3D data includes:

[0012] Two-dimensional image data from different angles were acquired using image acquisition devices at different angles.

[0013] A laser scanner is used to scan the surface of the human body to obtain three-dimensional point cloud data.

[0014] Using depth camera technology, RGB images and depth information of the human body surface are collected.

[0015] In this method, multiple image acquisition devices are used to capture images of the human body from different angles to obtain multi-view two-dimensional image data; a laser scanner is used to scan the human body to obtain accurate three-dimensional point cloud data; and a depth camera is used to acquire RGB images and depth information of the human body surface, providing more comprehensive two-dimensional data for the subsequent generation of a three-dimensional human body model, thereby making the three-dimensional human body model closer to the actual human body, the designed clothing more fit, and improving the user experience.

[0016] In one alternative implementation, a three-dimensional human body model is generated based on three-dimensional data, including:

[0017] Using computer vision algorithms, three-dimensional reconstruction is performed on two-dimensional image data from different angles to obtain the three-dimensional reconstructed human body surface.

[0018] The changes in the positions of preset marker points on the surface of the human body after 3D reconstruction are tracked, and the 3D coordinates are calculated using the changes in the positions of the marker points.

[0019] Construct a 3D mesh using 3D coordinates;

[0020] The time and phase changes of laser reflection are measured using a laser scanner. Based on the time and phase changes, the first point cloud data corresponding to the three-dimensional reconstructed human body surface is generated on a three-dimensional mesh.

[0021] The RGB image and depth information of the reconstructed human body surface are acquired using depth camera technology, and the second point cloud data corresponding to the reconstructed human body surface is generated on the three-dimensional mesh.

[0022] A 3D human body model is generated based on the first point cloud data and the second point cloud data.

[0023] This approach combines multiple technologies to improve the accuracy and completeness of data capture, thereby providing a high-precision 3D human body model, enhancing the realism of the design, and ensuring the high precision and quality of the generated 3D human body model.

[0024] In one optional implementation, a three-dimensional human body model is generated based on the first point cloud data and the second point cloud data, including:

[0025] Based on a preset filter, duplicate noise points and invalid data points in the first point cloud data and the second point cloud data are identified and deleted to obtain filtered first point cloud data and filtered second point cloud data. The preset filter includes at least one of the mean filter, median filter and bilateral filter.

[0026] Based on a preset interpolation method, the gaps in the filtered first point cloud data and the filtered second point cloud data are filled to obtain the filled first point cloud data and the filled second point cloud data.

[0027] Using the filled first point cloud data and the filled second point cloud data, a triangular mesh is generated, and isosurfaces are generated in the triangular mesh;

[0028] The three-dimensional human body model is reconstructed based on the isosurface to obtain the three-dimensional human body model.

[0029] In this method, a three-dimensional human body model is generated by reconstructing a three-dimensional surface based on isosurfaces; by performing triangulation based on optimized point cloud data, a non-overlapping triangular mesh is generated, which improves the accuracy and detail of the three-dimensional human body model, ensures the integrity and continuity of the model, and facilitates subsequent processing and design.

[0030] In one optional implementation, the three-dimensional human body model is preprocessed to obtain an optimized three-dimensional human body model, including:

[0031] Based on the preset Laplacian smoothing and bidirectional smoothing algorithms, noise and unsmooth parts of the optimized 3D human body model are removed to obtain the processed 3D human body model.

[0032] The color information of the two-dimensional image data is mapped onto the processed three-dimensional human body model to obtain an optimized three-dimensional human body model with texture.

[0033] In this method, a textured 3D model is generated by mapping the color information of the original image onto a 3D human body model. Laplacian smoothing and bidirectional smoothing algorithms are used to remove noise and unevenness from the model's surface. Mapping the color information of the original image onto the processed mesh model improves the model's resolution and detail, enhancing the visual appeal and realism of the 3D human body model. This ensures rich detail and provides a better foundation for clothing design.

[0034] In one alternative implementation, clothing design is performed using an optimized 3D human body model to generate clothing renderings and animations of the target garment, including:

[0035] Using animation and pose capture, the skeletal structure of the optimized 3D human body model is extracted;

[0036] Based on a preset finite element analysis algorithm and a mass spring model, the physical behavior of different fabrics is simulated. The physical behavior includes at least the elastic coefficient, stiffness coefficient, density, and friction coefficient.

[0037] Based on the skeletal structure and physical behavior of different fabrics under different postures and movements, the fitting effect of the target clothing on the optimized three-dimensional human body model is dynamically simulated.

[0038] Ray tracing is performed on the skeletal structure, physical behavior of different fabrics, and fitting effect of the optimized 3D human body model to generate clothing renderings and animations of the target garment.

[0039] In this approach, clothing designs are created on optimized 3D human models, generating clothing renderings and animations. These renderings and animations can then be visualized, thereby improving the accuracy and efficiency of clothing design, allowing designers to intuitively see the effect of clothing on different human bodies, and enhancing user experience and design interactivity.

