AR card interaction method and system based on user portrait and dynamic matching algorithm

Abstract

The invention relates to an AR card interaction method and system based on a user portrait and a dynamic matching algorithm, and the method comprises the steps: obtaining the materials of an IP card in the aspects of videos, 3D models and special effect resources, and constructing a user portrait database; identifying card features and associating a user account based on an AR module; according to the user portraits and the material labels, matching scores are calculated through a weighting formula, and a recommendation list is generated according to score sorting; loading the recommended material, and adjusting the special effect according to the 3D engine in combination with the environment data; and associating recommendation priorities according to the degrees of collecting, liking, commenting or purchasing the materials by the user, and updating the user portrait in real time. According to the method, a highly personalized effect is achieved by combining the user portrait and the environment data, the scene immersion is enhanced and the dynamic adaptability is improved by adjusting the recommended content and rendering the special effect in real time, and the viscidity is improved by supporting the user to actively participate in content selection and feedback, so that the interaction diversity is realized.

Description

Technical Field

[0001] The present invention relates to the field of AR card interaction, and particularly to an AR card interaction method and system based on user portraits and dynamic matching algorithms. Background Art

[0002] Traditional VR display technologies for collectible cards mainly use WebAR technology to identify specific IP card images or anime characters and load pre-set videos or 3D models for static display.

[0003] Although traditional technologies can achieve basic recognition and rendering, they have the following significant drawbacks:

[0004] 1. Lack of personalization: The display content seen by all users is the same, and it cannot be dynamically adjusted according to user characteristics (such as interests, levels, environments, etc.);

[0005] 2. Single interaction: Users cannot select or provide feedback on content through personalized recommendations, and the interactivity is limited to one-way display;

[0006] 3. Poor scene adaptability: The display content has no association with the user's real-time environment (such as weather, geographical location), resulting in insufficient immersion. Summary of the Invention

[0007] Based on this, it is necessary to provide an AR card interaction method and system based on user portraits and dynamic matching algorithms to address the problems of lack of personalization, single interaction, and poor scene adaptability in traditional VR display technologies for collectible cards.

[0008] An AR card interaction method based on user portraits and dynamic matching algorithms provided by the present invention includes:

[0009] Obtain materials of IP cards in terms of videos, 3D models, and special effect resources, and construct a user portrait database;

[0010] Based on the AR module, identify card features and associate with user accounts;

[0011] Calculate a matching score according to the user portrait and material tags through a weighted formula, and generate a recommendation list sorted by the score;

[0012] Load the recommended materials, and adjust the special effects according to the 3D engine combined with environmental data;

[0013] Associate the recommendation priority according to the degree of the user's collection, like, comment, or purchase of materials, and update the user portrait in real time.

[0014] In one embodiment, the step of obtaining materials of IP cards in terms of videos, 3D models, and special effect resources, and constructing a user portrait database includes:

[0015] Obtain multiple types of materials for IP cards and label them. The materials include videos, 3D models, and special effect resources, and the labels include style, scene, and emotion;

[0016] Build a user profile database and integrate static attributes and dynamic data. The static attributes include gender and interests, and the dynamic data includes real-time weather and mood.

[0017] In one embodiment, the calculation formula for calculating the matching score through the weighting formula is as follows: S = W m ·f m +W g ·f g +W h ·f h +W p ·f p +W mood ·f mood +W location ·f location +W weather ·f weather ,

[0018] where S is the final matching score, W m is the membership level weight, W g is the gender matching weight, W h is the hobby matching weight, W p is the preference label matching weight, W mood is the mood matching weight, W location is the region weight, W weather is the weather weight, f m = membership level / 5 (normalized). If the user's gender matches the resource requirements, then f g = 1, otherwise f g = 0, f h = number of matching hobbies / total number of hobbies, f p = number of matching preference labels / total number of labels. If the mood matches the resource recommendation, then f mood = 1, otherwise f mood = 0.5. If the resource recommendation is applicable to this region, then f location = 1, otherwise f location = 0.7. If the resource is suitable for the current weather, then f weather = 1, otherwise f weather = 0.5.

