A computer-aided based clothing design method and system

Abstract

This invention relates to the field of clothing design technology, specifically to a computer-aided clothing design method and system. The method includes acquiring all operation information and original clothing parameters from user actions on the computer-aided design interface; identifying the clothing modification area and modification parameters operated by the user based on all operation information and original clothing parameters; performing regional structure analysis on the user-operated clothing modification area to obtain the modification impact area; performing a fitting simulation on the clothing modification area based on the modification impact area and modification parameters to obtain qualified simulated fitting parameters; and adjusting the user-operated clothing modification parameters based on the qualified simulated fitting parameters to obtain the clothing design parameters. The purpose of this invention is to solve the problems of inaccurate fabric simulation and system delays in existing design methods, which lead to extended clothing design time and limited designer creativity.

Description

Technical Field

[0001] This invention relates to the field of clothing design technology, specifically to a computer-aided clothing design method and system. Background Technology

[0002] In the traditional clothing design process, designers complete their work by hand-drawing blueprints, creating physical patterns and sample garments. Modifications are costly and time-consuming, and precise representation is difficult when dealing with complex and intricately detailed garments. Currently, designers utilize digital tools provided by Computer-Aided Design (CAD) systems for assistance. Designers can create patterns on computers, view 3D garment effects, and even conduct virtual try-ons.

[0003] However, when designers attempt to create highly complex and detail-oriented haute couture garments—such as designs with layered pleats, asymmetrical cuts, or a mix of materials—existing garment design methods, in order to ensure smooth operation, automatically simplify the mesh of the 3D garment model. This results in the inaccurate reproduction of the fabric's natural behavior during subsequent virtual try-ons and physical simulations, leading to unnatural seepage or stiff deformation. Designers then need to manually adjust the mesh density and fabric parameters, which is time-consuming and causes significant system latency and lag, resulting in inaccurate feedback on their brushstrokes and easily disrupting their creative flow. Furthermore, the limitations of system performance and project time constraints negatively impact the uniqueness and artistic expression of the final design. Summary of the Invention

[0004] The purpose of this invention is to provide a computer-aided clothing design method and system to solve the problems that designers face when using existing clothing design methods to design complex clothing, such as inaccurate fabric simulation and system lag, which lead to extended design time and limited designer creativity.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a computer-aided clothing design method, comprising: Obtain all operation information and original clothing parameters performed by the user on the computer-aided design interface; Based on all the operation information and the original parameters of the clothing, identify the clothing modification area and clothing modification parameters operated by the user; Perform a region structure analysis on the clothing modification area operated by the user to obtain the area affected by the modification of the clothing modification area; Based on the area affected by the modification of the clothing modification area and the clothing modification parameters, a fitting simulation is performed on the clothing modification area to obtain the simulated fitting parameters that are qualified for fitting; wherein, the simulated fitting parameters include the fabric deformation of the modification area and the interaction force between overlapping fabrics; Based on the simulated fitting parameters that indicate the fitting was successful, the clothing modification parameters operated by the user are adjusted to obtain the clothing design parameters, thereby determining the user's clothing design scheme.

[0006] Preferably, the steps of identifying the clothing modification area and clothing modification parameters operated by the user based on all the operation information and the original clothing parameters include: Information identification is performed on all the operation information to obtain each operation parameter; Each of the operation parameters is compared with the original parameters of the clothing to determine the clothing modification parameters; Based on the original parameters of the clothing, perform regional analysis on each operation parameter to identify the clothing modification area operated by the user.

[0007] Preferably, the step of identifying all the operation information to obtain each operation parameter includes: Perform positional analysis on all the operation information to obtain the position coordinates of each operation; Perform operation action analysis on all the operation information to obtain the action information for each operation; Each operation parameter is determined based on the position coordinates of each operation and the action information of each operation.

[0008] Preferably, the step of determining each operation parameter based on the position coordinates of each operation and the action information of each operation includes: The position coordinates of each operation and the action information of each operation are associated to obtain the association information of each operation; The associated information of each operation is verified to obtain the parameters of each operation after the information verification is qualified; If the information verification fails, the position coordinates of each operation and the action information of each operation will be re-associated and an alarm will be issued.

[0009] Preferably, the step of performing a region structure analysis on the clothing modification area operated by the user to obtain the modification impact area of ​​the clothing modification area includes: Perform regional structure analysis on the clothing modification area operated by the user to determine the user operation area and modification elements of the clothing modification area. The modification elements include the seam relationship at the connection between the modified area and the unmodified area and the clothing fabric properties of the modified area. Based on the modified elements, identify the area affected by the unmodified regions; The modification impact area of ​​the clothing modification area is obtained based on the user operation area of ​​the clothing modification area and the impact area of ​​the unmodified area.

[0010] Preferably, the step of identifying the affected area of ​​the unmodified region based on the modified element includes: Based on the modified elements, determine the fold area and deformation area that cause the modified area to compress the unmodified area; Using the wrinkle area and deformation area, the influence area of ​​the unmodified area is identified and processed to obtain the influence area of ​​the unmodified area.

[0011] Preferably, the step of obtaining the modification influence area of ​​the clothing modification area based on the user operation area of ​​the clothing modification area and the influence area of ​​the unmodified area includes: The original area affected by the modification of the clothing area is determined based on the user's operation area in the clothing modification area and the area affected by the unmodified area. The original area affected by the modification of the clothing area is denoised to obtain the denoised original area affected by the modification. The original area affected by the denoised modification is subjected to area correction processing to obtain the area affected by the modification of the clothing modification area.

[0012] Preferably, the step of performing a fitting simulation on the clothing modification area based on the modification impact area and clothing modification parameters to obtain qualified simulated fitting parameters includes: Based on the clothing modification parameters, a try-on simulation is performed on the area affected by the modification of the clothing to obtain a try-on rendering image; The similarity comparison value is obtained by comparing the trial rendering image with the preset rendering image. Based on the similarity comparison value, a qualified virtual try-on rendering image is determined. Based on the simulated fitting rendering image that shows a successful fitting, the simulated fitting parameters are obtained.