[0040] Secondly, the present invention provides a clothing design device based on three-dimensional human body modeling, the device comprising:

[0041] A 3D scanning module is used to acquire 3D data of the human body.

[0042] The human body modeling module is used to generate 3D human body models based on 3D data.

[0043] The human body model processing module is used to preprocess the 3D human body model to obtain an optimized 3D human body model.

[0044] The clothing design and editing module is used to design clothing using an optimized 3D human body model, and generate clothing renderings and animations of the target clothing.

[0045] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the clothing design method based on human body three-dimensional modeling described in the first aspect or any corresponding embodiment.

[0046] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the clothing design method based on human body three-dimensional modeling described in the first aspect or any corresponding embodiment thereof.

[0047] Fifthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the clothing design method based on human body three-dimensional modeling described in the first aspect or any corresponding embodiment thereof. Attached Figure Description

[0048] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0049] Figure 1 This is a flowchart illustrating a clothing design method based on three-dimensional human body modeling according to an embodiment of the present invention.

[0050] Figure 2 This is a schematic diagram of the structure of a clothing design system based on three-dimensional human body modeling according to an embodiment of the present invention.

[0051] Figure 3 This is a flowchart illustrating another clothing design method based on three-dimensional human body modeling according to an embodiment of the present invention.

[0052] Figure 4 This is a flowchart illustrating another clothing design method based on three-dimensional human body modeling according to an embodiment of the present invention.

[0053] Figure 5 This is a structural block diagram of a clothing design device based on three-dimensional human body modeling according to an embodiment of the present invention.

[0054] Figure 6 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] In related technologies,

[0057] To address the aforementioned problems, this invention provides a clothing design method based on 3D human body modeling, used in a computer device. It should be noted that the executing entity can be a clothing design device based on 3D human body modeling. This device can be implemented as part or all of the computer device through software, hardware, or a combination of both. The computer device can be a terminal, client, or server. The server can be a single server or a server cluster composed of multiple servers. In this embodiment, the terminal can be a smartphone, personal computer, tablet computer, or other smart hardware device. The following method embodiments all use a computer device as the executing entity for illustration.

[0058] The computer equipment in this embodiment is suitable for use scenarios involving automatic clothing design based on 3D human body modeling. This invention provides a clothing design method based on 3D human body modeling, utilizing advanced technologies such as computer vision, laser scanning, and depth photography to capture 3D human body data and generate accurate 3D human body models. By designing in a 3D environment, designs can be directly tried on and adjusted on the 3D human body model. Combining 3D modeling, simulation, and rendering technologies enables virtual try-on and dynamic display, greatly improving the realism and interactivity of the design. Providing a high-precision 3D human body model enhances the realism of the design. The combination of multiple technologies also helps improve the accuracy and completeness of data capture.

[0059] According to an embodiment of the present invention, a method for clothing design based on three-dimensional human body modeling is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0060] This embodiment provides a clothing design method based on three-dimensional human body modeling, which can be used with the aforementioned computer equipment. Figure 1 This is a flowchart of a clothing design method based on three-dimensional human body modeling according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0061] Step S101: Obtain three-dimensional human body data.

[0062] In one example, acquiring two-dimensional images of the human body from multiple angles may include: using multiple cameras to capture images of the human body from different angles to obtain two-dimensional image data from multiple perspectives; using a laser scanner to scan the human body to obtain accurate three-dimensional point cloud data; and acquiring RGB images and depth information of the human body surface through a depth camera.

[0063] Step S102: Generate a three-dimensional human body model based on the three-dimensional data.

[0064] In one example, based on a preset modeling technique, three-dimensional data of the human body is captured, and based on the three-dimensional data, a corresponding three-dimensional human body model is generated; wherein, the modeling technique includes at least computer vision technology, laser scanning technology, and depth camera technology.

[0065] Step S103: Preprocess the 3D human body model to obtain an optimized 3D human body model.

[0066] In one example, an optimized 3D human body model is obtained by processing and optimizing the 3D human body model.

[0067] Step S104: Use the optimized 3D human body model to design clothing and generate clothing renderings and animations of the target clothing.

[0068] In one example, clothing design is performed on an optimized 3D human body model, and corresponding clothing renderings and animations are generated. The clothing renderings and animations can also be visualized.

[0069] In one implementation scenario, Figure 2 This is a structural schematic diagram of a clothing design system based on three-dimensional human body modeling according to an embodiment of the present invention, as shown below. Figure 2 As shown, the clothing design system based on 3D human body modeling includes: a 3D scanning and modeling module, used to capture 3D human body data based on preset modeling techniques, and generate corresponding 3D human body models based on the 3D data. The modeling techniques include at least computer vision technology, laser scanning technology, and depth camera technology; a human body model processing module, used to process and optimize the 3D human body model; a clothing design and editing module, used to design clothing on the optimized 3D human body model and generate corresponding clothing renderings and animations; and a human-computer interaction and visualization module, used to visualize the clothing renderings and animations.