[0019] In one embodiment, the loading of recommended materials and the adjustment of special effects in combination with environmental data by the 3D engine include:

[0020] Select appropriate resources for 3D models, textures, animations, and sound effects from the material library;

[0021] Import the materials into the 3D engine and organize and classify the materials;

[0022] Obtain the environmental data and map the environmental data to the parameters in the 3D scene;

[0023] Dynamically generate special effects according to the environmental data, and dynamically adjust the special effects using the particle system, shader or script of the engine.

[0024] The present invention also provides an AR card interaction device based on user portraits and dynamic matching algorithms, including:

[0025] A construction module for obtaining materials of IP cards in terms of videos, 3D models, and special effect resources, and constructing a user portrait database;

[0026] An association module for identifying card features and associating user accounts based on the AR module;

[0027] A calculation module for calculating a matching score through a weighted formula according to user portraits and material tags, and generating a recommendation list sorted by score;

[0028] A loading module for loading recommended materials and adjusting special effects according to the 3D engine combined with environmental data;

[0029] An update module for associating recommendation priorities according to the degree of user collection, like, comment or purchase of materials, and updating user portraits in real time.

[0030] In one embodiment, the construction module includes:

[0031] An acquisition module for acquiring various types of materials of IP cards and labeling tags. The materials include videos, 3D models, and special effect resources, and the tags include style, scene, and emotion;

[0032] An integration module for constructing a user portrait database and integrating static attributes and dynamic data. The static attributes include gender and interest, and the dynamic data include real-time weather and mood.

[0033] In one embodiment, the loading module includes:

[0034] A selection module for selecting appropriate resources of 3D models, textures, animations, and sound effects from the material library;

[0035] A classification module for importing the materials into the 3D engine and organizing and classifying the materials;

[0036] A mapping module for obtaining environmental data and mapping the environmental data to the parameters in the 3D scene;

[0037] An adjustment module, configured to dynamically generate special effects according to environmental data, and dynamically adjust the special effects using the particle system, shader, or script of the engine.

[0038] The present invention also provides an AR card interaction system based on user portraits and dynamic matching algorithms, including:

[0039] A user portrait database, configured to store user membership levels, genders, interest tags, historical behaviors, and real-time environmental data;

[0040] A material database, configured to store videos, 3D models, and special effect resources classified by IP cards, and each material is bound with multi-dimensional tags;

[0041] An AR recognition module, connected to the material database, and configured to scan the card through a camera, extract features, and match them with the material database;

[0042] A dynamic matching engine, connected to the user portrait database and the material database, and configured to calculate the matching degree between the user portrait and the material tags based on a weighted algorithm, and generate a recommendation list;

[0043] An interaction feedback module, connected to the user portrait database, and configured to support operations such as collection, like, comment, and purchase of recommended content by the user, and update the user portrait in real time;

[0044] A 3D rendering engine, configured to load recommended materials and overlay AR special effects, and adjust the rendering effect in combination with environmental data.

[0045] The present invention also provides an electronic device, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, it implements the AR card interaction method based on user portraits and dynamic matching algorithms as described in any one of the above.

[0046] The present invention also provides a computer-readable storage medium, storing a computer program, and when the computer program is executed by a processor, it implements the AR card interaction method based on user portraits and dynamic matching algorithms as described in any one of the above.

[0047] The above AR card interaction method and system based on user portraits and dynamic matching algorithms, by combining user portraits with environmental data, achieve an "individualized for each person" AR display effect, thus achieving a highly personalized effect, enhance the scene immersion by adjusting the recommended content and rendering special effects in real time, improve the dynamic adaptability, optimize the recommendation strategy through user behavior feedback, promote content consumption and IP derivative sales, thereby enhancing the commercial value, and enhance the stickiness by supporting the user's active participation in content selection and feedback, thus achieving interaction diversity, and the flexibility of the algorithm can be improved by configuring the parameters of the weighted formula to adapt to different IPs and operation requirements. Description of the Drawings

[0048] To more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0049] Figure 1 It is a schematic flowchart of an AR card interaction method based on user portraits and dynamic matching algorithms in an embodiment;

[0050] Figure 2 It is a schematic flowchart of constructing a user portrait database in an embodiment;

[0051] Figure 3 It is a schematic flowchart of adjusting special effects according to the 3D engine combined with environmental data in an embodiment;

[0052] Figure 4 It is a schematic structural diagram of an AR card interaction device based on user portraits and dynamic matching algorithms in an embodiment;

[0053] Figure 5 It is a schematic structural diagram of an AR card interaction system based on user portraits and dynamic matching algorithms in an embodiment;

[0054] Figure 6 It is an internal structural diagram of an electronic device in an embodiment.