[0013] Preferably, in the step of obtaining all operation information and original parameters of clothing performed by the user on the computer-aided design interface, the step of obtaining all operation information includes: Obtain all raw information about the user's actions on the computer-aided design interface; Analyze the speed, direction changes, and dwell time in all the original information of the operations; Based on the speed, direction change, and dwell time in all the original operation information, determine the operation error coefficient for each operation information; Using the operation error coefficient of each operation information, noise reduction processing is performed on all original operation information to obtain all operation information.

[0014] The present invention also provides a computer-aided clothing design system, the system comprising: The information acquisition module is used to acquire all operation information and original parameters of clothing performed by the user on the computer-aided design interface; The region identification module is used to identify the clothing modification region and clothing modification parameters operated by the user based on all the operation information and the original clothing parameters; The area analysis module is used to perform regional structure analysis on the clothing modification area operated by the user to obtain the area affected by the modification of the clothing modification area. The fitting simulation module is used to simulate the fitting of the clothing modification area based on the modification impact area and clothing modification parameters, and obtain the simulated fitting parameters that are qualified for fitting. The scheme determination module is used to adjust the clothing modification parameters operated by the user based on the simulated fitting parameters that have passed the fitting, so as to obtain the clothing design parameters and determine the user's clothing design scheme.

[0015] Compared with the prior art, the computer-aided clothing design method and system of the present invention have the following advantages: This invention acquires user operation information and original clothing parameters, identifies the clothing modification area and parameters, and performs regional structure analysis on the modification area to obtain the area affected by the modification. Based on the area affected by the modification and the modification parameters, a try-on simulation is conducted to obtain qualified simulated try-on parameters, which include the fabric deformation of the modification area and the forces between overlapping fabrics. Finally, the clothing modification parameters are adjusted based on the qualified simulated try-on parameters to obtain the clothing design parameters, thereby determining the user's clothing design scheme. By accurately identifying user operations and comprehensively analyzing the impact of modifications, a realistic try-on simulation is achieved, significantly improving the accuracy and efficiency of complex clothing design, ensuring the accurate reproduction of the natural behavior of the fabric, and avoiding unnatural penetration or stiff deformation. Simultaneously, by optimizing the simulation process, the system's computational load is reduced, effectively alleviating latency and lag, allowing designers to express their creative ideas smoothly, thus ensuring the artistry and originality of complex designs. Attached Figure Description

[0016] To more clearly illustrate the specific embodiments of the present invention, the accompanying drawings used in the specific embodiments will be briefly described below. In all the drawings, the elements or parts are not necessarily drawn to scale.

[0017] Figure 1 This is a flowchart illustrating a computer-aided clothing design method according to the present invention.

[0018] Figure 2 This is a schematic diagram of the structure of a computer-aided clothing design system according to the present invention.

[0019] In the diagram: 210, Information Acquisition Module; 220, Area Identification Module; 230, Area Analysis Module; 240, Fitting Simulation Module; 250, Scheme Determination Module.

[0020] The implementation and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0021] The following drawings disclose several embodiments of the present invention. For clarity, many practical details will be described in the following description. However, it should be understood that these practical details are not intended to limit the invention. That is, in some embodiments of the invention, these practical details are not essential. Furthermore, for the sake of simplicity, some conventional structures and components will be shown in the drawings in a simple schematic manner.

[0022] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0023] Furthermore, in this invention, the use of terms such as "first" and "second" is for descriptive purposes only and does not specifically refer to any order or sequence, nor is it intended to limit the invention. They are merely used to distinguish components or operations described using the same technical terms, and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but only if they are feasible for those skilled in the art. If a combination of technical solutions is contradictory or impossible to implement, such a combination should be considered nonexistent and not within the scope of protection claimed by this invention.

[0024] To further understand the content, features, and effects of this invention, the following embodiments are provided, and detailed descriptions are given below in conjunction with the accompanying drawings: Please see Figure 1 This invention provides a computer-aided clothing design method, comprising the following steps: S100. Obtain all operation information and original garment parameters performed by the user on the computer-aided design interface. The computer-aided design interface is a graphical user interface, typically running on a computer device, allowing designers to interact with design software using input devices such as a mouse, keyboard, and graphics tablet to perform operations such as drawing garment patterns and adjusting 3D models. Operation information refers to all interactive behavior data performed by the user on the computer-aided design interface, such as mouse clicks, dragging paths, and keyboard input. Original garment parameters refer to the initial design data of the garment before any modifications, including but not limited to the garment's size, pattern, fabric type, texture, and color. Specifically, all mouse clicks, drags, zooms, and rotations performed by the user on the design interface, as well as keyboard input data, can be recorded in real time. Original operation data can be stored in a log file with timestamps for later analysis. Original garment parameters can be loaded from a preset garment template library or manually entered and defined by the designer at the start of the project. For example, the designer selects a basic dress template and sets its initial size to medium and the fabric to cotton-linen to constitute the garment's original parameters.

[0025] S200. Based on all the operation information and the original clothing parameters, identify the clothing modification area and clothing modification parameters operated by the user. The clothing modification area refers to a specific area where the user makes local adjustments to the clothing during the design process, such as the collar, cuffs, and hem. Clothing modification parameters refer to the specific adjustment values ​​made to the clothing modification area, such as size increases / decreases, shape changes, and fabric replacements. Specifically, coordinate changes and interactive objects in the user operation information can be analyzed. For example, if the user drags a vertex or edge on the clothing 3D model, based on the operation information and the geometric structure defined in the original clothing parameters, determine which part of the clothing was manipulated, such as the cuffs or collar, and identify the dragging distance and angle changes as clothing modification parameters.

