A visual intelligent interaction design system

Abstract

The application relates to the field of intelligent interaction design, and specifically discloses a visual intelligent interaction design system, which comprises a three-dimensional structure design module, an intelligent color matching module, a visual rendering module and an interaction feedback analysis module. The three-dimensional structure design module can process imported or self-defined three-dimensional models, detect and repair topological errors and build a three-dimensional scene basic framework; the intelligent color matching module generates a color matching scheme based on instructions, a rule base or user preferences and displays a contrast view; the visual rendering module renders a three-dimensional scene in real time, collects rendering pipeline load parameters and quality indicators, analyzes a balance point to adjust rendering parameters; and the interaction feedback analysis module records interaction data, compares standard markers to identify out-of-limit nodes and analyzes root causes. Through the cooperation of the multiple modules, the system realizes efficient construction of a three-dimensional scene, intelligent color matching, rendering optimization and improvement of interaction experience, and is suitable for multiple field scenarios that require visual intelligent interaction design.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of intelligent interaction design, and relates to a visual intelligent interaction design system. BACKGROUND

[0002] With the rapid development of information technology, interaction design has been widely penetrated into virtual reality, augmented reality, game development, industrial design, architectural visualization and other fields. However, the existing interaction design system still has some deficiencies in actual use, which restricts the improvement of user experience and the breakthrough of design efficiency.

[0003] On the one hand, the existing interaction design generally adopts fixed parameter configuration when rendering, which cannot optimize rendering parameters and dynamically allocate resources in real time according to the user's demand for rendering quality. When processing high complexity scenes, the memory occupancy rate is too high to easily cause program lag, and reducing the rendering parameters can improve the fluency, but it will lead to image edge blur, incomplete color gamut coverage and other quality problems.

[0004] On the other hand, the interaction delay feedback mechanism of the existing interaction design is weak, which cannot accurately identify the over-limit interaction node and locate the root cause of the over-limit interaction node, and only relies on manual debugging, which is not conducive to targeted optimization. SUMMARY

[0005] In view of the above problems, the present application provides a visual intelligent interaction design system, which realizes the function of intelligent interaction design.

[0006] The technical scheme adopted by the present application to solve its technical problems is: the present application provides a visual intelligent interaction design system, which comprises: a three-dimensional structure design module: recognizing a three-dimensional model file imported by a user or a self-defined three-dimensional model and automatically detecting and repairing model topology errors, generating a three-dimensional scene basic framework containing spatial coordinate relationship.

[0007] An intelligent color matching module: generating a color matching scheme based on user input instructions, a preset color matching rule library or user preferences, and displaying a dynamic color matching scheme comparison view through an interface interaction component.

[0008] A visual rendering module: real-time rendering of a three-dimensional scene, synchronously collecting rendering pipeline load parameters and image quality evaluation indexes, analyzing the balance point of rendering efficiency and quality and adaptively adjusting rendering parameters, wherein the rendering pipeline load parameters include memory occupancy rate, shader execution period and frame synchronization delay, and the image quality evaluation indexes include color gamut coverage rate and edge sharpness value.

[0009] An interaction feedback analysis module: recording the interaction data of click response duration and animation transition delay in user operation, comparing the data with a preset fluency standard and marking over-limit interaction nodes, and performing interaction delay root cause analysis according to the marking result.

[0010] Compared with the prior art, the visual intelligent interaction design system has the following beneficial effects: 1. The color matching scheme is generated based on user input instructions, a pre-configured color matching rule library or user preferences. The cooperation and interaction of the three modes can cover the full-scene color matching requirements from standardized rules to personalized needs, and improve the accuracy of scheme generation and user satisfaction.

[0011] 2. The application can flexibly adapt to the priority according to different application scenarios, maximize the use of existing resources to provide the optimal experience by monitoring the rendering pipeline load parameters and image quality evaluation indexes in real time, analyzing the balance point of rendering efficiency and quality and adaptively adjusting the rendering parameters.

[0012] 3. The application realizes quick positioning and feedback of delay root cause by collecting interactive data of user operation combined with the mapping relationship of interactive nodes and scene components, realizes targeted optimization and avoids traditional trial-and-error modification. BRIEF DESCRIPTION OF DRAWINGS

[0013] In order to more clearly illustrate the technical solutions of the embodiments of the application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0014] Figure 1 The system module connection diagram of the application.

[0015] Figure 2 The system structure diagram of the application.