[0055] Reference numerals:

[0056] 410, construction module; 411, acquisition module; 412, integration module; 420, association module; 430, calculation module; 440, loading module; 441, selection module; 442, classification module; 443, mapping module; 444, adjustment module; 450, update module; 510, user portrait database; 520, material database; 530, AR recognition module; 540, dynamic matching engine; 550, interaction feedback module; 560, 3D rendering engine. Specific embodiments

[0057] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0058] The following combines Figures 1-6 to describe the AR card interaction method and system based on user portraits and dynamic matching algorithms of the present invention.

[0059] As Figure 1 shown, in one embodiment, an AR card interaction method based on user portraits and dynamic matching algorithms includes the following steps:

[0060] Step S110, obtain materials of IP cards in terms of videos, 3D models, and special effect resources, and construct a user portrait database.

[0061] It should be added that the user portrait database stores user membership levels, genders, interest tags, historical behaviors (collection / purchase), real-time environmental data (weather, geographical location), etc.

[0062] Step S120, based on the AR module, identify card features and associate them with user accounts.

[0063] After the user logs in and scans the card, the AR module identifies the card features and associates them with the user account.

[0064] Step S130, calculate the matching score through a weighted formula according to the user portrait and material tags, and generate a recommendation list sorted by score.

[0065] The recommendation list defaults to showing the highest score and supports manual switching.

[0066] It should be added that the calculation formula for calculating the matching score through the weighted formula is as follows: S = W m ·f m +W g ·f g +W h ·f h +W p ·f p +W mood ·f mood +W location ·f location +W weather ·f weather ,

[0067] where S is the final matching score, W m is the membership level weight, W g is the gender matching weight, W h is the hobby matching weight, W p is the preference tag matching weight, W mood is the mood matching weight, W location is the regional weight, W weather is the weather weight, f m= Membership level / 5 (normalized). If the user's gender matches the resource requirements, then f g = 1; otherwise, f g = 0. f h = Number of matching hobbies / Total number of hobbies. f p = Number of matching preference tags / Total number of tags. If the mood matches the resource recommendation, then f mood = 1; otherwise, f mood = 0.5. If the resource recommendation is applicable to this region, then f location = 1; otherwise, f location = 0.7. If the resource is suitable for the current weather, then f weather = 1; otherwise, f weather = 0.5.

[0068] Step S140: Load the recommended materials and adjust the special effects according to the 3D engine combined with the environmental data.

[0069] For example: Add snowflake particles to the snow scene.

[0070] Step S150: According to the degree of the user's collection, like, comment or purchase of the materials, associate the recommendation priority and update the user profile in real time.

[0071] The user's purchase behavior is directly associated with the recommendation priority to increase the exposure rate of high-value materials.

[0072] This AR card interaction method based on the user profile and dynamic matching algorithm realizes the "one-to-one" AR display effect by combining the user profile and environmental data, thus achieving a highly personalized effect. By adjusting the recommended content and rendering special effects in real time, it enhances the scene immersion and improves the dynamic adaptability. By optimizing the recommendation strategy through the user behavior feedback, it promotes content consumption and IP derivative sales, thus enhancing the commercial value. By supporting the user's active participation in content selection and feedback, it improves the stickiness, thus realizing the interaction diversity. By making the weighted formula parameters configurable, it adapts to different IP and operation requirements and improves the algorithm flexibility.

[0073] In this embodiment, refer to Figure 2 , obtain the materials of the IP card regarding videos, 3D models, and special effect resources, and construct a user profile database, including the following steps:

[0074] Step S111: Obtain various types of materials of the IP card and label them. The materials include videos, 3D models, and special effect resources, and the labels include style, scene, and emotion.

[0075] By adopting the multi-label matching algorithm and the method of combining collaborative filtering and content recommendation, it is convenient to dynamically adjust the weight parameters.

[0076] Step S112, construct a user profile database and integrate static attributes and dynamic data. The static attributes include gender and interests, and the dynamic data includes real-time weather and mood.

[0077] By integrating static user attributes, dynamic environment, and behavior data, comprehensively drive the personalized experience and achieve multi-source data fusion.