[0026] S300. Perform a regional structure analysis on the clothing modification area operated by the user to obtain the modification-affected area. Specifically, the geometric topology of the clothing modification area operated by the user can be analyzed. For example, if the user modifies the waist area of ​​the clothing, analyze the connection relationship between the waist area and the adjacent chest and hip areas, as well as the fabric properties of the waist area. Through analysis, the actual area of ​​the user-operated area can be determined, and the range that may affect the surrounding unmodified areas due to the modification can be identified. For example, tightening the waist may cause wrinkles or stretching in the chest or hips, and the affected area constitutes part of the modification-affected area.

[0027] S400. Based on the modification influence area and modification parameters of the garment modification area, a virtual try-on simulation is performed on the garment modification area to obtain qualified simulated try-on parameters. These simulated try-on parameters include the fabric deformation of the modification area and the forces between overlapping fabrics. These simulated try-on parameters are data generated during the virtual try-on process based on the results of a physical simulation, used to evaluate the wearing effect of the modified garment, including fabric deformation, wrinkles, drape under gravity, and the interaction forces between different fabric layers. Specifically, a physical simulation engine is used, with the modification influence area and modification parameters of the garment modification area as input, to perform a virtual try-on. For example, if the designer tightens the cuffs by 2 cm, the simulation calculates the fabric deformation, wrinkles, and forces between fabric layers after tightening. During the simulation, a series of simulated try-on parameters are generated, including the fabric deformation of the modification area and the forces between overlapping fabrics, to evaluate the realistic effect of the modified garment when worn.

[0028] S500. Based on the simulated fitting parameters that indicate the fitting was successful, adjust the clothing modification parameters operated by the user to obtain clothing design parameters, thereby determining the user's clothing design scheme. Specifically, based on the results of the fitting simulation, optimize and adjust the clothing modification parameters initially input by the user. For example, if the simulation results show that tightening the cuffs by 2 cm will cause excessive stretching of the fabric or unnatural wrinkles, it is recommended to adjust the tightening amount to 1.5 cm, or change the fabric's elasticity parameters to achieve a more natural wearing effect. After multiple iterations and optimizations, a set of clothing design parameters is finally determined to represent the validated and optimized clothing design scheme.

[0029] In this embodiment, the designer's initial modification intentions are transformed into quantifiable design parameters, which are then verified and optimized through physical simulation to ultimately generate a high-quality clothing design scheme. First, all actions performed by the designer on the computer-aided design interface are captured in real time. This operational information is combined with the original clothing parameters to accurately identify the clothing area the designer wants to modify and its specific modification parameters. This ensures an accurate understanding of the designer's intentions. Next, an in-depth structural analysis of the modified clothing area is performed, considering not only the areas directly manipulated by the user but also identifying the potential chain reactions that local modifications may have on surrounding unmodified areas, thus obtaining a more comprehensive area of ​​influence. For example, when the designer adjusts the shape of the collar, the connection between the collar and the shoulder and chest, as well as the physical properties of the fabric, are analyzed to predict possible wrinkles or stretching in the shoulder and chest, all of which are included in the area of ​​influence. Subsequently, a high-precision virtual try-on simulation is conducted using the area of ​​influence and the modification parameters set by the designer. During the simulation, various physical factors such as fabric elasticity, gravity, and friction are considered to calculate simulation try-on parameters such as the fabric deformation in the modified area and the forces between overlapping fabrics. This invention is used to evaluate the wearing effect of clothing, realistically reflecting the shape and comfort of clothing when actually worn. For example, if the simulation shows excessive fabric deformation, it may mean the clothing is too tight; if the forces between overlapping fabrics are abnormal, it may lead to discomfort. Finally, based on the simulated fitting parameters, the clothing modification parameters initially input by the designer are intelligently adjusted and optimized. If the simulation results are unsatisfactory, it is recommended to modify the parameters until the fitting standard is met. Through iterative optimization, a set of validated clothing design parameters is finally determined, thus forming the final clothing design scheme. This invention simulates the fitting of the clothing modification area based on the modification impact area and the clothing modification parameters, and obtains the simulated fitting parameters that are qualified for fitting. It not only considers the fabric deformation, but also focuses on the forces between overlapping fabrics, making the simulation more realistic and precise. It can effectively avoid unnatural phenomena such as fabric penetration and stiffness. By adjusting the clothing modification parameters operated by the user through the simulated fitting parameters that are qualified for fitting, the clothing design parameters are obtained to determine the user's clothing design scheme. This greatly reduces the workload of designers in manual adjustments and improves design efficiency and accuracy. Ensuring that the final clothing design not only aligns with the designer's vision but is also physically sound and comfortable to wear significantly improves the quality and efficiency of complex clothing design.

[0030] In some embodiments of this application described above, the step of identifying the clothing modification area and clothing modification parameters operated by the user based on all the operation information and the original clothing parameters includes: Information recognition is performed on all the operation information to obtain each operation parameter. Specifically, operation parameters include mouse click position, drag trajectory, keyboard input, and gesture recognition, etc., with the aim of converting continuous or discrete user behavior into structured data that can be processed by the system.

[0031] Each operational parameter is compared with the original parameters of the garment to determine the garment modification parameters. This step is to accurately identify the specific modifications the user intends to make to the garment. The original parameters of the garment include the initial design data, such as size, shape, fabric type, texture, and color. By comparison, it can be determined whether the original parameters have been changed by the user's operation, thereby determining the garment modification parameters. For example, if the user drags an edge of the garment, the size or shape of that edge is identified as changing, and these changes are used as garment modification parameters.

[0032] Based on the original parameters of the clothing, region analysis is performed on each operation parameter to identify the clothing modification area modified by the user. Specifically, region analysis can utilize the geometric model and topological structure of the clothing to map the user operation parameters to specific parts of the clothing. For example, if the user performs an operation on the cuff area of ​​the clothing, based on the definition of cuff in the original parameters of the clothing and combined with the location information of the operation parameters, the cuff area is identified as the clothing modification area. This step ensures the locality and accuracy of the modification, avoiding unnecessary global processing.

