A method and system for adaptive adjustment of interface style based on 3D car model

Abstract

This invention relates to the field of human-computer interaction interface management technology, and provides a method and system for adaptive adjustment of interface style based on a 3D car model. It identifies multi-dimensional attribute features such as geographical features, user features, and holiday features in the current scene in real time, and achieves style conversion through style scoring and differentiated adjustments, controlling the adaptive adjustment of the 3D car model's interface style. On the one hand, by integrating user features, geographical features, and holiday features, it achieves dynamic adaptive adjustment of the 3D car model's style, enabling flexible switching between multiple preset base models while balancing personalized expression and rendering efficiency. On the other hand, it differentiates the basic style of the target base model based on multi-dimensional attribute features, performs style conversion through a model style generation engine, and dynamically renders in real time to achieve intelligent repainting of textures that flexibly change with the scene.

Description

Technical Field

[0001] This invention relates to the field of human-computer interaction interface management technology, and in particular to a method and system for adaptive adjustment of interface style based on a 3D car model. Background Technology

[0002] With the rapid development of intelligent vehicle technology, in-vehicle human-machine interface (HMI) systems are gradually evolving from traditional two-dimensional displays to more immersive three-dimensional visualization interfaces. 3D exterior models of automobiles have become core visual elements for conveying brand personality and enhancing user perception and emotional engagement.

[0003] 3D car models play an important role in intelligent cockpit design and autonomous driving. For example: (1) Through multimodal interaction, AI intelligent partners, panoramic 3D vision and other technologies, they provide advanced 3D map rendering, ADAS visualization, spatial atmosphere creation and other functions. (2) They are used for automated data annotation and simulation data generation. Through large model technology, efficient and high-precision data annotation can be achieved, and real road scenes can be restored in virtual space, improving the training effect and safety of autonomous driving systems.

[0004] However, current 3D car models in the industry generally adopt a static and uniform modeling scheme, which cannot respond to environmental variables such as user characteristics, regional culture, and festive atmosphere, resulting in a lack of personalized experience and a fragmented user perception. In addition, the texture mapping of 3D car models is also difficult to change flexibly with the scene, limiting the expression of festivals and culture. Summary of the Invention

[0005] This invention provides a method and system for adaptive adjustment of interface style based on a 3D car model, which solves the technical problem that the existing 3D car model style depends on template library primitive coverage, the interface adjustment display is fixed and cannot be adjusted in real time, resulting in a poor user experience.

[0006] To address the above technical problems, this invention provides a method for adaptive adjustment of interface style based on a 3D car model, comprising:

[0007] Identify the current scene to obtain multi-dimensional attribute features, which include at least one or more of geographical features, user features, and holiday features;

[0008] The preset base model is style-scored based on the multidimensional attribute features, and then a target base model that is suitable for the current scene is determined from the preset base model.

[0009] Based on the aforementioned multidimensional attribute features, the basic style of the target base model is adjusted differentially to achieve style conversion;

[0010] The system renders and outputs a 3D car model based on the target base model after style transfer, and then updates the interface display.

[0011] This basic solution identifies multi-dimensional attribute features such as geographical features, user features, and holiday features in the current scene in real time. It achieves style conversion through style scoring and differentiated adjustments, controlling the adaptive adjustment of the car 3D model in terms of interface style. On the one hand, by integrating user features, geographical features, and holiday features, it achieves dynamic adaptive adjustment of the car 3D model style, and can flexibly switch between multiple preset base models (realistic, Q-style, and low-poly style), taking into account both personalized expression and rendering efficiency. On the other hand, it differentiates the basic style of the target base model based on multi-dimensional attribute features, performs style conversion through the model style generation engine, and dynamically renders in real time to achieve intelligent repainting of textures that change flexibly with the scene (that is, it breaks away from the limitations of template library primitives and truly achieves interface style changes that follow the scene).