[0016] Figure 3 The imported model processing unit workflow diagram of the application.

[0017] Figure 4 The self-defined model processing unit workflow diagram of the application. DETAILED DESCRIPTION

[0018] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only some embodiments of the application, not all. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the application.

[0019] Please refer to Figure 1 and Figure 2As shown, the application provides a visual intelligent interaction design system, which comprises a three-dimensional structure design module, an intelligent color matching module, a visual rendering module, and an interaction feedback analysis module.

[0020] The intelligent color matching module is connected with the three-dimensional structure design module and the visual rendering module, and the interaction feedback analysis module is connected with the visual rendering module.

[0021] The three-dimensional structure design module identifies the three-dimensional model file imported by the user or the three-dimensional model customized by the user, and automatically detects and repairs the model topology error to generate a three-dimensional scene basic framework containing spatial coordinate relationships.

[0022] Further, the three-dimensional structure design module comprises an imported model processing unit and a customized model processing unit, as shown in Figure 3 As shown, the specific working process of the imported model processing unit is as follows: A1, model import and identification: after the user selects and uploads the customized three-dimensional model file through the operation interface, the model data is parsed, and the key elements of the model are extracted to clarify the basic structure and characteristics of the model.

[0023] A2, topology error detection: after the model identification is completed, the topology error detection mechanism is automatically started, and the areas or elements with topology errors are marked out through geometric calculation and data comparison algorithms.

[0024] A3, topology error repair: based on the detected topology error, a preset repair algorithm is used for automatic repair.

[0025] A4, establishment of spatial coordinate system: according to the characteristics of the model and the user's settings, the parameters of the coordinate origin, coordinate axis direction and unit length are determined, and a unified spatial coordinate system is established.

[0026] A5, construction of three-dimensional scene basic framework: after the above steps are completed, the three-dimensional scene basic framework containing spatial coordinate relationships is constructed based on the repaired three-dimensional model and combined with the established spatial coordinate system.

[0027] It should be noted that in three-dimensional model design, topology error refers to logical defects in the geometric connection relationship of the model surface or structure, which will cause abnormalities in subsequent applications such as rendering, animation, physical simulation, 3D printing or engineering analysis.

[0028] As a preferred solution, in the topology error repair, for some simple errors such as small gaps or overlapping patches, the system may repair them by adjusting the vertex position, merging similar vertices or patches, etc.; for more complex non-manifold geometry problems, a specific reconstruction algorithm may be used to reconstruct the relevant areas to ensure that the topology structure of the model meets the specifications and provides a good foundation for subsequent processing and rendering.

[0029] As a preferred solution, the specific process of constructing the three-dimensional scene framework is: integrating each part of the model according to its position and posture in the spatial coordinate system to form a preliminary three-dimensional scene framework; at the same time, adding necessary metadata and attribute information to the scene framework, such as the boundary range of the scene, the lighting conditions, the initial position and the view angle of the camera, etc., which will provide basic support for subsequent visualization rendering, interactive operation and other module functions.

[0030] Further, referring to Figure 4 The specific working process of the custom model processing unit is: B1, user modeling behavior capture: analyzing the user multi-modal input obtained by the dual-channel of parameterized modeling and interactive modeling to obtain the sketch contour drawn by the user and identifying the basic geometric features of the sketch contour.

[0031] B2, modeling processing: performing corresponding parameterized modeling processing and interactive modeling processing according to the type of multi-modal input.

[0032] B3, topology structure pre-verification: running incremental error detection in real time during modeling, and providing dynamic repair scheme for detected problems.

[0033] B4, spatial relationship construction: automatically generating a local coordinate system based on the initial modeling plane, establishing an assembly relationship graph through user-defined spatial constraints, implementing a constraint propagation algorithm to solve the optimal solution of the global coordinate system and generating a hierarchical structure, further automatically assigning quality attributes and material distribution optimization to the feature structure according to the basic geometric features.

[0034] B5, dynamic construction of scene framework: sequentially performing real-time spatial indexing, light pre-adaptation, and multi-resolution management to dynamically construct the three-dimensional scene framework.

[0035] It should be noted that the dual recognition and topology repair capability of the three-dimensional structure design module can improve compatibility and flexibility, reduce manual intervention, and improve development efficiency.

[0036] The intelligent color matching module generates a color matching scheme based on user input instructions, a pre-set color matching rule library or user preferences, and displays a dynamic color matching scheme comparison view through an interface interaction component.