[0078] In this embodiment, refer to Figure 3 , load the recommended materials and adjust the special effects according to the 3D engine combined with the environmental data, including the following steps:

[0079] Step S141, select appropriate resources of 3D models, textures, animations, and sound effects from the material library.

[0080] It is convenient to select the corresponding materials according to the requirements.

[0081] Step S142, import the materials into the 3D engine and organize and classify the materials.

[0082] The 3D engine includes Unity, Unreal Engine, Blender, etc. When importing the materials into the 3D engine, it is necessary to ensure that the format of the materials is compatible with the engine. By organizing and classifying the materials, it is convenient for subsequent calling and adjustment.

[0083] Step S143, obtain the environmental data and map the environmental data to the parameters in the 3D scene.

[0084] For example: Lighting data: Adjust the light source intensity and color in the scene according to the real-time lighting;

[0085] Weather data: Adjust the fog effect, rain and snow effects, etc. in the scene according to the weather conditions;

[0086] Time data: Adjust the day-night cycle or dynamic light and shadow in the scene according to the time change.

[0087] Step S144, dynamically generate special effects according to the environmental data and use the particle system, shader, or script of the engine to dynamically adjust the special effects.

[0088] Obtain weather and geographical location data through the API to drive the rendering engine to dynamically adjust the scene lighting and special effects, so as to facilitate real-time environment adaptation.

[0089] Dynamically generate special effects from the environmental data, such as automatically generating raindrop effects on rainy days or generating starry sky effects at night.

[0090] Dynamically adjust the special effects as follows:

[0091] Particle effect: Adjust the particle movement trajectory according to the wind speed;

[0092] Material effect: Adjust the reflection or transparency of the material according to temperature changes;

[0093] Sound effect adjustment: Adjust the volume and pitch of the background music or sound effects according to the ambient sound.

[0094] Application scenario 1: Festival-themed card display

[0095] User profile:

[0096] Tags: Preference for "Christmas theme", interest tag "festival decoration"

[0097] Environmental data: Geographic location "New York", weather "heavy snow", time "December 24th"

[0098] Process steps:

[0099] 1. Card recognition: The user scans the "Santa Claus" physical card, and the AR module matches the "Santa Claus 3D model set" in the material library.

[0100] 2. Dynamic matching:

[0101] Interest weight (α = 0.6): Match the "Christmas theme" tag;

[0102] Environmental weight (β = 0.3): The snowy scene triggers the "snowfall special effect" tag;

[0103] Behavior weight (γ = 0.1): The user has historically collected "snow scene materials".

[0104] Total score calculation: S = 0.6 * 95 + 0.3 * 90 + 0.1 * 80 = 92 (out of 100)

[0105] 3. Rendering and interaction:

[0106] Load the "Santa Claus on a Snowy Night" model, overlay dynamic snowfall particles and festive lighting effects;

[0107] After the user clicks "Favorite", the system automatically increases the weight of "winter theme" materials to α = 0.7.

[0108] Application scenario 2: Game IP card battle scene

[0109] User profile:

[0110] Tags: Member level "diamond", purchase record "battle special effect package"

[0111] Environmental data: Geographic location "Tokyo", weather "sunny", time "weekend evening"

[0112] Process steps:

[0113] 1. Card Recognition: The user scans the "Dragon" card, and the AR module matches the "Flame Dragon Battle Group" in the material library.

[0114] 2. Dynamic Matching:

[0115] Interest Weight (α = 0.5): Prefers "battle style";

[0116] Environment Weight (β = 0.2): The night scene triggers the "Dark Special Effect" label;

[0117] Behavior Weight (γ = 0.3): The user has purchased the "Flame Special Effect".

[0118] Total Score Calculation: S = 0.5 * 90 + 0.2 * 70 + 0.3 * 95 = 87.5

[0119] 3. Rendering and Interaction:

[0120] Load the "Dragon Flame Breath" model, and overlay the battle BGM and screen vibration special effects;

[0121] After the user purchases the "Exclusive Achievement Animation Pack", the system pushes a time-limited discount on the "Dragon Race Skin Package".

[0122] Next, the AR card interaction device provided by the present invention based on the user portrait and dynamic matching algorithm will be described. The AR card interaction device based on the user portrait and dynamic matching algorithm described below can be mutually corresponding and referred to the AR card interaction method based on the user portrait and dynamic matching algorithm described above.