[0012] In a further implementation, the current scene is identified to obtain multi-dimensional attribute features, including:

[0013] Identify the driver in the current scene and obtain user characteristics based on the corresponding user preferences;

[0014] Based on the current scenario, vehicle location data is acquired, and local geographical features are obtained based on the vehicle location data.

[0015] Obtain the real-time date and automatically identify holiday characteristics;

[0016] The multidimensional attribute features include user features, geographical features, and the festival features.

[0017] This solution adjusts the 3D model to suit different user characteristics, providing a more personalized and customized experience and enhancing user engagement and satisfaction. Adjusting the 3D model to suit the geographical characteristics of different regions can better meet the cultural preferences of local users, increasing user acceptance and purchase intention for the vehicle model. During specific holidays, adjusting the 3D model to match the holiday theme effectively enhances the festive atmosphere for users.

[0018] In a further implementation scheme, a style score is performed on the preset base model based on the multidimensional attribute features, and then a target base model suitable for the current scene is determined from the preset base model, including:

[0019] Obtain the style fit of each of the multidimensional attribute features to each preset base model;

[0020] Based on the style fit of the multidimensional attribute features, a weighted calculation is performed to determine the style score of each preset base model;

[0021] The preset base model with the highest style score is selected as the target base model to adapt to the current scene.

[0022] In a further implementation, the weighted calculation formula for the style score is as follows:

[0023]

[0024] In the formula: This represents the total score of the i-th preset base model; This represents the degree to which user characteristics fit the preset base model; This represents the degree to which geographical features fit the preset base model; This represents the degree to which the characteristics of the festival fit the preset basic model; , , These represent the weighting coefficients for users, geography, and holidays, respectively, and satisfy the following conditions: .

[0025] This solution uses a weighted calculation of multi-dimensional attribute features to determine the style score of each preset base model. The preset base model with the highest style score is selected as the target base model to adapt to the current scene. The style of the 3D car model is dynamically adjusted based on user preference features, geographical and cultural features, and festival atmosphere features. It integrates multi-dimensional personalized needs with scene adaptation capabilities. By using a multi-feature weighted adjustment strategy, user profiles, spatial context, and time nodes are transformed into design parameters to achieve a personalized experience of "a thousand people, a thousand cars" while controlling costs through a standardized parameter system.

[0026] In a further implementation scheme, based on the multidimensional attribute features, the basic style of the target base model is differentiated and adjusted to achieve style transfer, including:

[0027] Obtain the basic style parameters of the target base model;

[0028] Determine the influence factor of each of the multidimensional attribute features on the target basic model;

[0029] Obtain the influence factors of all the multidimensional attribute features of each target base model, perform weighted calculation to determine the adjustment magnitude, and make differentiated adjustments to the base style parameters according to the adjustment magnitude to achieve style conversion;

[0030] The basic style parameters include the number of facets in the model and the smoothness parameter.

[0031] After determining the target base model that best fits the current scenario through comprehensive multi-dimensional attribute feature matching, this solution further fine-tunes the parameter-level optimization within the selected style framework (i.e., base style parameters) to achieve more refined personalized adaptation of the 3D car model. Through a two-stage dynamic adjustment mechanism, it ensures both the systematic nature of the macro style and the flexibility of the micro parameters, fully meeting personalized needs while effectively balancing user experience and implementation costs.

[0032] In a further implementation scheme, based on the multidimensional attribute features, the basic style of the target base model is differentially adjusted to achieve style transfer, which further includes:

[0033] Festival features are obtained from the multidimensional attribute features, and festival theme textures and festival factors are obtained based on the festival features;

[0034] The base texture is obtained from the base style of the target base model, and the holiday-themed texture is compared with the base texture to determine the texture differences used to perform differential adjustments.

[0035] The texture mapping parameters are determined based on the festival factor and the texture difference, and then mapped and superimposed with the base texture to obtain the target texture to achieve style transfer.

[0036] This solution uses festival-themed textures and festival factors based on festival characteristics to differentiate the base textures of the basic style. It then performs style transformation by overlaying festival textures onto the base textures. While maintaining the stability of the base model, it achieves a strong expression of the festival atmosphere through lightweight dynamic adjustments.