[0070] This embodiment provides a clothing design method based on 3D human body modeling. It utilizes advanced technologies such as computer vision, laser scanning, and depth photography to capture 3D human body data and generate accurate 3D human body models. By designing in a 3D environment, designs can be directly tried on and adjusted on the 3D human body model. Combining 3D modeling, simulation, and rendering technologies enables virtual try-on and dynamic display, greatly improving the realism and interactivity of the design. Providing a high-precision 3D human body model enhances the realism of the design. The combination of multiple technologies also helps improve the accuracy and completeness of data capture.

[0071] This embodiment provides a clothing design method based on three-dimensional human body modeling, which can be used with the aforementioned computer equipment. Figure 3This is a flowchart of another clothing design method based on three-dimensional human body modeling according to an embodiment of the present invention, such as... Figure 3 As shown, the process includes the following steps:

[0072] Step S301: Obtain human body 3D data.

[0073] Specifically, the three-dimensional human body data includes two-dimensional image data, three-dimensional point cloud data, RGB images of the human body surface, and depth information of the human body surface. Step S301 includes:

[0074] Step S3011: Use image acquisition devices at different angles to acquire two-dimensional image data at different angles.

[0075] Step S3012: Use a laser scanner to scan the surface of the human body and measure the three-dimensional point cloud data.

[0076] Step S3013: Using depth camera technology, acquire RGB images of the human body surface and depth information of the human body surface.

[0077] In one example, 3D human body data is acquired through a 3D scanning and modeling module. This module includes a multi-view stereo reconstruction unit, used to acquire 2D images of the human body from multiple angles. A preset computer vision algorithm is then used to perform 3D reconstruction on these 2D images. The computer vision algorithm includes at least a structure-motion algorithm and a multi-view stereo reconstruction algorithm. Multiple cameras are used to capture images of the human body from different angles, acquiring multi-view 2D image data.

[0078] Specifically, a laser scanner is used to scan the human body to obtain precise 3D point cloud data. A depth camera is used to acquire RGB images and depth information of the human body surface.

[0079] In this method, multiple image acquisition devices are used to capture images of the human body from different angles to obtain multi-view two-dimensional image data; a laser scanner is used to scan the human body to obtain accurate three-dimensional point cloud data; and a depth camera is used to acquire RGB images and depth information of the human body surface, providing more comprehensive two-dimensional data for the subsequent generation of a three-dimensional human body model, thereby making the three-dimensional human body model closer to the actual human body, the designed clothing more fit, and improving the user experience.

[0080] Step S302: Generate a three-dimensional human body model based on the three-dimensional data.

[0081] Specifically, step S302 includes:

[0082] Step S3021: Using computer vision algorithms, three-dimensional reconstruction is performed on two-dimensional image data from different angles to obtain the three-dimensional reconstructed human body surface.

[0083] Step S3022: Track the position changes of preset marker points on the surface of the human body after 3D reconstruction, and calculate the 3D coordinates using the position changes of the marker points.

[0084] Step S3023: Construct a three-dimensional mesh using three-dimensional coordinates.

[0085] Step S3024: Measure the time and phase changes of laser reflection using a laser scanner. Based on the time and phase changes, generate the first point cloud data corresponding to the three-dimensional reconstructed human body surface on a three-dimensional mesh.

[0086] Step S3025: Use depth camera technology to acquire RGB images and depth information of the reconstructed human body surface, and generate second point cloud data corresponding to the reconstructed human body surface on the three-dimensional mesh.

[0087] Step S3026: Generate a three-dimensional human body model based on the first point cloud data and the second point cloud data.

[0088] In some optional implementations, step S3026 above includes:

[0089] Step a1: Based on a preset filter, identify and delete duplicate noise points and invalid data points in the first point cloud data and the second point cloud data to obtain filtered first point cloud data and filtered second point cloud data. The preset filter includes at least one of a mean filter, a median filter and a bilateral filter.

[0090] Step a2: Based on a preset interpolation method, fill the gaps in the filtered first point cloud data and the filtered second point cloud data to obtain the filled first point cloud data and the filled second point cloud data.

[0091] Step a3: Using the filled first point cloud data and the filled second point cloud data, generate a triangular mesh, and generate isosurfaces in the triangular mesh.

[0092] Step a4: Reconstruct the three-dimensional human body model based on the isosurface to obtain the three-dimensional human body model.

[0093] In one example, a 3D human body model is generated through a 3D scanning and modeling module. This module also includes: a marker tracking unit, used to capture the positional changes of pre-set markers on the 3D reconstructed human body surface and calculate the 3D coordinates; a mesh construction unit, used to construct a 3D mesh using the 3D coordinates; a lidar unit, used to use a laser scanner to illuminate the human body surface, measure the time and phase changes of the reflected laser light, and generate the corresponding first point cloud data on the 3D mesh; a depth camera unit, used to use preset depth camera technology to capture the RGB image and depth information of the 3D reconstructed human body surface and generate second point cloud data containing color and depth information on the 3D mesh; and a 3D human body model unit, used to further transform and optimize the first and second point cloud data into a mesh to generate a 3D human body model.