[0037] Further, the intelligent color matching module includes a user-defined color matching unit, an automatic color matching unit, and a user preference color matching unit, wherein the specific working process of the user-defined color matching unit is: analyzing and extracting keywords from the user's natural language instructions or parameterized input, and converting them into calculable color parameters in combination with a set color theory knowledge base.

[0038] The color matching combination is automatically generated based on the analysis result, including single color, gradient color, and multi-color matching mode, and the color matching scheme is optimized in combination with a preset industry template.

[0039] As a preferred solution, the keywords are such as "cool tone", "high saturation", and "similar color matching", the color theory knowledge base is such as RGB / HSB color space and color wheel rules, and the color parameters are such as hue range and lightness threshold. In a specific embodiment, the user inputs "generate a blue-purple gradient scheme", and the system analyzes it as a linear gradient with a hue of 240°-270° and a lightness of 40%-70%.

[0040] It should be noted that the core logic of generating a color matching scheme based on user input instructions is to analyze natural language instructions or parameterized inputs and map them to a color model to generate a scheme; the core logic of generating a color matching scheme based on a preset color matching rule base is to call a color combination model of the built-in rule base and quickly match a scheme according to a preset logic; and the core logic of generating a color matching scheme based on user preferences is to train a personalized model through user historical operation data and dynamically generate a scheme that meets the preferences.

[0041] It should be noted that the present application generates a color matching scheme based on user input instructions, a preset color matching rule base, or user preferences. The synergy and interaction of the three modes enable the color matching link to cover full-scene color matching requirements from standardized rules to personalized needs, while improving the accuracy of scheme generation and user satisfaction.

[0042] Further, the specific working process of the automatic color matching unit is to obtain the type of the three-dimensional scene and extract the key element features in the three-dimensional scene, including material properties, lighting conditions, and user-marked visual focus areas.

[0043] According to the key element features of the three-dimensional scene, the three-dimensional scene is compared with the historical case library under the same scene type in the preset color matching rule base in terms of similarity, candidate color matching schemes are selected from the preset color matching rule base according to the matching degree, a new scheme is generated through a genetic algorithm, the scheme is further sorted and displayed in the user interface according to the visual coordination degree, the user can manually adjust the color value and preview the effect in real time.

[0044] Further, the specific working process of the user preference color matching unit is to obtain user preference data and build a user portrait label according to the user's past selected color matching scheme parameters, interactive behavior, and rating feedback.

[0045] Based on a collaborative filtering algorithm or a deep learning model, the association between the user preference data and the color parameters is analyzed, a color matching scheme is generated, and the user preference data is updated in real time to adjust the color matching scheme.

[0046] As a preferred solution, the color matching scheme parameters such as commonly used primary color RGB value, preferred color tone inclination, etc., the interactive behavior such as the residence time of a certain color matching scheme, the modification frequency, etc., the scoring feedback such as "like" and "dislike" labels, etc., and the user portrait label such as "prefer warm color tone", "commonly used high contrast color matching", etc.

[0047] In one specific embodiment, the user uses red as the primary color and prefers high saturation multiple times, and the system automatically generates a high-contrast scheme with red as the base tone and complementary green.

[0048] It should be noted that the multi-source input advantage of the intelligent color matching module can combine personalization and standardization, reduce decision-making cost, and improve cross-domain applicability.

[0049] The visualization rendering module renders the three-dimensional scene in real time, synchronously collects rendering pipeline load parameters and image quality evaluation indicators, analyzes the balance point of rendering efficiency and quality, and adaptively adjusts the rendering parameters, wherein the rendering pipeline load parameters include video memory occupancy rate, shader execution period, and frame synchronization delay, and the image quality evaluation indicators include color gamut coverage rate and edge sharpness value.

[0050] Further, the specific working process of the visualization rendering module includes monitoring the total amount of video memory occupied by the current rendering task and calculating its proportion in the total available video memory to obtain the video memory occupancy rate.

[0051] In the rendering pipeline, a timestamp query record is inserted to record the number of clock cycles from the start to the end of the shader and convert it to the actual time consumption to obtain the shader execution period.

[0052] During the rendering process, the difference between the time point when the frame is submitted to the GPU and the actual screen refresh time point is calculated to obtain the frame synchronization delay.