[0123] As Figure 4 shown, in one embodiment, an AR card interaction device based on the user portrait and dynamic matching algorithm includes a construction module 410, an association module 420, a calculation module 430, a loading module 440, and an update module 450.

[0124] The construction module 410 is used to obtain materials of the IP card in terms of video, 3D model, and special effect resources, and construct a user portrait database.

[0125] The association module 420 is used to identify card features and associate user accounts based on the AR module.

[0126] The calculation module 430 is used to calculate the matching score through a weighted formula according to the user portrait and material tags, and generate a recommendation list by sorting according to the score.

[0127] The loading module 440 is used to load the recommended materials and adjust the special effects according to the 3D engine combined with the environmental data.

[0128] The update module 450 is used to associate recommended priorities according to the degree of users' favorites, likes, comments or purchases of materials, and update the user profile in real time.

[0129] In this embodiment, the construction module 410 includes an acquisition module 411 and an integration module 412.

[0130] The acquisition module 411 is used to acquire various types of materials of IP cards and label them. The materials include videos, 3D models and special effect resources, and the labels include styles, scenes and emotions.

[0131] The integration module 412 is used to construct a user profile database and integrate static attributes and dynamic data. The static attributes include gender and interests, and the dynamic data include real-time weather and mood.

[0132] In this embodiment, the loading module 440 includes a selection module 441, a classification module 442, a mapping module 443 and an adjustment module 444.

[0133] The selection module 441 is used to select appropriate resources of 3D models, textures, animations and sound effects from the material library.

[0134] The classification module 442 is used to import the materials into the 3D engine and organize and classify the materials.

[0135] The mapping module 443 is used to acquire environmental data and map the environmental data to the parameters in the 3D scene.

[0136] The adjustment module 444 is used to dynamically generate special effects according to the environmental data and dynamically adjust the special effects using the particle system, shader or script of the engine.

[0137] This AR card interaction device based on user profile and dynamic matching algorithm realizes the "one-size-fits-one" AR display effect by combining the user profile with environmental data, thus achieving a highly personalized effect. By adjusting the recommended content and rendering special effects in real time, it enhances the scene immersion and improves the dynamic adaptability. By optimizing the recommendation strategy through user behavior feedback, it promotes content consumption and IP derivative sales, thus enhancing the commercial value. By supporting users to actively participate in content selection and feedback, it improves the stickiness, thus realizing interactive diversity. By making the weighted formula parameters configurable, it adapts to different IP and operation requirements and improves the algorithm flexibility. By integrating static user attributes, dynamic environment and behavior data, it comprehensively drives the personalized experience and realizes the integration of multi-source data.

[0138] Such as Figure 5As shown in the figure, in one embodiment, an AR card interaction system based on user portraits and dynamic matching algorithms includes a user portrait database 510, a material database 520, an AR recognition module 530, a dynamic matching engine 540, an interaction feedback module 550, and a 3D rendering engine 560.

[0139] The user portrait database 510 is used to store user membership levels, genders, interest tags, historical behaviors, and real-time environmental data.

[0140] Historical behaviors such as collection or purchase behaviors, and real-time environmental data such as weather and geographical location.

[0141] The material database 520 is used to store videos, 3D models, and special effect resources classified by IP cards, and each material is bound with multi-dimensional tags.

[0142] Multi-dimensional tags such as style, scene, and emotion.

[0143] The AR recognition module 530 is connected to the material database 520, and the AR recognition module 530 is used to scan the cards through a camera, extract features, and match them with the material database.

[0144] The dynamic matching engine 540 is connected to the user portrait database 510 and the material database 520, and the dynamic matching engine 540 is used to calculate the matching degree between the user portrait and the material tags based on a weighted algorithm and generate a recommendation list.

[0145] The interaction feedback module 550 is connected to the user portrait database 510, and the interaction feedback module 550 is used to support users' operations of collecting, liking, commenting on, and purchasing recommended content, and to update the user portrait in real time.

[0146] The 3D rendering engine 560 is used to load recommended materials and overlay AR special effects, and adjust the rendering effect in combination with environmental data.

[0147] Adjust the rendering effect in combination with environmental data, such as showing a wet special effect on a rainy day.