[0094] For example, the three-dimensional human body model unit includes: a data denoising unit, used to identify and delete duplicate noise points and invalid data points in the first point cloud data and the second point cloud data based on a preset filter; wherein the filter includes at least one of a mean filter, a median filter, and a bilateral filter; a hole filling unit, used to fill holes in the first point cloud data and the second point cloud data based on a preset interpolation method; a triangulation unit, used to generate a non-overlapping triangular mesh using the filled first point cloud data and the second point cloud data, and generate isosurfaces in the preset three-dimensional mesh; and a three-dimensional human body model unit, used to reconstruct the three-dimensional surface based on the isosurfaces to generate the corresponding three-dimensional human body model.

[0095] The data denoising unit uses filters to identify and remove noise and invalid data points. The acquired point cloud data is filtered to remove noise and invalid data points. The hole-filling unit uses interpolation methods to fill holes in the point cloud data, ensuring model integrity. The triangulation unit generates non-overlapping triangular meshes and isosurfaces. The isosurface generation steps include calculating the density field or distance field in 3D space based on the point cloud data. The Marching Cubes algorithm is used to extract isosurfaces from the density field, and the 3D space is divided into cubes. The values ​​of the vertices are calculated for each cube to determine the position of the isosurfaces. The 3D human body modeling unit reconstructs the 3D surface based on the isosurfaces, generating a 3D human body model. Based on the optimized point cloud data, triangulation is performed to generate non-overlapping triangular meshes, improving the accuracy and detail of the 3D human body model. This technical solution ensures the integrity and continuity of the model, facilitating subsequent processing and design.

[0096] The multi-view stereo reconstruction unit acquires 2D images from multiple angles and performs 3D reconstruction using structural motion algorithms and multi-view stereo algorithms. The marker tracking unit captures the positional changes of preset markers and calculates their 3D coordinates. Markers, which can be colored spots, reflective spheres, or other high-contrast markers, are needed to capture positional changes or are preset on the human body surface to ensure easy identification in the image. Alternatively, multiple cameras can be used to capture images of the human body containing markers from different angles, ensuring that each marker is captured from multiple viewpoints. Computer vision algorithms (such as blob detection and color thresholding) are used to automatically identify the positions of the markers in the acquired images, ensuring accurate positioning of the markers in each viewpoint for subsequent processing. Feature matching algorithms (such as SIFT, SURF, and ORB) are used to find corresponding markers in images from different viewpoints. Triangulation is used to calculate the positional correspondence of markers in different images. Feature points are extracted from the multi-view images and matched. Triangulation is used to calculate the 3D coordinates of the markers based on their positions in multiple viewpoints. The mesh construction unit constructs a 3D mesh using these 3D coordinates. The application structure calculates the camera's position and pose using motion algorithms to initially reconstruct a 3D point cloud on a 3D mesh. The LiDAR unit generates the first point cloud data using laser scanning technology. The depth camera unit captures RGB images and depth information to generate the second point cloud data. Optical flow is used to track the position changes of marker points in consecutive image frames, ensuring the continuity and accuracy of marker point positions during human movement. Multi-view stereo technology is used to combine depth information from multiple viewpoint images to generate high-precision 3D point cloud data. The 3D human model unit performs mesh transformation and optimization on the first and second point cloud data to generate a 3D human model. The generation of the triangular mesh mainly involves acquiring high-precision 3D point cloud data from multi-view images, laser scanning, and depth camera footage. Filtering techniques (such as mean filters, median filters, and bilateral filters) are used to remove noise and invalid data points from the point cloud data. Interpolation methods are used to fill holes in the point cloud data to ensure data integrity. The Delaunay triangulation algorithm or the Poisson surface reconstruction algorithm is used to triangulate the point cloud data, generating a non-overlapping triangular mesh. Delaunay triangulation ensures that the generated triangles do not contain the inner circle of other points. Poisson surface reconstruction generates a smooth triangular mesh by fitting the point cloud. This technical solution provides a high-precision 3D human body model, enhancing the realism of the design. The combination of multiple technologies also helps improve the accuracy and completeness of data capture.

[0097] This approach combines multiple technologies to improve the accuracy and completeness of data capture, thereby providing a high-precision 3D human body model, enhancing the realism of the design, and ensuring the high precision and quality of the generated 3D human body model. The 3D human body model is generated by reconstructing the 3D surface based on isosurfaces; by performing triangulation based on optimized point cloud data to generate non-overlapping triangular meshes, the accuracy and detail of the 3D human body model are improved, ensuring the model's integrity and continuity, facilitating subsequent processing and design.

[0098] Step S303 involves preprocessing the 3D human body model to obtain an optimized 3D human body model. For details, please refer to [link to relevant documentation]. Figure 1 Step S103 of the illustrated embodiment will not be described again here.