[0053] The rendering result is intercepted as bitmap data, and the distribution proportion of pixels in the target color gamut is calculated by the GPU computing shader or CPU-side image processing library to obtain the color gamut coverage rate.

[0054] On the GPU side, the image gradient is calculated in real time through the post-processing channel to generate an edge intensity map, and the average gradient amplitude or peak signal-to-noise ratio of the edge region is calculated to obtain the edge sharpness value.

[0055] It should be noted that the video memory occupancy rate, the shader cycle and the frame synchronization delay are selected as the rendering pipeline load parameters because they are directly related to the GPU resource bottleneck, the calculation efficiency and the picture fluency, which correspond to the storage, the calculation and the output link respectively, forming a closed-loop performance monitoring system; the color gamut coverage and the edge sharpness value are selected as the image quality evaluation indexes because they quantify the color authenticity and the visual clarity, which are the two experience dimensions most sensitive to users, and the two together define the visual fidelity.

[0056] Further, the specific working process of the visualization rendering module further comprises: adjusting the rendering pipeline load parameters in equal gradient according to a set increasing order to obtain multiple sets of rendering pipeline load parameters and corresponding image quality evaluation indexes.

[0057] The multiple sets of rendering pipeline load parameters are substituted into a preset relationship model between the video memory occupancy rate, the shader execution cycle, the frame synchronization delay and the rendering efficiency to obtain multiple sets of data of the rendering efficiency, and the relationship model comprises a quantitative mapping relationship between the video memory occupancy rate, the shader execution cycle, the frame synchronization delay and the rendering efficiency.

[0058] Similarly, the multiple sets of image quality evaluation indexes are substituted into a preset relationship model between the color gamut coverage and the edge sharpness value and the rendering quality to obtain multiple sets of data of the rendering quality.

[0059] Based on the multiple sets of data of the rendering efficiency and the rendering quality, the correlation between the rendering efficiency and the rendering quality is analyzed, the demand value of the rendering quality is substituted into the correlation to obtain the corresponding rendering efficiency and recorded as a balance point of the rendering efficiency and the quality, and the corresponding rendering pipeline load parameters are calculated according to the balance point and then the rendering pipeline load parameters are adjusted.

[0060] It should be noted that the image quality is improved, the video memory occupancy rate is significantly increased, the shader execution cycle is also nonlinearly increased, at the same time, high-quality rendering leads to an increase in single-frame rendering time and then affects the synchronization delay, so that the frame synchronization delay is increased.

[0061] As a preferred solution, the adjustment of the rendering pipeline load parameters will not exceed the corresponding working range.

[0062] It should be noted that the core value of the adaptive adjustment of the rendering parameters based on the efficiency and quality balance point lies in avoiding the "performance excess" or "picture quality deficiency" caused by the fixed parameters, which can flexibly adapt to the priority according to different application scenarios, covers from low-end to high-end hardware, maximizes the use of existing resources to provide the optimal experience; through the data feedback loop, the traditional "static rendering pipeline" is upgraded to an "adaptive rendering ecosystem", and finally the bidirectional optimal solution of efficiency and quality is realized.

[0063] It should be noted that the present application monitors the rendering pipeline load parameter and image quality evaluation index in real time, analyzes the balance point of rendering efficiency and quality and adaptively adjusts the rendering parameter, is beneficial to dynamic resource optimization, avoids performance bottleneck, quantifies balance decision, can flexibly adapt priority according to different application scenes, and maximizes the use of existing resources to provide optimal experience.

[0064] The interaction feedback analysis module records the interaction data of click response duration and animation transition delay in user operation, compares the data with the preset fluency standard and marks the over-limit interaction node, and performs interaction delay root cause analysis according to the marking result.

[0065] Further, the specific working process of the interaction feedback analysis module includes: recording the time stamp of user click occurrence through user click event listening software in the front-end page, then recording the time stamp of the moment when the response action triggered by the click event starts to execute, and obtaining the click response duration in user operation according to the difference between the two time stamps.

[0066] The time stamps of the start of animation and the key transition point are recorded through animation event listening software, and the animation transition delay in user operation is obtained by calculating the time difference between adjacent key frames.

[0067] It should be noted that the click response duration and the animation transition delay are selected as the operation data of user interaction, both of which are core interaction quality indicators, and exceeding the human perception threshold will significantly reduce the satisfaction.