[0148] The AR card interaction system based on user portraits and dynamic matching algorithms combines user portraits with environmental data to achieve a "one-size-fits-one" AR display effect, thus achieving a highly personalized effect. By adjusting the recommended content and rendering special effects in real time, it enhances the scene immersion, improves the dynamic adaptability. By optimizing the recommendation strategy through user behavior feedback, it promotes content consumption and IP derivative sales, thus enhancing the commercial value. By supporting users to actively participate in content selection and feedback, it enhances the stickiness, thus realizing interaction diversity. By making the weighted formula parameters configurable, it adapts to different IPs and operation requirements, and improves the algorithm flexibility.

[0149] Figure 6Illustrates a schematic diagram of the physical structure of an electronic device, which can be a smart terminal, and its internal structure diagram can be as Figure 6 shown. The electronic device includes a processor, a memory, and a network interface connected through a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface of the electronic device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it realizes an AR card interaction method based on a user portrait and a dynamic matching algorithm. The method includes:

[0150] Obtain materials of the IP card in terms of video, 3D model, and special effect resources, and construct a user portrait database;

[0151] Based on the AR module, identify the card features and associate them with the user account;

[0152] According to the user portrait and material tags, calculate the matching score through a weighted formula, and generate a recommendation list by sorting according to the score;

[0153] Load the recommended materials, and adjust the special effects according to the 3D engine combined with the environmental data;

[0154] According to the degree of the user's collection, like, comment, or purchase of materials, associate the recommendation priority, and update the user portrait in real time.

[0155] Those skilled in the art can understand that Figure 6 the structure shown in

[0156] is only a block diagram of some structures related to the solution of the present invention, and does not constitute a limitation on the electronic device to which the solution of the present invention is applied. The specific electronic device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0157] Obtain materials of the IP card in terms of video, 3D model, and special effect resources, and construct a user portrait database;

[0158] Based on the AR module, identify the card features and associate them with the user account;

[0159] According to the user portrait and material tags, calculate the matching score through a weighted formula, and generate a recommendation list by sorting according to the score;

[0160] Load recommended materials and adjust special effects according to the 3D engine combined with environmental data;

[0161] Associate the recommendation priority according to the degree of the user's collection, like, comment or purchase of materials, and update the user profile in real time.

[0162] In another aspect, a computer program product or a computer program is provided. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the electronic device reads the computer instructions from the computer-readable storage medium. When the processor executes the computer instructions, an AR card interaction method based on the user profile and the dynamic matching algorithm is implemented. The method includes:

[0163] Obtain materials of IP cards in terms of videos, 3D models, and special effect resources, and build a user profile database;

[0164] Based on the AR module, identify the card features and associate the user account;

[0165] According to the user profile and material tags, calculate the matching score through a weighted formula, and generate a recommendation list by sorting according to the score;

[0166] Load recommended materials and adjust special effects according to the 3D engine combined with environmental data;

[0167] Associate the recommendation priority according to the degree of the user's collection, like, comment or purchase of materials, and update the user profile in real time.

[0168] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to the memory, storage, database or other media used in the embodiments provided by the present invention can include non-volatile and / or volatile memories. The non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. The volatile memory can include random access memory (RAM) or an external cache memory.

[0169] By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct Rambus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0170] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0171] The above-described embodiments merely represent several implementation manners of the present invention. The description thereof is relatively specific and detailed, but it should not be construed as a limitation to the scope of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the appended claims.

Claims

1. An AR card interaction method based on user portraits and dynamic matching algorithms, characterized in that, The method includes: Obtain materials of the IP card regarding videos, 3D models, and special effect resources, and construct a user profile database; Based on the AR module, identify card features and associate with the user account; According to the user profile and material tags, calculate the matching score through a weighted formula, and generate a recommendation list sorted by the score; Load the recommended materials, and adjust the special effects according to the 3D engine combined with environmental data; According to the degree of the user's collection, like, comment, or purchase of materials, associate the recommendation priority and update the user profile in real time.

2. The AR card interaction method based on user portraits and dynamic matching algorithms according to claim 1, wherein, The obtaining of materials of the IP card regarding videos, 3D models, and special effect resources, and constructing a user profile database includes: Obtain various types of materials of the IP card and label them. The materials include videos, 3D models, and special effect resources, and the labels include style, scene, and emotion; Construct a user profile database, and integrate static attributes and dynamic data. The static attributes include gender and interest, and the dynamic data includes real-time weather and mood.

