Automated Garment Grading via Avatar Strain Ratios
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Solution Overview
Problem
Existing methods for grading clothing patterns fail to accurately generate target patterns that fit a target avatar of different size and body type, as they do not account for varying degrees of deformation in body portions, leading to inaccuracies in fitting.
Innovation Solution
An automatic grading method that determines avatar strain ratios between a 3D source and target avatar, maps 3D source garment polygons to target garment polygons, and applies a garment transfer function to deform source patterns into target patterns, while maintaining curvature and sewing line ratios, using optimization algorithms to ensure accurate fitting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If existing grading methods are used to generate target patterns, then the grading process is simple and fast, but the fitting accuracy on target avatar of different size and body type deteriorates
Solution Approach 1:
The patent segments the avatar body into multiple body portions (e.g., torso, limbs, head) and calculates strain ratios separately for each portion. This segmentation allows the system to account for differential deformations in different body regions, improving fitting accuracy while managing complexity through modular processing of each body segment independently.
Solution Approach 2:
The patent applies local quality by determining specific strain ratios for different body portions rather than using a uniform scaling approach. Each body portion receives customized deformation based on its specific strain ratio, allowing the grading method to adapt to local anatomical variations and improve overall fitting accuracy on the target avatar.
2Manufacturing precision
If uniform scaling is applied for grading, then the process is simple and computationally efficient, but the varying deformation in different body portions cannot be accounted for
Solution Approach 1:
The patent changes the scaling parameter from a single uniform scale factor to multiple body portion-specific strain ratios. By calculating and applying different strain ratios for different body portions, the system achieves accurate pattern deformation that reflects actual anatomical variations, improving manufacturing precision while maintaining computational efficiency through systematic parameter management.
3Manufacturing precision
If detailed body portion deformation is accounted for, then the target patterns fit better on target avatar, but the grading method becomes more complex
Solution Approach 1:
The patent introduces an intermediary computational layer that calculates strain ratios based on corresponding points between source and target avatars. This intermediary step translates complex anatomical differences into manageable strain ratio parameters, which then guide the pattern deformation process, achieving better target pattern fitting without overwhelming system complexity.
Data Source
AI summary
Provided is an automatic grading method including calculating a first strain ratio between a three-dimensional (3D) source avatar and a 3D target avatar, determining a mapping relationship between 3D source garment draped over the source avatar and a body portion of the source avatar, converting the source garment into 3D target garment draped over the target avatar, based on the first strain ratio and the mapping relationship, and outputting a two-dimensional (2D) target pattern constituting the target garment.