Virtual Tailor 3D User Modeling for Custom Garment Fit
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Solution Overview
Problem
Current clothing garments are often ill-fitting for individuals with anatomical measurements that deviate from the average, as they are sized based on average measurements, leading to challenges in finding proper fits and requiring time-consuming and expensive alterations or custom clothing solutions.
Innovation Solution
A method using a communication device application that generates a three-dimensional user model based on user data, matches clothing attributes with human attributes using machine learning techniques, and virtually fits clothing garments on the model, allowing for customized garment production and display, including supervised and unsupervised learning to optimize attribute matching and user feedback integration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If clothing garments are sized based on average anatomical measurements, then mass production and standardization are simplified, but fit accuracy for individuals with non-average measurements deteriorates
Solution Approach 1:
The system changes the parameter approach from fixed standard sizes to dynamic, individualized measurements. It captures precise anatomical data (body shape, proportions, measurements) and uses this to generate customized garment parameters, transforming the manufacturing process from static standardization to adaptive personalization while maintaining digital manufacturing efficiency
Solution Approach 2:
The system creates a digital 3D copy of the user's anatomy and applies virtual tailoring to this copy. Instead of physically altering garments or creating custom physical patterns, it generates a virtual fitted garment model that replicates the ideal fit, allowing physical manufacturing to follow the optimized digital design
2Manufacturing precision
If custom clothing is produced for each individual, then fit accuracy is improved, but production time and cost increase
Solution Approach 1:
The system replaces manual tailoring and physical pattern-making with automated computer vision, machine learning, and digital 3D modeling. The mechanical process of measuring, marking, and altering is substituted by algorithms that automatically generate customized garment designs from captured anatomical data, dramatically reducing production time and labor requirements
Solution Approach 2:
The system performs preliminary digital design and virtual fitting before physical production. It pre-calculates the optimized garment pattern and measurements based on the user's anatomy, allowing the physical manufacturing process to directly produce the final customized garment without time-consuming on-site alterations or iterative adjustments
3Manufacturing precision
If traditional tailoring alterations are performed, then garment fit is improved, but time consumption and labor requirements increase
Solution Approach 1:
The system performs all fit calculations and pattern adjustments in advance during the digital design phase. By pre-determining the exact measurements and pattern modifications needed based on the user's anatomy, it eliminates the need for time-consuming on-site alterations, allowing the garment to be manufactured to the correct fit from the start
Solution Approach 2:
The system substitutes manual tailoring operations with automated digital pattern generation. Instead of having a tailor physically measure and alter a garment, the system uses computer vision and machine learning to automatically calculate and generate the corrected pattern, reducing alteration time from hours to minutes
Data Source
AI summary
Provided is a machine-readable medium storing instructions that when executed by a processor effectuate operations including: receiving, with an application executed by a communication device, a first set of inputs including user data; generating, with the application, a three-dimensional model of the user based on the user data; receiving, with the application, a second set of inputs including a type of clothing garment; generating, with the application, a first set of clothing garments including clothing garments from a database of clothing garments that are the same type of clothing garment; generating, with the application, a second set of clothing garments from the first set of clothing garments based on the user data and one or more relationships between clothing attributes and human attributes; and presenting, with the application, the clothing garments from the second set of clothing garments virtually fitted on the three-dimensional model of the user.