[0037] In a further implementation, the 3D model of the car is rendered and output based on the style-transferred target base model, and the interface is updated and displayed, including:

[0038] Style transfer keywords are generated based on the target texture, and then a texture is generated based on the style transfer keywords and mapped onto the UV area of ​​the vehicle body.

[0039] The Unreal Engine is used to dynamically bind the model parameters of the target base model after style transfer, and the stylized car model is rendered and output in real time. It is then connected to the HMI in-vehicle system to achieve interface update and display.

[0040] This solution achieves limited holiday texture repainting on the vehicle body area by precisely controlling the model's facet count and smoothness, and generating style transfer keywords based on holiday factors, creating an immersive atmosphere. Furthermore, the texture patterns are mapped only to the vehicle body's UV areas, without interfering with functional structural areas, ensuring overall visual harmony and functional safety.

[0041] In a further implementation, the method further includes: after the interface is updated and displayed, detecting user operation data, updating the weight coefficients and influencing factors corresponding to user characteristics based on the user operation data, and performing closed-loop optimization of user feedback.

[0042] This solution establishes a closed-loop optimization logic based on user feedback, providing a real-time update and feedback mechanism to continuously optimize style matching effects and enhance the personalized expression and user-perceived value of the in-vehicle HMI system.

[0043] This invention also provides an interface style adaptive adjustment system based on a 3D car model, comprising:

[0044] Processor and its connected memory and data acquisition module;

[0045] The data acquisition module is used to identify the current scene to obtain multi-dimensional attribute features, which include at least one or more of geographical features, user features, and holiday features.

[0046] The memory stores instructions that the processor can execute;

[0047] When the processor is configured to execute the instructions, it implements the interface style adaptive adjustment method based on a 3D car model as described above.

[0048] In a further implementation, the data acquisition module includes a GPS positioning module, a user information module, and a date processing module;

[0049] The GPS positioning module is used to acquire vehicle location data, obtain climate data of the current area through the weather interface, and identify the human preferences of the current area from the historical database to obtain geographical features.

[0050] The user information module is used to determine user information through facial recognition and to obtain user characteristics by determining the user's personalized preferences based on the user information;

[0051] The date processing module is used to identify whether the current period is a specific holiday by using the built-in calendar and holiday database, and then obtain the holiday characteristics.

[0052] This solution automatically activates the corresponding holiday textures via the system clock / Network Time Protocol (NTP), eliminating the need for manual user intervention. Attached Figure Description

[0053] Figure 1 This is a flowchart of an interface style adaptive adjustment method based on a 3D car model provided in an embodiment of the present invention. Detailed Implementation

[0054] The embodiments of the present invention are described in detail below with reference to the accompanying drawings. The embodiments are given for illustrative purposes only and should not be construed as limiting the present invention. The accompanying drawings are for reference and illustration only and do not constitute a limitation on the scope of patent protection of the present invention, because many changes can be made to the present invention without departing from the spirit and scope of the present invention.

[0055] Example 1

[0056] This invention provides a method for adaptive adjustment of interface style based on a 3D car model, such as... Figure 1 As shown, in this embodiment, steps S1 to S5 are included:

[0057] S1. Identify the current scene to obtain multi-dimensional attribute features, wherein the multi-dimensional attribute features include at least one or more of geographical features, user features, and holiday features;

[0058] In this embodiment, identifying the current scene to obtain multi-dimensional attribute features includes:

[0059] Identify the driver in the current scene and obtain user characteristics based on the corresponding user preferences;

[0060] Based on the current scenario, vehicle location data is acquired, and local geographical features are obtained based on the vehicle location data.

[0061] Obtain the real-time date and automatically identify holiday characteristics;

[0062] The multidimensional attribute features include user features, geographical features, and the festival features.

[0063] User feature recognition includes data collection based on registration information, facial recognition, and vehicle sensors, including age, gender, and driving habits. To ensure user privacy and security, the system strictly adheres to its privacy policy. All user data is encrypted to ensure it cannot be leaked or tampered with during transmission.