[0033] This invention, by identifying all operational information, transforms raw and fragmented user interaction data into structured operational parameters, laying the foundation for subsequent analysis. Secondly, by precisely comparing the operational parameters with the original clothing parameters, the modifications made by the user can be accurately quantified, thereby determining the specific clothing modification parameters. Finally, by combining the original clothing parameters with regional analysis of each operational parameter, the area of ​​clothing modification affected by the user's actions can be accurately located. This allows for a clearer and more accurate understanding of the user's design intent, providing reliable input for subsequent clothing design adjustments and simulations.

[0034] In some embodiments of this application described above, the step of identifying all the operation information to obtain each operation parameter includes: Positional analysis is performed on all the operation information to obtain the position coordinates of each operation. This step involves tracking the movement trajectory of the user's cursor, touch point, or other input device on the computer-aided design interface, recording and analyzing its coordinate changes in two-dimensional or three-dimensional space. This allows us to obtain the precise position coordinates of each operation on the interface. For example, when a user drags a clothing element, the position coordinates of its starting point, path points, and ending points are all recorded.

[0035] All the operation information is analyzed to obtain the action information for each operation. This step identifies the type and nature of user input behavior, including but not limited to clicks, drags, zooms, rotations, and selections. By analyzing the key states, movement speed, directional changes, and duration of the input device, the specific action information for each operation can be obtained. For example, a long press and move might be identified as a drag action, while a short click might be identified as a selection action.

[0036] Based on the position coordinates and action information of each operation, each operation parameter is determined. This step involves associating and integrating the analyzed position and action information. For example, if a dragging action (action information) occurs in the cuff area of ​​the clothing model (position coordinates), then an operation parameter for cuff dragging can be determined. The purpose is to transform discrete user actions into structured data with clear semantics and scope, providing accurate input for subsequent clothing modification area and parameter identification.

[0037] This invention decomposes complex user actions on a computer-aided design interface into quantifiable position coordinates and identifiable action information, and further integrates these two elements to systematically and accurately determine each operation parameter. Through this decomposition and integration mechanism, semantically clear operation units can be extracted from the raw and continuous user input stream, avoiding the ambiguity and inaccuracy that may exist in directly identifying parameters from raw operation information. By independently analyzing and then synthesizing position and action, accurate capture of user intent is ensured, laying a solid foundation for subsequent clothing modification recognition.

[0038] In some embodiments of this application described above, the step of determining each operation parameter based on the position coordinates of each operation and the action information of each operation includes: The position coordinates and action information of each operation are correlated to obtain the correlation information for each operation. This step involves matching and integrating the spatial location data generated by each user operation on the computer-aided design interface with the action data over time. For example, a mouse click action is accompanied by specific screen coordinates, while a drag action includes a series of consecutive coordinate points and corresponding key presses or release actions. Through correlation processing, it can be ensured that the generation of each operation parameter is based on complete and mutually corresponding position and action data.

[0039] The associated information for each operation is verified to obtain the operation parameters that pass the verification. This step involves checking the consistency, completeness, and validity of the associated location and action data. For example, it checks for isolated location data without corresponding actions, action data without corresponding locations, or whether the location data is within the valid operation range. The purpose is to filter out reliable operation data and avoid errors in subsequent parameter identification due to data quality issues.

[0040] If the information verification fails, the position coordinates and action information of each operation are re-associated, and an alarm is issued. Specifically, the re-association process may attempt to use different matching algorithms or fault-tolerance mechanisms to repair or reinterpret the original data to some extent. The purpose of issuing the alarm is to promptly inform the user or system administrator of data anomalies so that manual intervention or adjustment of the input method can be carried out, thereby ensuring that each operation parameter after the final information verification is accurate and reliable.

[0041] Specifically, when a user attempts to drag a clothing component to adjust its position on a computer-aided design interface, under normal circumstances, the mouse movement trajectory (position coordinates) and the left mouse button press state (action information) are continuously acquired. However, due to network latency or device malfunction, at a certain point in time, only the mouse position coordinates are recorded, without recording the left mouse button press action information, or vice versa. In this case, these scattered position coordinates and action information are first correlated. For example, an attempt is made to match consecutive position coordinates with the most recent mouse press and release actions. If a match is successful, the corresponding correlation information is generated. Subsequently, this correlation information is validated. For example, if the validation finds that a mouse press action occurred at the start of a drag operation, but no corresponding mouse release action occurred at the end, or if there is an unreasonable speed change during the drag, the information validation will be deemed unqualified. Once the validation fails, the operation parameters will not be directly generated; instead, the original position coordinates and action information will be re-adjusted, possibly using more lenient matching rules or a backtracking mechanism. Simultaneously, an alarm is immediately issued, such as a pop-up dialog box on the interface indicating that abnormal operation data has been detected, requesting users to check their input or retry, or a detailed error message is recorded in the log. Users can choose to re-operate based on the prompts, or, after re-processing, if a reasonable result is obtained, continue with subsequent steps, but the operation parameter will be marked as corrected. This method ensures that even in the event of abnormal input, accurate operation parameters are obtained as much as possible, or that users are promptly alerted to intervene, thereby guaranteeing the smoothness of the clothing design process and the reliability of the results.

[0042] This invention ensures that the position coordinates and action information of each operation are correctly matched and integrated through association processing, forming logically complete operation association information. Secondly, the information verification step performs rigorous quality checks on this association information, enabling the timely detection and elimination of potential errors or abnormal data. This makes the subsequently generated operation parameters more accurate and reliable. Furthermore, when verification fails, re-association processing can be performed and an alarm can be issued, providing not only an opportunity for error correction but also enhancing the system's robustness and preventing the failure of the entire design process or the generation of inaccurate design results due to underlying data issues.