[0099] Step S304: Using the optimized 3D human body model, clothing design is performed to generate a clothing rendering and animation of the target garment. For details, please refer to [link to relevant documentation]. Figure 1 Step S104 of the illustrated embodiment will not be described again here.

[0100] This embodiment provides a clothing design method based on 3D human body modeling. It utilizes multiple image acquisition devices to capture images of the human body from different angles, obtaining multi-view 2D image data. A laser scanner is used to scan the human body, acquiring precise 3D point cloud data. A depth camera acquires RGB images and depth information of the human body surface, providing more comprehensive 2D data for subsequent generation of the 3D human body model. This results in a 3D human body model that more closely resembles the actual human body, leading to a better-fitting garment and improved user experience. The combination of multiple technologies helps improve the accuracy and completeness of data capture, thus providing a high-precision 3D human body model, enhancing the realism of the design, and ensuring the high precision and quality of the generated 3D human body model. The 3D human body model is generated by reconstructing the 3D surface based on isosurfaces. Triangulation based on optimized point cloud data generates non-overlapping triangular meshes, improving the accuracy and detail of the 3D human body model, ensuring the model's integrity and continuity, and facilitating subsequent processing and design.

[0101] This embodiment provides a clothing design method based on three-dimensional human body modeling, which can be used with the aforementioned computer equipment. Figure 4 This is a flowchart of another clothing design method based on three-dimensional human body modeling according to an embodiment of the present invention, such as... Figure 4 As shown, the process includes the following steps:

[0102] Step S401: Obtain 3D human body data. For details, please refer to [link / reference]. Figure 3 Step S301 of the illustrated embodiment will not be described again here.

[0103] Step S402: Generate a 3D human body model based on the 3D data. For details, please refer to [link to details]. Figure 3 Step S302 of the illustrated embodiment will not be described again here.

[0104] Step S403: Preprocess the 3D human body model to obtain an optimized 3D human body model.

[0105] Specifically, step S403 includes:

[0106] Step S4031: Based on the preset Laplacian smoothing and bidirectional smoothing algorithms, remove noise and unsmooth parts from the optimized 3D human body model to obtain the processed 3D human body model.

[0107] Step S4032: Map the color information of the two-dimensional image data to the processed three-dimensional human body model to obtain an optimized three-dimensional human body model with texture.

[0108] In one example, a human body model processing module preprocesses a 3D human body model to obtain an optimized 3D human body model. The human body model processing module includes: a smoothing unit, which removes noise and uneven parts from the surface of the 3D human body model based on preset Laplacian smoothing and bidirectional smoothing algorithms to obtain a processed mesh model; a texture mapping unit, which maps the color information of the original image onto the processed mesh model to generate a textured 3D model; and an optimization unit, which improves the resolution and detail of the 3D model to optimize the 3D human body model.

[0109] Mapping the color information of the original image onto a triangular mesh generates a textured 3D model. The smoothing unit uses Laplacian smoothing and bidirectional smoothing algorithms to remove noise and unevenness from the model's surface. The texture mapping unit maps the color information of the original image onto the processed mesh model. The optimization unit improves the model's resolution and detail. Texture mapping finds the corresponding pixel in the original image for each vertex in the triangular mesh and assigns the RGB color value of the corresponding pixel to that vertex. This calculates the texture coordinates of each triangle, ensuring the texture image is correctly aligned with the 3D mesh. This improves the visual effect and realism of the 3D human body model, ensuring rich detail and providing a better foundation for clothing design.

[0110] In this method, a textured 3D model is generated by mapping the color information of the original image onto a 3D human body model. Laplacian smoothing and bidirectional smoothing algorithms are used to remove noise and unevenness from the model's surface. Mapping the color information of the original image onto the processed mesh model improves the model's resolution and detail, enhancing the visual appeal and realism of the 3D human body model. This ensures rich detail and provides a better foundation for clothing design.

[0111] Step S404: Use the optimized 3D human body model to design clothing and generate clothing renderings and animations of the target clothing.

[0112] Specifically, step S404 includes:

[0113] Step S4041: Using animation and pose capture, extract the skeletal structure of the optimized 3D human body model.

[0114] Step S4042: Based on the preset finite element analysis algorithm and mass spring model, simulate the physical behavior of different fabrics.

[0115] In embodiments of the present invention, the physical behavior includes at least the elastic coefficient, stiffness coefficient, density, and friction coefficient.

[0116] Step S4043: Based on the skeletal structure and physical behavior of different fabrics under different postures and movements, dynamically simulate the fitting effect of the target clothing on the optimized three-dimensional human body model.

[0117] Step S4044: Perform ray tracing on the skeletal structure, physical behavior of different fabrics, and fitting effect of the optimized 3D human body model to generate clothing effect diagrams and animations of the target garment.