[0064] Style preferences based on user characteristics, for example: middle-aged and elderly men prefer realistic styles, young women prefer rounded and cute styles, and young men prefer low-poly styles.

[0065] Geographic feature recognition: Relying on GPS modules to obtain vehicle location data, obtaining climate data of the current area through a weather interface, and identifying the human preferences of the current area from historical databases.

[0066] Style preferences based on geographical characteristics, for example: users in cold regions prefer warm and realistic styles, users in tropical regions prefer transparent and bright cartoon styles, and users in Europe prefer low saturation and minimalist styles.

[0067] Holiday Feature Recognition: Utilizes a built-in calendar and holiday database to identify whether a specific holiday is currently in effect. It automatically identifies and tags holiday features based on the date.

[0068] Style preferences based on the characteristics of the festival, for example: adapting different design styles according to the characteristics of different festivals, such as using a rounded, warm gold realistic style to enhance the sense of reunion for the Mid-Autumn Festival, using a Q version and colorful cartoon style to highlight friendliness for Children's Day, and using a low saturation and low polygon style to reflect simplicity and practicality for Labor Day.

[0069] This embodiment adjusts the 3D model to suit different user characteristics, providing a more personalized and customized experience and enhancing user engagement and satisfaction. Adjusting the 3D model to suit the geographical characteristics of different regions can better meet the cultural preferences of local users, increasing user acceptance and purchase intention for the vehicle model. During specific holidays, adjusting the 3D model to match the holiday theme effectively enhances the user's sense of the festive atmosphere.

[0070] S2. Based on the multi-dimensional attribute features, perform style scoring on the preset base model, and then determine the target base model suitable for the current scene from the preset base model, including:

[0071] S21. Obtain the style fit of each of the multidimensional attribute features to each preset basic model;

[0072] The preset base model can be set to two or more types according to actual needs, such as: realistic style, chibi style and low polygon style.

[0073] S22. Based on the style fit of the multidimensional attribute features, perform a weighted calculation of the style score for each preset basic model;

[0074] In this embodiment, the weighted calculation formula for the style score is as follows:

[0075]

[0076] In the formula: This represents the total score of the i-th preset base model; This represents the degree to which user characteristics fit the preset base model; This represents the degree to which geographical features fit the preset base model; This represents the degree to which the characteristics of the festival fit the preset basic model; , , These represent the weighting coefficients for users, geography, and holidays, respectively, and satisfy the following conditions: .

[0077] S23. Obtain the preset base model with the highest style score and determine it as the target base model that is suitable for the current scene.

[0078] Specifically, the matching relationship between style scores and the preset base model is shown in Table 1 below:

[0079]

[0080] Table 1

[0081] If the largest and second largest difference between the three scores is less than 0.05, an empirical interval is introduced to assist in the judgment and improve the system stability.

[0082] This embodiment calculates the style score of each preset base model by weighting multi-dimensional attribute features. The preset base model with the highest style score is selected as the target base model to adapt to the current scene. The style of the 3D car model is dynamically adjusted by weighting user preference features, geographical and cultural features, and festival atmosphere features. It integrates multi-dimensional personalized needs and scene adaptation capabilities. By using a multi-feature weighted adjustment strategy, user profiles, spatial context, and time nodes are transformed into design parameters to achieve a personalized experience of "a thousand people, a thousand cars" while controlling costs through a standardized parameter system.

[0083] S3. Based on the aforementioned multidimensional attribute features, the basic style of the target base model is adjusted to achieve style transfer, including:

[0084] S31A. Obtain the basic style parameters of the target base model;

[0085] S32A. Determine the influence factor of each of the multidimensional attribute features on the target basic model;

[0086] S33A. Obtain the influence factors of all the multidimensional attribute features of each target base model, perform weighted calculation to determine the adjustment amplitude, and make differentiated adjustments to the base style parameters according to the adjustment amplitude to achieve style conversion;

[0087] The basic style parameters include the number of facets in the model and the smoothness parameter.