[0043] In some embodiments of this application described above, the step of performing regional structure analysis on the clothing modification area operated by the user to obtain the modification influence area of ​​the clothing modification area includes: A regional structure analysis is performed on the user-operated clothing modification area to determine the user-operated area and modification elements. These modification elements include the seam relationship between the modified and unmodified areas and the fabric properties of the modified area. Specifically, the user-operated area of ​​the clothing modification area is determined; this area refers to the actual geometric dimensions of the area where the user directly performs modifications on the computer-aided design interface. Simultaneously, modification elements related to the modification area are identified; these elements are key factors affecting the overall structure and appearance of the clothing. The seam relationship between the modified and unmodified areas refers to the structural connection method between the modified area and other parts of the clothing, such as sewing, bonding, or other connection methods, as well as the strength and elasticity of these connections. The fabric properties include the material, thickness, elasticity, drape, texture, and other physical and visual characteristics of the fabric used in the modification area.

[0044] Based on the modified elements, the affected area of ​​the unmodified region is identified. Specifically, the affected area of ​​the unmodified region refers to the clothing portion indirectly affected by changes to the modified region, even though the user did not directly manipulate it. For example, when the fabric properties of the modified region change or the seam relationships are adjusted, adjacent unmodified regions may experience wrinkles, stretching, or deformation, thus creating an affected area. By analyzing the modified elements, the scope and extent of these indirect effects can be accurately simulated and predicted.

[0045] The modification impact area of ​​the clothing modification area is obtained by comparing the user's operation area in the clothing modification area with the impact area of ​​the unmodified area. Specifically, the modification impact area is a more comprehensive and accurate evaluation indicator, as it not only includes the area directly operated by the user but also covers the surrounding areas indirectly affected by the operation, providing a more realistic and complete data foundation for subsequent try-on simulations.

[0046] This invention refines the structural analysis of clothing modification areas by identifying the user's operational area, the modified elements, and the affected area of ​​the unmodified area. This allows for a more comprehensive capture of the structural and visual changes brought about by clothing modifications. Previous analyses might only focus on the area directly manipulated by the user, neglecting the potential impact of modifications on surrounding areas. By introducing modified elements (such as seam relationships and fabric properties) as analytical basis, a deeper understanding of the physical and mechanical coupling relationship between the modified and unmodified areas can be achieved. Indirect effects such as wrinkles, stretching, or deformation in the unmodified area can be accurately identified and quantified. This comprehensive regional structural analysis method ensures that the input data for subsequent try-on simulations is closer to reality, thereby improving the accuracy and reliability of the simulation results.

[0047] In some embodiments of this application described above, the step of identifying the affected area of ​​the unmodified region based on the modified element includes: Based on the modified elements, the wrinkle area and deformation area resulting from the compression effect of the modified area on the unmodified area are determined. Specifically, the modified elements are a set of parameters describing the seam relationship at the connection between the modified and unmodified areas and the fabric properties of the modified area. Based on the modified elements, the physical effects of the modified area on adjacent unmodified areas can be further analyzed. The wrinkle area refers to the area formed by the stacking and folding of fabric in adjacent unmodified areas due to the contraction or expansion of the modified area. For example, when the cuff is tightened, the fabric at the connection between the sleeve and the cuff may wrinkle. The deformation area refers to the area formed by the stretching and twisting of fabric in adjacent unmodified areas due to the stretching or compression of the modified area. For example, when the waist is enlarged, the fabric around the waist may be stretched. The wrinkle area and deformation area can be determined in various ways. For example, a physics simulation engine can be used to calculate the deformation of the fabric under stress based on physical properties such as the elastic modulus and Poisson's ratio of the fabric, as well as the geometric changes of the modified area, thereby quantifying the area of ​​the wrinkle and deformation areas. In addition, it is possible to predict possible wrinkles and deformation patterns and estimate their area by using a preset rule base or machine learning model, based on different modified elements and clothing structures.

[0048] Using the wrinkle area and deformation area, the influence area of ​​the unmodified area is identified and processed to obtain the influence area of ​​the unmodified area.

[0049] Specifically, when a user tightens the cuffs of a shirt on a computer-aided design interface, the process begins by identifying the cuff as a garment modification area and determining its modification parameters, such as the degree of tightening. Next, during the area structure analysis of the user-manipulated modification area, modification elements are determined based on the seam relationship between the cuff and the sleeve body, as well as the properties of the shirt fabric, such as the softness and elasticity of cotton. Specifically, to identify the unmodified area, i.e., the affected area of ​​the sleeve body, the compression effect on the sleeve body fabric when the cuff is tightened is simulated based on the modification elements. For example, when the cuff is tightened, fabric stacking may occur at the cuff-sleeve body connection, forming wrinkles; the area of ​​these wrinkles is calculated. Simultaneously, the fabric near the cuff may be slightly stretched or compressed, causing deformation; the area of ​​this deformation is calculated. By comprehensively considering these wrinkle and deformation areas, the actual impact range of the cuff modification on the entire sleeve body area can be more accurately identified, rather than simply the geometrically adjacent area. Therefore, the area affected by the unmodified region will more realistically reflect the physical changes that may occur when clothing is actually worn.

[0050] This invention, by introducing the concepts of wrinkle area and deformation area, enables a more precise capture of the physical interaction between modified and unmodified areas. By delving into the physical properties and stress-induced deformation of the fabric, the identification of the affected area is no longer a simple expansion of the region, but a precise calculation based on actual physical effects. By considering the wrinkles and deformations caused by compression, the identification of the affected area of ​​the unmodified region more closely reflects the actual wearing effect of the garment, thus providing more realistic basic data for subsequent fitting simulations.

[0051] In some embodiments of this application described above, the step of obtaining the modification influence area of ​​the clothing modification area based on the user operation area of ​​the clothing modification area and the influence area of ​​the unmodified area includes: Based on the user's operational area and the affected area of ​​the unmodified area, the original area of ​​the clothing modification impact is determined. This step involves logically merging or superimposing these two areas after initially identifying or calculating the area of ​​the user's operational area and the affected area of ​​the unmodified area, thus forming the total area of ​​the modification impact area before refined processing. This original area may include irregular boundaries, minor voids, or redundant parts resulting from data collection or preliminary algorithm identification.

