Garment Size Recommendation Engine Using Body Measurement Segmentation
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Solution Overview
Problem
The lack of a standardized sizing system in the fashion industry leads to uncertainty in garment fit for consumers, resulting in unsatisfied purchases and failed sales goals for manufacturers.
Innovation Solution
A computing system that receives body measurements from user devices, uses machine learning to recommend the appropriate size of a garment based on captured images, and communicates this recommendation to the user, incorporating calibrated member training data for improved accuracy over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If brands use a single fit model as the base size and grade up and down to create patterns for each size, then manufacturing efficiency is improved, but garment fit accuracy deteriorates
Solution Approach 1:
The invention segments the sizing problem by creating multiple fit models representing different body shapes and sizes rather than using a single fit model. This segmentation allows the system to capture diverse body types and provide more accurate size recommendations for different consumer groups, thereby improving garment fit accuracy while maintaining manufacturing efficiency through systematic pattern grading from multiple bases.
Solution Approach 2:
The invention changes the parameters by introducing multiple fit models with varying body measurements and characteristics instead of relying on a single base size. This parameter diversification enables the system to match consumers with garments that better suit their specific body types, improving fit accuracy without compromising manufacturing productivity through the use of standardized grading processes from multiple patterns.
2Measurement precision
If the system collects and processes detailed body measurements from multiple images, then size recommendation accuracy is improved, but system complexity increases
Solution Approach 1:
The invention applies universality by using a single multi-functional computing system that performs multiple tasks: capturing images, extracting body measurements, comparing measurements against fit models, and generating size recommendations. This consolidates what could be separate complex systems into one unified platform, improving size recommendation accuracy through comprehensive measurement analysis while managing system complexity through integration rather than multiplication of components.
Solution Approach 2:
The system enables self-service by automatically capturing body measurements from images taken by the consumer using their own device, eliminating the need for manual measurement input or professional fitting services. The computing system autonomously processes the images, extracts measurements, and generates recommendations, thereby improving measurement precision through automated analysis while reducing the operational complexity of manual data collection and processing.
3Adaptability or versatility
If the system uses multiple fit models representing different body shapes, then garment fit for diverse consumers is improved, but data processing requirements increase
Solution Approach 1:
The invention applies preliminary action by pre-establishing a comprehensive database of fit models with detailed body measurements and characteristics before the consumer makes a purchase. This advance preparation allows the system to quickly match consumers with appropriate sizes by comparing their measurements against the pre-organized fit model database, thereby improving adaptability to diverse body types while managing data processing requirements through prior organization and indexing of the fit model data.
Data Source
AI summary
A method implemented by a computing system comprises receiving, by the computing system and from a user device, a subject profile information that specifies a plurality of body measurements associated with one or more images of a subject that are captured by the user device. The computing device receives a selection of a garment, where the garment is associated with a category, a brand, a style, and a plurality of sizes. A sizing recommendation engine of the computing system determines, based on the plurality of body measurements, a particular size of the garment that is associated with the subject profile information. The computing system communicates the particular size to the user device.