[0088] In this embodiment, after determining the target base model that best fits the current scene by comprehensively matching multi-dimensional attribute features, further fine-tuning is performed within the selected style framework (i.e., base style parameters) to optimize parameters at the parameter level, thereby achieving more refined personalized adaptation of the 3D car model. Through a two-stage dynamic adjustment mechanism, the systematic nature of the macro style is ensured, while the flexibility of the micro parameters is realized, fully meeting personalized needs and effectively balancing user experience and implementation costs.

[0089] Also includes:

[0090] S31B. Obtain festival features from the multidimensional attribute features, and obtain festival theme texture and festival factors based on the festival features;

[0091] S32B: Obtain the base texture from the base style of the target base model, compare the holiday theme texture with the base texture, and determine the texture differences used to perform differential adjustments;

[0092] S33B. Determine the texture mapping parameters based on the festival factor and the texture difference, and map and superimpose them with the base texture to obtain the target texture to achieve style conversion.

[0093] This embodiment uses festival-themed textures and festival factors based on festival characteristics to differentiate the base textures of the basic style, and performs style transformation by overlaying festival textures on the base textures. While maintaining the stability of the base model, it achieves a strong expression of the festival atmosphere through lightweight dynamic adjustment.

[0094] In this embodiment, the style transfer includes three dimensions: model polygon count, smoothness, and texture mapping. Using this basic style as the starting point, further differentiated adjustments are performed based on holiday characteristics, geographical features, and user characteristics to achieve the final style refinement as follows:

[0095] (1) Taking the original model as having 3000 faces as an example, adjust the model complexity according to the basic style:

[0096]

[0097] The formula for adjusting the number of faces in a model is as follows:

[0098]

[0099] in, This refers to the adjusted number of faces in the model. The original input model has a total number of faces (assumed to be 3000 faces); weighting coefficients. , , These represent the degree of influence of user characteristics, geographical characteristics, and holiday characteristics on style adjustment, ranging from 0 to 1; , , These represent the influencing factors of user characteristics, geographical characteristics, and holiday characteristics, respectively, ranging from 0 to 1.

[0100] The sum of the weighting coefficients must meet the normalization requirements. .

[0101] (2) The smoothness adjustment formula is as follows:

[0102]

[0103] in, The adjusted smoothness; Smoothness of the original model (set the model to have 3000 faces, smoothness to 5); weighting coefficients. , , These represent the degree of influence of user characteristics, geographical characteristics, and holiday characteristics on style adjustments, respectively. , , These represent the influencing factors of user characteristics, geographical characteristics, and holiday characteristics, respectively, ranging from 0 to 1.

[0104] The sum of the weighting coefficients must meet the normalization requirements. .

[0105]

[0106] The texture mapping area is limited to the vehicle body UV channel, which is achieved by setting a UV map mask or an independent UV channel. Only the holiday pattern is allowed to affect the vehicle body, while maintaining the original materials of the lights, tires, glass, etc.

[0107] The UV channels in this proposal contain the positional coordinates of the texture as it unfolds and adheres to the surface of the 3D model.

[0108] (3) The texture mapping formula is as follows:

[0109]

[0110] in, The adjusted target texture; Set the base texture (to a neutral standard car body texture with light white metallic paint and no holiday-themed patterns). For holiday-themed textures; The festival factor determines the complexity of the festival texture, ranging from 0 to 1. The larger the factor, the more distinct the festival pattern colors and the more complex the design.

[0111] Table 2 below defines the festive atmosphere and textures corresponding to the festival factors:

[0112]

[0113] Table 2

[0114] S4. Render the 3D car model based on the style-transferred target base model and update the interface display, including:

[0115] S41. Generate style transfer keywords based on the target texture, and then generate a texture based on the style transfer keywords and limit the mapping to the UV area of ​​the vehicle body;

[0116] Specifically, style transition keywords are automatically generated using preset templates to create holiday textures, making the textures more closely match the actual "car cover style" requirements. Keyword framework: Prompt = tone description + holiday pattern elements + application method + surface texture + defined area.