[0052] The original area affected by the clothing modification is denoised to obtain the denoised original area affected by the modification. This step involves applying various digital image processing or geometric processing algorithms to eliminate random errors, spikes, or discontinuities in the original area. For example, smoothing filters, morphological operations (such as opening and closing operations), or threshold-based denoising methods can be used to remove tiny regions or isolated points that are not within the actual modification area, thus making the area boundaries smoother and clearer. The aim is to improve the accuracy and stability of subsequent processing.

[0053] The original area affected by the denoised modification is then subjected to area correction processing to obtain the area affected by the modification of the clothing area. Specifically, this step involves further optimizing and adjusting the geometry, boundary accuracy, or matching degree with the actual physical model of the area based on the denoised data. For example, based on preset clothing structure rules, fabric physical properties, or design specifications, the denoised area can be fitted to boundaries, its shape regularized, or precisely aligned with adjacent areas. The aim is to ensure that the final area affected by the modification is not only smooth and noise-free, but also highly reasonable and accurate geometrically and physically, providing reliable input for subsequent fitting simulations.

[0054] Specifically, when a user zooms in on the cuff area of ​​a shirt on a computer-aided design interface, the system first identifies the area of ​​user interaction based on the user's movement and the original cuff size. Then, considering the seam relationship between the cuff and sleeve and the fabric properties, the affected area of ​​the sleeve is identified. Superimposing these two areas yields the original area of ​​the modification's impact. However, due to the precision of the user's operation or minor errors in system recognition, the boundaries of this original area may contain jagged or discontinuous regions. Therefore, the original area of ​​the modification's impact is denoised. For example, a median filtering algorithm can be used to smooth the area boundaries, removing tiny protrusions or depressions with widths less than a specific threshold, resulting in a smoother and more continuous denoised original area of ​​the modification's impact. Furthermore, to ensure the accuracy of the area, area correction processing is performed on the denoised original area of ​​the modification's impact. For example, if the area affected by modifications in the cuff region still exhibits slight distortion after denoising, the system can perform geometric fitting and correction on this area based on a preset circular or elliptical cuff standard template, making it more consistent with the standard cuff shape while maintaining consistency with the user's operational intent. Consequently, the final area affected by modifications to the garment will be more accurate and realistic, providing a high-quality data foundation for subsequent try-on simulations.

[0055] This invention effectively solves the problems of insufficient accuracy and poor robustness that may exist in the initial calculation of the modification impact area of ​​clothing modifications by introducing methods such as determining the original area of ​​modification impact, denoising, and area correction. First, determining the original area of ​​modification impact provides a comprehensive foundation for subsequent refined processing. Second, denoising filters out interference information introduced by data acquisition or initial identification errors in the original area, making the area outline clearer and avoiding the negative impact of unnecessary details on subsequent calculations. Finally, area correction further optimizes the denoised area based on the inherent logic and physical constraints of the clothing design, ensuring that the final modification impact area is more geometrically and physically consistent with reality. This makes the calculation results of the modification impact area more accurate and reliable.

[0056] In some embodiments of this application described above, the step of performing a fitting simulation on the clothing modification area based on the modification impact area and clothing modification parameters to obtain qualified simulated fitting parameters includes: Based on the clothing modification parameters, a try-on simulation is performed on the area affected by the modification of the clothing, resulting in a try-on rendering image. Specifically, the try-on rendering image is a visual image, created using computer graphics technology, simulating the clothing being worn on a virtual model after considering its modification area and the clothing modification parameters. This image intuitively demonstrates the appearance and shape of the modified clothing when actually worn. The clothing modification parameters may include, but are not limited to, size adjustments, fabric type, texture, color, and cutting methods, defining the user's specific modification intentions. The modification area affected by the clothing modification refers to the sum of the area modified by the user and the surrounding areas affected by the modification, ensuring the comprehensiveness and accuracy of the try-on simulation.

[0057] The similarity comparison value is obtained by comparing the rendered image of the try-on with a preset rendered image. The preset rendered image refers to a reference image generated during the clothing design process based on preset design standards, aesthetic requirements, or specific wearing effects. This image can serve as a benchmark for evaluating the results of the try-on simulation; for example, it can be an image of clothing that ideally conforms to design specifications. The similarity comparison quantifies the visual differences between the rendered image of the try-on and the preset rendered image through image processing and analysis algorithms. For example, methods such as pixel-level comparison, feature point matching, and structural similarity index can be used to calculate the similarity. The similarity comparison value is a numerical value representing the degree of similarity between the two images. Generally, a higher similarity comparison value means that the rendered image of the try-on is closer to the preset rendered image, i.e., the try-on effect is more in line with expectations.

[0058] Based on the similarity comparison value, a qualified virtual try-on rendering image is determined. Determining a qualified virtual try-on rendering image typically involves setting a similarity threshold. When the similarity comparison value reaches or exceeds this threshold, the virtual try-on rendering image is considered qualified, indicating that the try-on effect in the clothing modification area meets the design requirements.

[0059] Based on the simulated fitting rendering image that has passed the fitting simulation, the simulated fitting parameters that have passed the fitting simulation are obtained. Specifically, the simulated fitting parameters that have passed the fitting simulation are extracted or derived from the qualified fitting rendering image, and can accurately describe the fabric deformation and the interaction force between overlapping fabrics in the clothing modification area under the qualified fitting state.

[0060] This invention ensures the objectivity and accuracy of the fitting results by refining the fitting simulation process of clothing modification areas into multiple stages, including rendering, comparison, evaluation, and parameter extraction. Specifically, firstly, based on the clothing modification parameters input by the user and the area affected by the modification, a visual fitting rendering image is generated, intuitively presenting the effect of the modified clothing. Secondly, by comparing the similarity of this fitting rendering image with a preset rendering image, the degree of conformity between the fitting effect and the design expectations is quantitatively evaluated. When the similarity comparison value reaches a preset standard, the fitting simulation is considered qualified, thus determining the fitting rendering image that meets the design requirements. Finally, precise simulation fitting parameters are extracted from these qualified rendering images, providing a reliable basis for subsequent adjustments to clothing design parameters.