[0118] In one example, the clothing design and editing module generates clothing renderings and animations of the target garment. This module includes: a skeleton extraction unit for animation and pose capture, extracting the skeletal structure of a 3D human body model; a fabric physical property simulation unit for simulating the physical behavior of different fabrics based on a preset finite element analysis algorithm and a point-spring model; wherein the physical behavior includes at least the elastic coefficient, stiffness coefficient, density, and friction coefficient; a clothing try-on simulation unit for dynamically simulating the try-on effect of the garment on the 3D human body model based on the skeletal structure under different postures and movements and the physical behavior of different fabrics; and a rendering and visualization unit for performing ray tracing on the skeletal structure of the 3D human body model, the physical behavior of different fabrics, and the try-on effect to generate corresponding clothing renderings and animations.

[0119] The skeleton extraction unit pre-marks points on the human body surface and identifies the positions of these markers in multi-view images; it extracts the skeletal structure of the 3D human model for animation and pose capture. The fabric physical property simulation unit uses finite element analysis (FEA) algorithms and a point-spring model to simulate the physical behavior of the fabric. Specifically, this includes: establishing a physical model of the fabric, including parameters such as elasticity, rigidity, density, and coefficient of friction; simulating fabric deformation and stress distribution through finite element analysis (FEA); and simulating the elasticity and dynamic behavior of the fabric through a point-spring model. The clothing try-on simulation unit, based on the skeletal structure and fabric physical behavior under different postures and movements, uses a physics engine (such as Bullet or PhysX) for real-time simulation, simulating fabric deformation under different postures and movements, and dynamically simulating the clothing try-on effect. The rendering and visualization unit performs ray tracing on 3D human models, fabric physics, and try-on effects, projecting rays from a virtual camera to every pixel in the scene; calculating the intersections of rays with 3D objects (such as triangular meshes); calculating the ray path based on reflection and refraction to simulate the propagation of light on different material surfaces; calculating the color and brightness of light at the intersection points based on light source and material properties; performing ray tracing rendering on static 3D scenes to generate high-quality clothing renderings; performing frame-by-frame ray tracing rendering on dynamic 3D scenes (including human movements and fabric deformation) to generate continuous animation frames; and performing post-processing such as color correction and shadow processing on the rendered images and animations to improve visual effects. The generated clothing renderings and animations can be exported to common image and video formats for users to view and share. It provides realistic clothing try-on effects to help designers adjust and optimize designs, dynamically showcasing the effects of clothing in different poses and improving design intuitiveness.

[0120] For example, a clothing design system based on 3D human body modeling may further include a human-computer interaction and visualization module, which includes: a user interface unit for user input and access to other modules of the clothing design system; a layer management unit for managing and editing design elements of different layers using preset drawing tools; a 3D visualization unit for displaying clothing renderings and animations through preset functions, including at least rotation, scaling, and movement functions; an import / export function unit for obtaining input dimensions and specifications and exporting clothing renderings and animations to preset image formats according to the input dimensions and specifications, including at least images and 3D model files; and a feedback and collaboration unit for providing commenting, annotation, and real-time collaboration functions.

[0121] The user interface unit provides users with an interface for inputting information and accessing other modules of the system. The layer management unit manages and edits design elements across different layers. The 3D visualization unit displays garment renderings and animations, supporting rotation, scaling, and movement. The import / export function unit imports dimensions and specifications and exports renderings and animations to specified formats. The feedback and collaboration unit provides commenting, annotation, and real-time collaboration features. It offers a user-friendly interface to enhance the user experience. It supports team collaboration and design adjustments, improving design efficiency.

[0122] In this approach, clothing designs are created on optimized 3D human models, generating clothing renderings and animations. These renderings and animations can then be visualized, thereby improving the accuracy and efficiency of clothing design, allowing designers to intuitively see the effect of clothing on different human bodies, and enhancing user experience and design interactivity.

[0123] This embodiment provides a clothing design method based on 3D human body modeling. By mapping the color information of the original image onto a 3D human body model, a textured 3D model is generated. Laplacian smoothing and bidirectional smoothing algorithms are used to remove noise and uneven parts from the model surface. The color information of the original image is mapped onto the processed mesh model, improving the model's resolution and detail, enhancing the visual effect and realism of the 3D human body model, ensuring rich detail, and providing a better foundation for clothing design. Clothing design is then performed on the optimized 3D human body model, generating clothing renderings and animations. These renderings and animations can be visualized, thereby improving the accuracy and efficiency of clothing design, allowing designers to intuitively see the effect of clothing on different human bodies, and enhancing user experience and design interactivity.

[0124] This embodiment also provides a clothing design device based on three-dimensional human body modeling. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0125] This embodiment provides a clothing design device based on three-dimensional human body modeling, such as... Figure 5 As shown, it includes:

[0126] The 3D scanning module 501 is used to acquire 3D human body data. For details, please refer to [link / reference needed]. Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0127] The human body modeling module 502 is used to generate 3D human body models based on 3D data. For details, please refer to [link / reference]. Figure 1 Step S102 of the illustrated embodiment will not be described again here.