[0117] For example:

[0118] The generated prompt text reads: "The main color scheme is pink and purple gradient, with rose, gift box, and heart ribbon patterns. The visual effect is soft and the style is more like a high-end car body paint effect. It is limited to the UV area of ​​the car body and should avoid covering the glass and light areas."

[0119] The generated textures are mapped to the UV area of ​​the vehicle body to ensure that the original materials of lights, glass, etc. are preserved.

[0120] S42. Use the Unreal Engine to dynamically bind the model parameters (i.e., model face count, smoothness, and texture) of the target base model after style conversion, render and output the stylized car model in real time, and connect to the HMI vehicle system to achieve interface update display.

[0121] This embodiment achieves limited holiday texture repainting on the vehicle body area by precisely controlling the model's facet count and smoothness, and generating style transfer keywords based on holiday factors, creating an immersive atmosphere. Furthermore, the texture pattern is mapped only to the vehicle body's UV area, without interfering with functional structural areas, ensuring overall visual harmony and functional safety.

[0122] S5. After the interface is updated and displayed, detect user operation data, update the weight coefficients and influencing factors corresponding to user characteristics based on the user operation data, and perform user feedback closed-loop optimization.

[0123] User operation data includes, but is not limited to, the number of times a user manually switches styles, dwell time, and voice preference settings. By updating feature factors and weights, the accuracy of style recommendations and personalized expression capabilities are continuously improved.

[0124] This embodiment sets up a user feedback closed-loop optimization logic to provide a real-time update and feedback mechanism, which can continuously optimize the style matching effect and enhance the personalized expression and user perceived value of the in-vehicle HMI system.

[0125] In this embodiment, calculations are performed using a specific set of user and scene data to output the style-adjusted model parameters and holiday texture map style. The specific interface style adaptive adjustment process is as follows:

[0126] v1. Input Settings:

[0127] Original model face count: =3000;

[0128] Original smoothness: =5;

[0129] v2. Input conditions: Influencing factors of user characteristics, geographical characteristics, and festival characteristics:

[0130] Current holiday (Valentine's Day): ;

[0131] User characteristics (young women): ;

[0132] Geographical location (tropical region): ;

[0133] Preliminary review weighting coefficient: , , .

[0134] v3, Calculate style scores:

[0135] Using the scoring formula:

[0136]

[0137]

[0138]

[0139]

[0140] The system selects the highest-rated chibi style as the base style.

[0141] v4. Face count adjustment:

[0142]

[0143]

[0144] The model's face count has been adjusted to 2070, which falls within the chibi style range (1200-2400).

[0145] v5, Smoothness Adjustment:

[0146]

[0147]

[0148] The smoothness was adjusted to 3.45, which is consistent with the Q-version style range (3.0-3.9).

[0149] v6, Texture mapping adjustment:

[0150] Based on the above conditions, supplement and condition:

[0151] Current holiday (Valentine's Day): ;

[0152] Holiday textures (Valentine's Day): =Pink gradient + rose pattern;

[0153] Basic textures: =Light white standard car body surface.

[0154]

[0155]

[0156] Calculation result:

[0157] The texture complexity is medium to high, using Valentine's Day exclusive elements such as roses, ribbons, and gifts. The color tone is pinkish-purple, suitable for "car wrap" style and limited to the UV area of ​​the car body.

[0158] v7. Style transfer keyword generation:

[0159] After generating the prompt, the system passes the prompt as input to the image generation module, as follows:

[0160] "The main colors are pink and purple gradient, with rose, gift box and heart ribbon patterns. The visual effect is soft and the style is more like a high-end car body paint effect. It is limited to the UV area of ​​the car body to avoid covering the glass and light areas."

[0161] The resulting 1024x1024 PNG texture map is then processed and applied to the corresponding material channel of the vehicle body UV map.