[0061] In some embodiments of this application described above, the step of obtaining all operation information and original clothing parameters performed by the user on the computer-aided design interface includes: Acquire all raw information about user actions on the computer-aided design (CAD) interface. This step involves directly capturing raw, unprocessed user interaction data from the CAD interface, such as mouse movements, click events, keyboard inputs, or stylus strokes. The raw information may include subtle jitters, uncertainties, or unintentional actions generated by the user during the operation.

[0062] Analyze the speed, direction changes, and dwell time in all the raw information of the operations. This step identifies characteristic patterns in user operations. Speed ​​refers to the distance the user's input device (such as a mouse or stylus) moves per unit time; direction change refers to the instantaneous change in the direction of the movement trajectory; dwell time refers to the duration for which the user maintains an operation at a certain position or area. Combined analysis of these parameters helps distinguish between conscious, deliberate user actions and unconscious noise. For example, rapid and directionally stable movement often indicates drawing or selection, while frequent and small-amplitude directional changes may indicate hand tremors.

[0063] Based on the speed, direction changes, and dwell time in all the original operation information, an operation error coefficient is determined for each operation segment. The operation error coefficient is a quantitative indicator used to assess the noise level or unintended nature of each operation segment. For example, when the speed is too low, the direction changes are frequent, or the dwell time is unusually short or too long, the corresponding operation error coefficient will be set to a higher value, indicating that the operation segment may contain more noise.

[0064] By utilizing the operation error coefficient of each operation information, denoising is performed on all original operation information to obtain all operation information. Specifically, denoising can be implemented using various algorithms, such as smoothing filtering, median filtering, Kalman filtering, or threshold-based filtering. Denoising effectively removes inaccurate or unnecessary components from the original operation information, thereby obtaining more accurate operation information that better reflects the user's true intent, providing high-quality input for subsequent identification of clothing modification areas and parameters.

[0065] Specifically, when a user is drawing the cuff curve of a dress on a computer-aided design interface, slight hand tremors during mouse or stylus drawing may result in small, unintentional jagged or irregular path points in the original mouse trajectory. This constitutes all the raw operation information. By acquiring and analyzing this raw operation information in real time, for example, it can be detected that within a very short timeframe, the mouse speed changes frequently and its direction undergoes multiple small but abrupt changes, with extremely short dwell times. Based on these characteristics, an operation error coefficient for the operation information within that timeframe is derived and set to a high value. Next, this operation error coefficient is used to denoise this segment of raw operation information. For example, a smoothing filter algorithm is applied to smooth these jagged path points, resulting in a smoother cuff curve that better reflects the user's true intentions—this is the denoised operation information. This high-quality input data will then be used for subsequent identification of garment modification areas (cuffs) and garment modification parameters (curve shape), ensuring the accuracy of the design results.

[0066] This invention effectively solves the noise problem that may exist in traditional methods of directly acquiring operation information by introducing a refined analysis and denoising mechanism for the raw user operation information. Specifically, it first acquires all unprocessed raw operation information to ensure that all user interaction data is captured. Then, through in-depth analysis of the speed, direction changes, and dwell time of the raw information, potential noise features in user operations can be identified, such as uneven trajectories caused by hand tremors and brief clicks or unintentional pauses caused by accidental touches. Based on these analysis results, an operation error coefficient is determined for each operation information segment, which intuitively reflects the reliability or noise level of that segment. Finally, the operation error coefficient is used to perform targeted denoising processing on all raw operation information, thereby removing inaccurate or interfering parts from the raw data and obtaining clean and accurate operation information. This ensures that the subsequent identification of clothing modification areas and parameters is based on high-quality and highly reliable input data, significantly improving the accuracy and stability of the entire clothing design method.

[0067] For a computer-aided clothing design method based on any of the above embodiments, please refer to [link / reference]. Figure 2 The present invention also provides a computer-aided clothing design system, which includes an information acquisition module 210, an area identification module 220, an area analysis module 230, a fitting simulation module 240, and a scheme determination module 250.

[0068] The information acquisition module 210 is used to acquire all operation information and original parameters of clothing performed by the user on the computer-aided design interface.

[0069] The region identification module 220 is used to identify the clothing modification region and clothing modification parameters operated by the user based on all the operation information and the original clothing parameters.

[0070] The area analysis module 230 is used to perform regional structure analysis on the clothing modification area operated by the user to obtain the modification impact area of ​​the clothing modification area.

[0071] The fitting simulation module 240 is used to perform a fitting simulation on the clothing modification area based on the modification impact area and clothing modification parameters, and obtain the simulated fitting parameters that are qualified for fitting.

[0072] The scheme determination module 250 is used to adjust the clothing modification parameters operated by the user based on the simulated fitting parameters that have passed the fitting, so as to obtain the clothing design parameters and determine the user's clothing design scheme.

[0073] In this embodiment, the information acquisition module 210 captures all user operation information on the design interface in real time and comprehensively, and combines it with the original parameters of the clothing to lay the foundation for accurate identification in the future, avoiding the ambiguity in the understanding of user intent in traditional systems. The collaborative work of the region identification module 220 and the area analysis module 230 enables the system not only to identify the areas directly operated by the user, but also to comprehensively evaluate the chain effect of local modifications on the entire structure and shape of the clothing, thus considering more comprehensive deformation in the simulation stage. The fitting simulation module 240 can perform high-precision fitting simulation based on the modification area of ​​the clothing modification region and the clothing modification parameters, and obtain simulated fitting parameters including fabric deformation and the force between overlapping fabrics. This makes the simulation more realistic and refined, effectively avoiding unnatural phenomena such as fabric penetration and stiffness, and significantly improving the reliability of virtual fitting. Finally, the scheme determination module 250 can intelligently adjust and optimize the clothing modification parameters based on the simulation fitting parameters that have passed the fitting test, greatly reducing the workload of designers in manual adjustments and improving design efficiency and accuracy. This ensures that the final clothing design not only aligns with the designer's vision but is also practical and comfortable to wear, thus significantly improving the quality and efficiency of complex clothing design.