3. The AR card interaction method based on user portraits and dynamic matching algorithms according to claim 2, characterized in that, The calculation formula for calculating the matching score through the weighted formula is as follows: S = W m ·f m +W g ·f g +W h ·f h +W p ·f p +W mood ·f mood +W location ·f location +W weather ·f weather , Among them, S is the final matching score, W m is the membership level weight, W g is the gender matching weight, W h is the hobby matching weight, W p is the preference label matching weight, W mood is the mood matching weight, W location is the region weight, W weather is the weather weight, f m = membership level / 5 (normalized), if the user's gender matches the resource requirements, then f g = 1, otherwise f g = 0, f h = number of matching hobbies / total number of hobbies, f p = number of matching preference labels / total number of labels, if the mood matches the resource recommendation, then f mood = 1, otherwise f mood = 0.5, if the resource recommendation is applicable to this region, then f location = 1, otherwise f location = 0.7, if the resource is suitable for the current weather, then f weather = 1, otherwise f weather = 0.

5.

4. The AR card interaction method based on user portraits and dynamic matching algorithms according to claim 3, characterized in that The loading of the recommended materials and adjusting the special effects according to the 3D engine combined with environmental data includes: Select appropriate resources of 3D models, textures, animations, and sound effects from the material library; Import the materials into the 3D engine, and organize and classify the materials; Obtain environmental data and map the environmental data to the parameters in the 3D scene; Dynamically generate special effects according to the environmental data, and dynamically adjust the special effects using the particle system, shader, or script of the engine.

5. An AR card interaction device based on user portraits and dynamic matching algorithms, characterized in that, Include: A construction module for obtaining materials of the IP card regarding videos, 3D models, and special effect resources, and constructing a user profile database; An association module for identifying card features and associating with the user account based on the AR module; A calculation module for calculating the matching score through a weighted formula according to the user profile and material tags, and generating a recommendation list sorted by the score; A loading module for loading the recommended materials and adjusting the special effects according to the 3D engine combined with environmental data; An update module for associating the recommendation priority according to the degree of the user's collection, like, comment, or purchase of materials, and updating the user profile in real time.

6. The AR card interaction device based on the user portrait and the dynamic matching algorithm according to claim 5, wherein The construction module includes: An obtaining module for obtaining various types of materials of the IP card and labeling them. The materials include videos, 3D models, and special effect resources, and the labels include style, scene, and emotion; An integration module for constructing a user profile database and integrating static attributes and dynamic data. The static attributes include gender and interest, and the dynamic data includes real-time weather and mood.

7. The AR card interaction device based on the user portrait and the dynamic matching algorithm according to claim 6, wherein, The loading module includes: A selection module for selecting appropriate resources of 3D models, textures, animations, and sound effects from the material library; A classification module for importing the materials into the 3D engine and organizing and classifying the materials; A mapping module for obtaining environmental data and mapping the environmental data to the parameters in the 3D scene; An adjustment module for dynamically generating special effects according to the environmental data and dynamically adjusting the special effects using the particle system, shader, or script of the engine.

8. An AR card interaction system based on user portraits and dynamic matching algorithms, characterized in that, Include: A user profile database for storing the user's membership level, gender, interest tags, historical behaviors, and real-time environmental data; A material database for storing videos, 3D models, and special effect resources classified by IP cards, with each material bound with multi-dimensional tags; An AR recognition module connected to the material database and used to scan cards through a camera, extract features, and match them with the material database; A dynamic matching engine connected to the user portrait database and the material database and used to calculate the matching degree between the user portrait and the material tags based on a weighted algorithm and generate a recommendation list; An interactive feedback module connected to the user portrait database and used to support the user's operations of collecting, liking, commenting on, and purchasing the recommended content and update the user portrait in real time; A 3D rendering engine for loading the recommended materials and overlaying AR special effects, and adjusting the rendering effect in combination with environmental data.

9. An electronic device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the AR card interaction method based on the user portrait and the dynamic matching algorithm described in any one of claims 1 to 4.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the AR card interaction method based on the user portrait and the dynamic matching algorithm described in any one of claims 1 to 4.

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