[0162] v8, Output Binding Phase:

[0163] Using the Unreal Engine Rendering system on the car, the model's UV coordinates are mapped in real time to ensure that textures are applied to the UV areas of the car body while other materials remain unchanged.

[0164] v9. Final output style determination:

[0165] Model face count: 2070, belongs to the chibi style;

[0166] Smoothness: 3.45 indicates a smooth and rounded finish;

[0167] Texture: Pink and purple color scheme + Valentine's Day elements, festive car wrap sticker.

[0168] v10, Result:

[0169] Based on the input features, the system quickly transforms the style, outputs a Q-version style model, and dynamically applies Valentine's Day-themed car cover textures and patterns, limited to the UV area of ​​the car body, ultimately generating a 3D car model appearance that fits the festive atmosphere and meets user preferences.

[0170] This invention identifies multi-dimensional attribute features such as geographical features, user features, and holiday features in the current scene in real time. It achieves style conversion through style scoring and differentiated adjustments, controlling the adaptive adjustment of the car 3D model in terms of interface style. On the one hand, by integrating user features, geographical features, and holiday features, it achieves dynamic adaptive adjustment of the car 3D model style, which can flexibly switch between multiple preset base models (realistic, Q-style, and low-poly style), taking into account both personalized expression and rendering efficiency. On the other hand, it differentiates the basic style of the target base model based on multi-dimensional attribute features, performs style conversion through the model style generation engine, and dynamically renders in real time to achieve intelligent repainting of textures that change flexibly with the scene (i.e., breaking away from the limitations of template library primitives and truly realizing the change of interface style that follows the scene).

[0171] This solution achieves a dynamic reconstruction of 3D model-level styles that interface template technologies cannot cover through multiple dimensions, including parameter-driven modeling adjustment, algorithmic texture generation, rendering binding output, and feedback optimization mechanisms. It binds the style to the engine output in real time, realizing a fundamental breakthrough across dimensions from "visual theme selection" to "model style generation engine".

[0172] Example 2

[0173] This invention also provides an interface style adaptive adjustment system based on a 3D car model, comprising:

[0174] Processor and its connected memory and data acquisition module;

[0175] The data acquisition module is used to identify the current scene to obtain multi-dimensional attribute features, which include at least one or more of geographical features, user features, and holiday features.

[0176] The memory stores instructions that the processor can execute;

[0177] When the processor is configured to execute the instructions, it implements the interface style adaptive adjustment method based on a 3D car model as described above.

[0178] In this embodiment, the data acquisition module includes a GPS positioning module, a user information module, and a date processing module;

[0179] The GPS positioning module is used to acquire vehicle location data, obtain climate data of the current area through the weather interface, and identify the human preferences of the current area from the historical database to obtain geographical features.

[0180] The user information module (e.g., a face recognition module including a camera) is used to determine user information through face recognition (in other embodiments, user information can also be determined based on the user's manual input), and to determine the user's personalized preferences based on the user information to obtain user characteristics;

[0181] The date processing module is used to identify whether the current period is a specific holiday by using the built-in calendar and holiday database, and then obtain the holiday characteristics.

[0182] This embodiment automatically activates the corresponding holiday texture through the system clock / Network Time Protocol (NTP), without requiring manual operation by the user.