[0068] Further, the specific working process of the interaction feedback analysis module further includes: extracting the fluency standard stored in the database, obtaining the threshold of click response duration and animation transition delay, comparing the interaction data of user operation collected with the above threshold, and if the click response duration or animation transition delay of a certain interaction node exceeds the corresponding threshold, the interaction node is marked as an over-limit interaction node.

[0069] The mapping relationship between the interaction node and the scene component stored in the database and the problem set existing in the running process of each scene component are extracted, the scene component associated with the over-limit interaction node and the problem set existing in the running process of the scene component are matched, and feedback is performed.

[0070] In one specific embodiment, the threshold of click response duration is set to 200 milliseconds, and the threshold of animation transition delay is set to 100 milliseconds.

[0071] As a preferred scheme, the scene component corresponding to each interaction node is associated in the system design stage. The mapping relationship can be recorded through code annotation, configuration file or data structure.

[0072] As a preferred solution, the performance monitoring data and code logs of the binding system are combined to obtain possible problems of the scene component during running.

[0073] In a specific embodiment, if a button click response is timed out, the corresponding scene component is a complex form submission component, which may be caused by complex form verification logic, network request delay or memory leakage, etc.

[0074] As a preferred solution, the operation steps and data of the recorded out-of-limit interaction nodes are further simulated to reproduce the lag problem. The execution process of the scene component is analyzed step by step through the debugging tool to find out the specific code or logic causing the delay.

[0075] It should be noted that the present application realizes rapid positioning and feedback of the delay root cause by collecting the interaction data of user operation in combination with the mapping relationship between the interaction nodes and the scene component, realizes targeted optimization, and avoids traditional trial-and-error modification.

[0076] The above embodiments can be realized wholly or partially by software, hardware, firmware or any combination thereof. When realized by software, the above embodiments can be realized in the form of a computer program product wholly or partially.

[0077] Those skilled in the art can realize that the modules and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solutions. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0078] In addition, the functional modules in each embodiment of the present application can be integrated in one processing module, or each module can exist physically alone, or two or more modules can be integrated in one module.

[0079] The above is merely a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any skilled person in the art can easily think of changes or replacements within the technical range disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0080] Finally, the above is merely a preferred embodiment of the present application and is not used to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A visual intelligent interaction design system, characterized in that, The application relates to a three-dimensional scene design method and device. The three-dimensional structure design module comprises an imported model processing unit and a self-defined model processing unit, wherein the specific working process of the imported model processing unit is as follows: The intelligent color matching module comprises the following steps: The visual rendering module comprises the following steps: The interactive feedback analysis module comprises the following steps: The monitoring of the total GPU memory occupied by the current rendering task and the calculation of the proportion of the total available GPU memory obtain the GPU memory occupancy rate. The rendering process calculates the difference between the time point when the frame is submitted to the GPU and the actual screen refresh time point to obtain the frame synchronization delay. The rendering result is intercepted as bitmap data, and the distribution proportion of pixels in the target color gamut is calculated through the GPU calculation shader or the CPU-side image processing library to obtain the color gamut coverage rate. The rendering pipeline load parameters are adjusted in equal gradient according to the set increasing order to obtain multiple sets of rendering pipeline load parameters and corresponding image quality evaluation indexes. The multiple sets of rendering pipeline load parameters are substituted into a preset relationship model between the GPU memory occupancy rate, the shader execution cycle and the frame synchronization delay and the rendering efficiency to obtain multiple sets of data of the rendering efficiency.

2. The visual intelligent interaction design system of claim 1, wherein: The multiple sets of image quality evaluation indexes are substituted into a preset relationship model between the color gamut coverage rate and the edge sharpness value and the rendering quality to obtain multiple sets of data of the rendering quality. The correlation between the rendering efficiency and the rendering quality is analyzed based on the multiple sets of data of the rendering efficiency and the rendering quality, the demand value of the rendering quality is substituted into the correlation to obtain the corresponding rendering efficiency and is recorded as the balance point of the rendering efficiency and the quality, and the corresponding rendering pipeline load parameters are calculated according to the balance point to adjust the rendering pipeline load parameters. The three-dimensional structure design module comprises an imported model processing unit and a self-defined model processing unit, wherein the specific working process of the imported model processing unit is as follows: A1, model import and recognition: after the user selects and uploads a custom three-dimensional model file through the operation interface, the model data is parsed, and the key elements of the model are extracted to determine the basic structure and features of the model; A2, topology error detection: after the model recognition is completed, the topology error detection mechanism is automatically started, and the areas or elements with topology errors are marked through geometric calculation and data comparison algorithms; A3, topology error repair: based on the detected topology errors, the preset repair algorithm is used for automatic repair; A4, establishment of spatial coordinate system: according to the characteristics of the model and the user's settings, the parameters of the coordinate origin, coordinate axis direction and unit length are determined, and a unified spatial coordinate system is established; A5, construction of three-dimensional scene basic framework: after the above steps are completed, a three-dimensional scene basic framework containing spatial coordinate relationship is constructed based on the repaired three-dimensional model and combined with the established spatial coordinate system.

