Avatar Template Matching for Rapid Virtual Outfit Visualization
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Solution Overview
Problem
Existing virtual try-on technologies are slow and resource-intensive, requiring significant processing time and resources to generate realistic images of users trying on clothing, especially when multiple items or varied image types are involved, and they often require specific image formats, limiting real-time and versatile application.
Innovation Solution
Pre-computing avatar template images with diverse body types and parameters, allowing for rapid selection and adaptation of clothing items to match user body parameters, enabling real-time or near-real-time generation of realistic virtual try-on images across various image types and sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If existing virtual try-on technologies process images in real-time with full processing pipelines, then image generation quality is maintained, but processing time and resource consumption increase significantly
Solution Approach 1:
The system performs preliminary actions by pre-computing and storing avatar template images with diverse body types, parameters, and clothing items in a database during an offline setup phase. This pre-processing includes generating multiple avatar templates with different body measurements, clothing styles, and backgrounds, then storing them for rapid retrieval during runtime. When a user requests a virtual try-on, the system quickly queries the database for matching templates rather than generating images from scratch, dramatically reducing processing time while maintaining quality through the use of pre-rendered high-quality templates.
Solution Approach 2:
The system segments the virtual try-on process into distinct phases: an offline setup phase for pre-computing and storing avatar templates with diverse parameters, and a runtime phase for rapid template selection and image composition. This segmentation allows computationally intensive operations to be performed beforehand when resources are abundant, while runtime operations focus only on lightweight queries and compositions, resolving the contradiction between quality maintenance and processing speed.
2Measurement precision
If existing virtual try-on technologies use comprehensive processing pipelines for accurate clothing fitting, then visualization accuracy is improved, but resource utilization increases
Solution Approach 1:
The system performs preliminary actions by pre-computing and storing avatar template images with diverse body types, parameters, and clothing items in a database during an offline setup phase. This pre-processing includes generating multiple avatar templates with different body measurements, clothing styles, and backgrounds, then storing them for rapid retrieval during runtime. When a user requests a virtual try-on, the system quickly queries the database for matching templates rather than generating images from scratch, dramatically reducing processing time while maintaining quality through the use of pre-rendered high-quality templates.
Solution Approach 2:
The system creates and stores multiple copies of avatar templates with different body parameters, clothing items, and configurations in advance. Instead of generating unique images for each user request, the system retrieves and composes from pre-generated template copies that match user characteristics. This copying approach maintains visualization accuracy by providing diverse, pre-rendered options while significantly reducing runtime computational resources.
3Adaptability or versatility
If existing virtual try-on technologies process multiple clothing items and image types, then versatility is improved, but processing complexity increases
Solution Approach 1:
The system implements a universal database structure that stores avatar templates supporting multiple clothing items, body types, and image formats within a single integrated framework. The template system is designed to accommodate diverse image types (frontal views, side views, different lighting conditions) and clothing categories (tops, bottoms, dresses, accessories) using a common storage and retrieval mechanism. This universality allows the system to handle varied image types and clothing items without requiring separate processing pipelines for each case, thus maintaining versatility while controlling complexity.
4Manufacturing precision
If existing virtual try-on technologies generate images from scratch for each user, then customization accuracy is improved, but processing speed decreases
Solution Approach 1:
The system performs preliminary actions by pre-computing and storing avatar template images with diverse body types, parameters, and clothing items in a database during an offline setup phase. This pre-processing includes generating multiple avatar templates with different body measurements, clothing styles, and backgrounds, then storing them for rapid retrieval during runtime. When a user requests a virtual try-on, the system quickly queries the database for matching templates rather than generating images from scratch, dramatically reducing processing time while maintaining quality through the use of pre-rendered high-quality templates.
Solution Approach 2:
The system uses parameter-based template matching where user body measurements and characteristics are compared against stored template parameters to identify the best matching pre-generated avatar. By changing from full image generation to parameter-based template selection, the system achieves rapid customization that maintains accuracy through precise parameter matching while significantly improving processing speed.
Data Source
AI summary
There is provided a method, comprising: in a set-up phase: instructing a ML image generator for generating avatar template images each depicting a different representative body type having different parameters, adapting s segmented source clothing item to correspond to the parameters of each avatar template image, for each avatar template image, generating a clothed image including the avatar template image wearing the adapted segmented source clothing item, during run-time: receiving an input image depicting a body of a user, computing parameters of the body of the user, searching the avatar template images for an avatar template image most correlated with the parameters of the body of the user, and presenting the clothed image associated with the avatar template image, wherein a body of an avatar wearing the segmented source clothing depicted in the clothed image emulates the body of the user virtually wearing the source clothing.