[0074] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the present invention specification.

Claims

1. A computer-aided based fashion design method, characterized by, include: Obtain all operation information and original clothing parameters performed by the user on the computer-aided design interface; Based on all the operation information and the original parameters of the clothing, identify the clothing modification area and clothing modification parameters operated by the user; Perform a region structure analysis on the clothing modification area operated by the user to obtain the area affected by the modification of the clothing modification area; Based on the area affected by the modification of the clothing modification area and the clothing modification parameters, a fitting simulation is performed on the clothing modification area to obtain the simulated fitting parameters that are qualified for fitting; wherein, the simulated fitting parameters include the fabric deformation of the modification area and the interaction force between overlapping fabrics; Based on the simulated fitting parameters that indicate the fitting was successful, the clothing modification parameters operated by the user are adjusted to obtain the clothing design parameters, thereby determining the user's clothing design scheme.

2. The computer-aided based clothing design method according to claim 1, wherein, Based on all the operation information and the original clothing parameters, the steps to identify the clothing modification area and clothing modification parameters operated by the user include: Information identification is performed on all the operation information to obtain each operation parameter; Each of the operation parameters is compared with the original parameters of the clothing to determine the clothing modification parameters; Based on the original parameters of the clothing, perform regional analysis on each operation parameter to identify the clothing modification area operated by the user.

3. The computer-aided clothing design method according to claim 2, characterized in that, The steps for identifying all the operation information to obtain each operation parameter include: Perform positional analysis on all the operation information to obtain the position coordinates of each operation; Perform operation action analysis on all the operation information to obtain the action information for each operation; Each operation parameter is determined based on the position coordinates of each operation and the action information of each operation.

4. The computer-aided clothing design method according to claim 3, characterized in that, The steps for determining each operation parameter based on the position coordinates of each operation and the action information of each operation include: The position coordinates of each operation and the action information of each operation are associated to obtain the association information of each operation; The associated information of each operation is verified to obtain the parameters of each operation after the information verification is qualified; If the information verification fails, the position coordinates of each operation and the action information of each operation will be re-associated and an alarm will be issued.

5. The computer-aided clothing design method according to claim 1, characterized in that, The steps for performing region structure analysis on the clothing modification area operated by the user to obtain the modification impact area include: Perform regional structure analysis on the clothing modification area operated by the user to determine the user operation area and modification elements of the clothing modification area. The modification elements include the seam relationship at the connection between the modified area and the unmodified area and the clothing fabric properties of the modified area. Based on the modified elements, identify the area affected by the unmodified regions; The modification impact area of ​​the clothing modification area is obtained based on the user operation area of ​​the clothing modification area and the impact area of ​​the unmodified area.

6. The computer-aided clothing design method according to claim 5, characterized in that, The step of identifying the affected area of ​​the unmodified region based on the modified element includes: Based on the modified elements, determine the fold area and deformation area that cause the modified area to compress the unmodified area; Using the wrinkle area and deformation area, the influence area of ​​the unmodified area is identified and processed to obtain the influence area of ​​the unmodified area.

7. The computer-aided clothing design method according to claim 5, characterized in that, The steps for obtaining the modification influence area of ​​the clothing modification area based on the user operation area of ​​the clothing modification area and the influence area of ​​the unmodified area include: The original area affected by the modification of the clothing area is determined based on the user's operation area in the clothing modification area and the area affected by the unmodified area. The original area affected by the modification of the clothing area is denoised to obtain the denoised original area affected by the modification. The original area affected by the denoised modification is subjected to area correction processing to obtain the area affected by the modification of the clothing modification area.

8. The computer-aided clothing design method according to claim 1, characterized in that, The steps for performing a fitting simulation on the clothing modification area based on the modification impact area and clothing modification parameters to obtain qualified fitting simulation parameters include: Based on the clothing modification parameters, a try-on simulation is performed on the area affected by the modification of the clothing to obtain a try-on rendering image; The similarity comparison value is obtained by comparing the trial rendering image with the preset rendering image. Based on the similarity comparison value, a qualified fitting simulation rendering image is determined; Based on the simulated fitting rendering image that shows a successful fitting, the simulated fitting parameters are obtained.

9. The computer-aided clothing design method according to claim 1, characterized in that, The step of obtaining all operation information and original parameters of clothing performed by the user on the computer-aided design interface includes the following steps: Obtain all raw information about the user's actions on the computer-aided design interface; Analyze the speed, direction changes, and dwell time in all the original information of the operations; Based on the speed, direction change, and dwell time in all the original operation information, determine the operation error coefficient for each operation information; Using the operation error coefficient of each operation information, noise reduction processing is performed on all original operation information to obtain all operation information.

10. A computer-aided clothing design system, characterized in that, The system includes: The information acquisition module is used to acquire all operation information and original parameters of clothing performed by the user on the computer-aided design interface; The region identification module is used to identify the clothing modification region and clothing modification parameters operated by the user based on all the operation information and the original clothing parameters; The area analysis module is used to perform regional structure analysis on the clothing modification area operated by the user to obtain the area affected by the modification of the clothing modification area. The fitting simulation module is used to simulate the fitting of the clothing modification area based on the modification impact area and clothing modification parameters, and obtain the simulated fitting parameters that are qualified for fitting. The scheme determination module is used to adjust the clothing modification parameters operated by the user based on the simulated fitting parameters that have passed the fitting, so as to obtain the clothing design parameters and determine the user's clothing design scheme.

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