Virtual Image Generation via Standard Model Mapping and Texture Filling
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Solution Overview
Problem
The high cost and inefficiency of producing personalized virtual images in virtual reality and augmented reality applications, where customized high-precision models can cost up to $1 million and require extensive designer customization, limit the widespread adoption and accessibility of virtual agents in digital environments.
Innovation Solution
A virtual image generation method that acquires base coefficients from target face pictures, generates a virtual image structure based on a mapping relationship between a preset virtual model and a standard model, and performs texture filling to produce a virtual image, utilizing neural network models for efficient and cost-effective generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional designer customization is used to produce personalized virtual images, then the quality and precision of virtual agent models can be improved, but the production cost increases significantly (tens of thousands to over 1 million dollars)
Solution Approach 1:
The patent uses a standard model as a template that can be copied and adapted for different virtual images. Instead of creating each virtual agent from scratch through expensive designer customization, the system copies the standardized structure and applies automatic parameter adjustment to generate personalized virtual images, dramatically reducing production costs while maintaining quality
Solution Approach 2:
The system adjusts specific parameters of the standard model (such as facial features, body proportions, and other attributes) to generate different personalized virtual images. By changing parameters rather than redesigning entire models, the system achieves high-quality customization at low cost
2Adaptability or versatility
If traditional designer customization is used for virtual image production, then personalized virtual agents can be created, but the production time and efficiency are significantly reduced
Solution Approach 1:
The system enables automatic generation of personalized virtual images through algorithm-driven parameter adjustment rather than manual designer intervention. The standardized model automatically adapts to different personalization requirements through computational methods, eliminating the time-consuming manual customization process and dramatically improving production efficiency
Solution Approach 2:
The patent pre-establishes a standardized model with all necessary structural components and parameters configured in advance. This preliminary preparation allows for rapid generation of personalized virtual images by simply adjusting parameters, rather than starting from scratch for each customization request
Data Source
AI summary
A virtual image generation method and apparatus, an electronic device and a storage medium which relates to the field of artificial intelligence technologies such as augmented reality, computer vision and deep learning. A specific implementation scheme involves: acquiring base coefficients corresponding to key points of a target face based on a target face picture; generating a structure of a virtual image of the target face based on a mapping relationship of spatial alignment between a preset virtual model and a standard model, a base of the standard model and the base coefficients corresponding to the key points of the target face; and performing texture filling on the structure of the virtual image based on textures of the target face picture, to obtain the virtual image of the target face.