Virtual Avatar Generation Using User and Event Attributes
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Solution Overview
Problem
Existing digital avatars in the metaverse are monotonous and lack personalization, leading to a poor user experience.
Innovation Solution
A virtual image generation method that considers user attribute features and event attribute information to create personalized digital avatars recognizable by others, enhancing user experience through customizable and interactive virtual image generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If digital avatars are generated based only on actual user features, then the generation process is simple, but the avatars are monotonous and lack personalization
Solution Approach 1:
The patent segments the avatar generation process into multiple independent modules: user feature acquisition module, event feature acquisition module, and virtual image generation module. Each module handles specific tasks (user attributes, event attributes, image synthesis), allowing the system to achieve high personalization through modular complexity rather than monolithic complexity. This segmentation enables the system to incorporate diverse data sources without overwhelming the generation process.
Solution Approach 2:
The patent performs preliminary actions by pre-acquiring and storing user attribute features and event attribute features before the actual avatar generation. User features are obtained through registration or authentication, and event features are obtained through event registration or authentication. These preliminary data preparations enable the generation module to focus solely on synthesizing the personalized avatar, simplifying the core generation process while achieving high adaptability.
2Reliability
If multiple features are integrated to create personalized avatars, then user experience is improved, but the data processing complexity increases
Solution Approach 1:
The patent divides data processing into separate segments: user feature processing (through authentication or registration) and event feature processing (through event registration or authentication). Each segment handles specific data types independently, reducing the complexity of integrating multiple data sources. The segmentation allows the system to process diverse features without creating a monolithic complex processing pipeline.
Solution Approach 2:
The patent introduces an intermediary generation model that mediates between raw user features and raw event features to produce the final virtual image. This intermediary model acts as a bridge that processes and integrates multiple feature types without requiring direct complex interactions between all data sources. The generation model transforms diverse input features into a cohesive personalized avatar, reducing overall system complexity.
Data Source
AI summary
A virtual image generation method includes: determining, in response to a login event of a target user, a user identifier of the target user, and displaying a virtual image generation interface to the target user; acquiring at least one user attribute feature of the target user according to the user identifier, and acquiring event attribute information for a target event determined by the target user on the virtual image generation interface; and generating a virtual image of the target user according to the at least one user attribute feature of the target user and the event attribute information. The virtual image of the target user has the at least one user attribute feature of the target user.