3. The visual, intelligent interaction design system of claim 2, wherein: The specific working process of the custom model processing unit is: B1, user modeling behavior capture: the user's multi-modal input obtained through the dual-channel of parameterized modeling and interactive modeling is parsed to obtain the sketch contour drawn by the user and identify the basic geometric features of the sketch contour; B2, modeling processing: corresponding parameterized modeling processing and interactive modeling processing are performed according to the type of multi-modal input; B3, topology structure pre-verification: incremental error detection is performed in real time during modeling, and dynamic repair solutions are provided for detected problems; B4, spatial relationship construction: based on the initial modeling plane, a local coordinate system is automatically generated, an assembly relationship diagram is established based on user-defined spatial constraints, a constraint propagation algorithm is used to solve the optimal solution of the global coordinate system and generate a hierarchical structure, and further quality attributes are automatically assigned according to the basic geometric features and material distribution optimization is performed on the feature structure; B5, dynamic construction of scene framework: real-time spatial indexing, light pre-adaptation and multi-resolution management are sequentially performed to dynamically construct a three-dimensional scene framework.

4. The visual, intelligent interaction design system of claim 1, wherein: The intelligent color matching module includes a user-defined color matching unit, an automatic color matching unit, and a user preference color matching unit. The specific working process of the user-defined color matching unit is: The user's natural language instructions or parameterized input are parsed to extract keywords, and combined with the set color theory knowledge base, they are converted into calculable color parameters; Based on the analysis results, color matching combinations are automatically generated, including single color, gradient color and multi-color matching modes, and the color matching scheme is optimized in combination with the preset industry template.

5. The visual, intelligent interaction design system of claim 4, wherein: The specific working process of the automatic color matching unit is: The type of the three-dimensional scene is obtained, and the key element features in the three-dimensional scene are extracted, including material attributes, lighting conditions and user-marked visual focus areas; According to the key element features of the three-dimensional scene, similarity comparison is performed with the historical case library under the same scene type in the preset color matching rule library, candidate color matching schemes are selected from the preset color matching rule library according to the matching degree, and new schemes are generated through genetic algorithm iteration, and the schemes are further sorted and displayed in the user interface according to the visual coordination degree, supporting user manual adjustment of color values and real-time preview of effects.

6. The visual, intelligent, interactive design system of claim 4, wherein: The specific working process of the user preference color matching unit is: According to the color matching scheme parameters, interaction behavior, and score feedback of the user's past choices, user preference data is obtained and a user portrait label is constructed; Based on a collaborative filtering algorithm or a deep learning model, the association between user preference data and color parameters is analyzed, a color matching scheme is generated, and user preference data is updated in real time to adjust the color matching scheme.

7. The visual, intelligent, interactive design system of claim 1, wherein: The specific working process of the interaction feedback analysis module includes: Through user click event monitoring software in the front-end page, the time stamp of the user click occurrence is recorded, then the time stamp of the start of the response action triggered by the click event is recorded, and the click response time in the user operation is obtained according to the difference between the two time stamps; Through animation event monitoring software, the time stamps of the start of the animation and the key transition points are recorded, and the animation transition delay in the user operation is obtained by calculating the time difference between adjacent key frames.

8. The visual, intelligent interaction design system of claim 7, wherein: The specific working process of the interaction feedback analysis module also includes: The smoothness standard stored in the database is extracted, the threshold values of the click response time and the animation transition delay are obtained, the collected interaction data of the user operation is compared with the above threshold values, and if the click response time or the animation transition delay of a certain interaction node exceeds the corresponding threshold value, the interaction node is marked as an out-of-limit interaction node; The mapping relationship between the interaction nodes and the scene components and the problem set existing in the running process of each scene component stored in the database are extracted, the scene components associated with the out-of-limit interaction node and the problem set existing in the running process of the scene components are matched, and feedback is given.

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