[0128] The human body model processing module 503 is used to preprocess the 3D human body model to obtain an optimized 3D human body model. For details, please refer to [link to relevant documentation]. Figure 1 Step S103 of the illustrated embodiment will not be described again here.

[0129] The Clothing Design and Editing module 504 is used to design clothing using an optimized 3D human body model, generating garment renderings and animations of the target garment. For details, please refer to [link to module 504]. Figure 1 Step S104 of the illustrated embodiment will not be described again here.

[0130] In some optional implementations, the three-dimensional human body data includes two-dimensional image data, three-dimensional point cloud data, RGB images of the human body surface, and depth information of the human body surface. The three-dimensional scanning module 501 includes:

[0131] The image acquisition unit is used to acquire two-dimensional image data from different angles using image acquisition devices at different angles.

[0132] The laser scanning unit is used to scan the surface of the human body using a laser scanner to obtain three-dimensional point cloud data.

[0133] The depth acquisition unit is used to acquire RGB images of the human body surface and depth information using depth camera technology.

[0134] In some alternative implementations, the human body modeling module 502 includes:

[0135] The human body surface 3D reconstruction unit is used to perform 3D reconstruction on 2D image data from different angles using computer vision algorithms to obtain the 3D reconstructed human body surface.

[0136] The marker tracking unit is used to track the position changes of preset markers on the surface of the human body after 3D reconstruction, and to calculate the 3D coordinates using the position changes of the markers.

[0137] 3D mesh building blocks are used to construct 3D meshes using 3D coordinates.

[0138] The first point cloud data generation unit is used to measure the time and phase changes of laser reflection using a laser scanner, and based on the time and phase changes, to generate the first point cloud data corresponding to the three-dimensional reconstructed human body surface on a three-dimensional mesh.

[0139] The second point cloud data generation unit is used to acquire RGB images and depth information of the three-dimensional reconstructed human body surface using depth camera technology, and generate the second point cloud data corresponding to the three-dimensional reconstructed human body surface on the three-dimensional mesh.

[0140] The human body model generation unit is used to generate a three-dimensional human body model based on the first point cloud data and the second point cloud data.

[0141] In some alternative implementations, the human model generation unit includes:

[0142] The data filtering subunit is used to identify and delete duplicate noise points and invalid data points in the first point cloud data and the second point cloud data based on a preset filter, so as to obtain filtered first point cloud data and filtered second point cloud data. The preset filter includes at least one of the mean filter, median filter and bilateral filter.

[0143] The data filling subunit is used to fill the gaps in the filtered first point cloud data and the filtered second point cloud data based on a preset interpolation method, so as to obtain the filled first point cloud data and the filled second point cloud data.

[0144] The isosurface generation sub-unit is used to generate a triangular mesh using the filled first point cloud data and the filled second point cloud data, and to generate isosurfaces in the triangular mesh.

[0145] The human body model reconstruction sub-unit is used to reconstruct the three-dimensional human body model based on the isosurface to obtain the three-dimensional human body model.

[0146] In some alternative implementations, the human model processing module 503 includes:

[0147] The noise removal unit is used to remove noise and unsmooth parts from the optimized 3D human body model based on preset Laplacian smoothing and bidirectional smoothing algorithms, so as to obtain the processed 3D human body model.

[0148] The color mapping unit is used to map the color information of two-dimensional image data to the processed three-dimensional human body model, resulting in an optimized three-dimensional human body model with texture.

[0149] In some alternative implementations, the clothing design and editing module 504 includes:

[0150] The skeleton extraction unit is used to extract the skeletal structure of the optimized 3D human model using animation and pose capture.

[0151] The physical simulation unit is used to simulate the physical behavior of different fabrics based on a preset finite element analysis algorithm and a mass spring model. The physical behavior includes at least the elastic coefficient, stiffness coefficient, density, and friction coefficient.

[0152] The try-on simulation unit is used to dynamically simulate the try-on effect of the target garment on an optimized 3D human body model based on the skeletal structure and physical behavior of different fabrics under different postures and movements.

[0153] The ray tracing unit is used to perform ray tracing on the skeletal structure, physical behavior of different fabrics, and fitting effect of the optimized 3D human body model, generating clothing renderings and animations of the target garment.

[0154] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0155] In this embodiment, the clothing design device based on human body 3D modeling is presented in the form of functional units. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0156] This invention also provides a computer device having the above-described features. Figure 5 The clothing design device shown is based on three-dimensional human body modeling.

[0157] Please see Figure 6 , Figure 6 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 6 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 6 Take a processor 10 as an example.

[0158] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GPA), or any combination thereof.

[0159] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0160] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0161] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0162] The computer device also includes an input device 30 and an output device 40. The processor 10, memory 20, input device 30, and output device 40 can be connected via a bus or other means. Figure 6 Taking the example of a connection between China and Israel via a bus.

