Facial and Garment Image Fusion for Low-Complexity Personalized Rendering
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Solution Overview
Problem
Existing garment customization methods lack realism and accuracy, require significant human resources and time, and are complex for ordinary users to operate, making it difficult to intuitively showcase how garments look on different body types.
Innovation Solution
A method and system for personalized image generation using generative algorithms to fuse facial and dressing effect images, allowing users to adjust elements and customize model faces for high-quality, quick image production with low operational difficulty.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional garment customization methods (hand-drawing, image editing software, virtual reality) are used, then some level of customization is achieved, but realism and accuracy are insufficient
Solution Approach 1:
The patent replaces traditional mechanical/image-editing methods with an AI-based system that automatically generates realistic garment rendering images. The system uses trained models to process input images and generate customized garment effects without requiring manual image editing operations, thereby achieving high realism while simplifying user interaction to basic input provision.
Solution Approach 2:
The patent creates digital copies of garments and models that can be virtually combined and rendered. By copying garment images and model images into a virtual environment, the system generates realistic composite images showing garments on different body types without physical prototypes, achieving both realism and operational simplicity.
2Productivity
If traditional garment customization methods are used, then some customization capability is provided, but significant human resources and time are required
Solution Approach 1:
The patent replaces manual image editing and customization processes with an automated AI system. The trained model automatically processes input images, extracts features, and generates customized garment rendering images, eliminating the need for human operators to perform time-consuming manual editing tasks and significantly improving productivity.
Solution Approach 2:
The patent performs preliminary training of the AI model using datasets of garments and models before actual customization. This pre-trained model can then quickly generate customized images without requiring time-consuming manual processing for each new customization request, reducing time and labor costs for production.
3Adaptability or versatility
If image editing software is used for custom rendering, then some customization is achievable, but users need image processing skills that ordinary users lack
Solution Approach 1:
The patent replaces complex image editing software operations with an automated AI system that handles all image processing tasks. Users only need to provide input images and select customization options, while the trained model automatically performs feature extraction, image combination, and rendering, making the system accessible to ordinary users without image processing skills.
Solution Approach 2:
The patent enables the system to perform image processing and customization automatically without human intervention in the technical steps. The AI model self-adjusts parameters, automatically combines images, and generates results based on user inputs, eliminating the need for users to manually execute complex editing operations.
4Adaptability or versatility
If virtual reality technology is used for garment visualization, then immersive experience is provided, but expensive equipment and specialized knowledge are required
Solution Approach 1:
The patent creates high-quality 2D/3D digital copies of garments and models that realistically visualize garment effects on different body types. These digital representations provide comprehensive visualization capability without requiring immersive virtual reality equipment, achieving adaptability while reducing device complexity and accessibility barriers.
Data Source
AI summary
A method and a system for personalized image generation are provided. The method includes: determining a facial description text specified by a user; generating, based on the facial description text, a facial image by using a generative algorithm; obtaining a first dressing effect image of a target garment, the first dressing effect image presenting a wearing effect of the target garment on a digital model; and generating a second dressing effect image of the target garment by performing a fusion operation on the facial image and the first dressing effect image, the second dressing effect image presenting a wearing effect of the target garment on a fused digital model. The provided solution not only enables the rapid, high-quality generation of garment images but also ensures that the fused images maintain feature consistency, meeting users' personalized display preferences.