[0183] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A method for adaptive adjustment of interface style based on a 3D car model, characterized in that, include: Identify the current scene to obtain multi-dimensional attribute features, which include at least one or more of geographical features, user features, and holiday features; The preset base model is style-scored based on the multidimensional attribute features, and then a target base model that is suitable for the current scene is determined from the preset base model. Based on the aforementioned multidimensional attribute features, the basic style of the target base model is adjusted differentially to achieve style conversion; Render the 3D model of the car based on the target base model after style transfer, and update the interface display accordingly; Based on the aforementioned multidimensional attribute features, the basic style of the target base model is differentiated and adjusted to achieve style transfer, including: Obtain the basic style parameters of the target base model; Determine the influence factor of each of the multidimensional attribute features on the target basic model; Obtain the influence factors of all the multidimensional attribute features of each target base model, perform weighted calculation to determine the adjustment magnitude, and make differentiated adjustments to the base style parameters according to the adjustment magnitude to achieve style conversion; The basic style parameters include the model facet count parameter and the smoothness parameter; Based on the aforementioned multidimensional attribute features, the basic style of the target base model is differentiated and adjusted to achieve style transfer, which also includes: Festival features are obtained from the multidimensional attribute features, and festival theme textures and festival factors are obtained based on the festival features; The base texture is obtained from the base style of the target base model, and the holiday-themed texture is compared with the base texture to determine the texture differences used to perform differential adjustments. The texture mapping parameters are determined based on the festival factor and the texture difference, and then mapped and superimposed with the base texture to obtain the target texture to achieve style conversion; Render the 3D car model based on the style-transferred target base model and update the interface display, including: Style transfer keywords are generated based on the target texture, and then a texture is generated based on the style transfer keywords and mapped onto the UV area of ​​the vehicle body. The Unreal Engine is used to dynamically bind the model parameters of the target base model after style transfer, and the stylized car model is rendered and output in real time. It is then connected to the HMI in-vehicle system to achieve interface update and display.

2. The method for adaptive adjustment of interface style based on a 3D car model as described in claim 1, characterized in that, Identify the current scene to obtain multi-dimensional attribute features, including: Identify the driver in the current scene and obtain user characteristics based on the corresponding user preferences; Based on the current scenario, vehicle location data is acquired, and local geographical features are obtained based on the vehicle location data. Obtain the real-time date and automatically identify holiday characteristics; The multidimensional attribute features include user features, geographical features, and the festival features.

3. The method for adaptive adjustment of interface style based on a 3D car model as described in claim 2, characterized in that, Based on the multidimensional attribute features, a style score is performed on the preset base model, and then a target base model suitable for the current scene is determined from the preset base model, including: Obtain the style fit of each of the multidimensional attribute features to each preset base model; Based on the style fit of the multidimensional attribute features, a weighted calculation is performed to determine the style score of each preset base model; The preset base model with the highest style score is selected as the target base model to adapt to the current scene.

4. The method for adaptive adjustment of interface style based on a 3D car model as described in claim 3, characterized in that, The weighted calculation formula for the style score is as follows: In the formula: This represents the total score of the i-th preset base model; This represents the degree to which user characteristics fit the preset base model; This represents the degree to which geographical features fit the preset base model; This represents the degree to which the characteristics of the festival fit the preset basic model; , , These represent the weighting coefficients for users, geography, and holidays, respectively, and satisfy the following conditions: .

5. The method for adaptive adjustment of interface style based on a 3D car model as described in claim 1, characterized in that, Also includes: After the interface is updated and displayed, user operation data is detected, and the weight coefficients and influencing factors corresponding to user characteristics are updated according to the user operation data, and user feedback closed-loop optimization is performed.

6. A system for adaptively adjusting the interface style based on a 3D car model, characterized in that, include: Processor and its connected memory and data acquisition module; The data acquisition module is used to identify the current scene to obtain multi-dimensional attribute features, which include at least one or more of geographical features, user features, and holiday features. The memory stores instructions that the processor can execute; When the processor is configured to execute the instructions, it implements the interface style adaptive adjustment method based on a 3D car model as described in any one of claims 1 to 5.

7. The interface style adaptive adjustment system based on a 3D car model as described in claim 6, characterized in that: The data acquisition module includes a GPS positioning module, a user information module, and a date processing module; The GPS positioning module is used to acquire vehicle location data, obtain climate data of the current area through the weather interface, and identify the human preferences of the current area from the historical database to obtain geographical features. The user information module is used to determine user information through facial recognition and to obtain user characteristics by determining the user's personalized preferences based on the user information; The date processing module is used to identify whether the current period is a specific holiday by using the built-in calendar and holiday database, and then obtain the holiday characteristics.

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