[0163] Input device 30 can receive input numerical or character information, and generate key signal inputs related to user settings and function control of the computer device, such as a touchscreen, keypad, mouse, trackpad, touchpad, joystick, one or more mouse buttons, trackball, joystick, etc. Output device 40 may include display devices, auxiliary lighting devices (e.g., LEDs), and haptic feedback devices (e.g., vibration motors). The aforementioned display devices include, but are not limited to, liquid crystal displays, light-emitting diodes, displays, and plasma displays. In some alternative embodiments, the display device may be a touchscreen.

[0164] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0165] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0166] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A clothing design method based on three-dimensional human body modeling, characterized in that, The method includes: Acquire human body 3D data; Based on the aforementioned three-dimensional data, a three-dimensional human body model is generated; The three-dimensional human body model is preprocessed to obtain an optimized three-dimensional human body model; The optimized 3D human body model is used for clothing design, generating clothing renderings and animations of the target garment.

2. The method according to claim 1, characterized in that, The three-dimensional human body data includes two-dimensional image data, three-dimensional point cloud data, RGB images of the human body surface, and depth information of the human body surface. The acquisition of the three-dimensional human body data includes: Two-dimensional image data from different angles are acquired using image acquisition devices at different angles; A laser scanner is used to scan the surface of the human body to obtain three-dimensional point cloud data. Using depth camera technology, RGB images of the human body surface and depth information of the human body surface are acquired.

3. The method according to claim 2, characterized in that, The process of generating a three-dimensional human body model based on the three-dimensional data includes: Using computer vision algorithms, three-dimensional reconstruction is performed on the two-dimensional image data from different angles to obtain the three-dimensional reconstructed human body surface; The position changes of preset marker points on the surface of the reconstructed human body are tracked, and the three-dimensional coordinates are calculated using the position changes of the marker points. A three-dimensional mesh is constructed using the aforementioned three-dimensional coordinates; Using a laser scanner, the time and phase changes of laser reflection are measured. Based on the time and phase changes, the first point cloud data corresponding to the three-dimensional reconstructed human body surface is generated on the three-dimensional grid. The RGB image and depth information of the three-dimensional reconstructed human body surface are acquired using depth camera technology, and the second point cloud data corresponding to the three-dimensional reconstructed human body surface is generated on the three-dimensional mesh. The three-dimensional human body model is generated based on the first point cloud data and the second point cloud data.

4. The method according to claim 3, characterized in that, The step of generating the three-dimensional human body model based on the first point cloud data and the second point cloud data includes: Based on a preset filter, duplicate noise points and invalid data points in the first point cloud data and the second point cloud data are identified and deleted to obtain filtered first point cloud data and filtered second point cloud data. The preset filter includes at least one of a mean filter, a median filter and a bilateral filter. Based on a preset interpolation method, the gaps in the filtered first point cloud data and the filtered second point cloud data are filled to obtain the filled first point cloud data and the filled second point cloud data. Using the filled first point cloud data and the filled second point cloud data, a triangular mesh is generated, and an isosurface is generated in the triangular mesh; The three-dimensional human body model is reconstructed based on the isosurface to obtain the three-dimensional human body model.

5. The method according to claim 2, characterized in that, The preprocessing of the three-dimensional human body model to obtain an optimized three-dimensional human body model includes: Based on the preset Laplacian smoothing and bidirectional smoothing algorithms, noise and unsmooth parts of the optimized 3D human body model are removed to obtain the processed 3D human body model. The color information of the two-dimensional image data is mapped onto the processed three-dimensional human body model to obtain an optimized three-dimensional human body model with texture.

6. The method according to claim 1, characterized in that, The step of using the optimized 3D human body model to design clothing and generate clothing renderings and animations of the target clothing includes: The skeletal structure of the optimized 3D human body model is extracted using animation and pose capture. Based on a preset finite element analysis algorithm and a mass spring model, the physical behavior of different fabrics is simulated, and the physical behavior includes at least the elastic coefficient, stiffness coefficient, density and friction coefficient. Based on the skeletal structure under different postures and movements and the physical behavior of different fabrics, the fitting effect of the target garment on the optimized three-dimensional human body model is dynamically simulated. Ray tracing is performed on the skeletal structure of the optimized 3D human body model, the physical behavior of different fabrics, and the fitting effect to generate clothing effect images and animations of the target garment.

7. A clothing design device based on three-dimensional human body modeling, characterized in that, The device includes: A 3D scanning module is used to acquire 3D data of the human body. The human body modeling module is used to generate a three-dimensional human body model based on the three-dimensional data. The human body model processing module is used to preprocess the three-dimensional human body model to obtain an optimized three-dimensional human body model. The clothing design and editing module is used to design clothing using the optimized 3D human body model, and generate clothing renderings and animations of the target clothing.

8. A computer device, characterized in that, include: The device includes a memory and a processor, which are interconnected and the memory stores computer instructions. The processor executes the computer instructions to perform the clothing design method based on human body three-dimensional modeling as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the clothing design method based on human body three-dimensional modeling as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, It includes computer instructions for causing a computer to execute the clothing design method based on three-dimensional human body modeling as described in any one of claims 1 to 6.

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