3D Body Model Matching for Personalized Transactions
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Solution Overview
Problem
Conventional electronic transactions for consumer-specific products, such as apparel and footwear, often require multiple interactions and transmit sensitive information, leading to inefficiencies and increased processor and battery usage due to redundant user inputs.
Innovation Solution
A system and method utilizing a mobile device with a processor, 3D user body database, and communication interface to execute personalized transactions by searching for items matching user-specific 3D body information, providing alternatives when no match is found, and facilitating purchasing when a match is identified.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional electronic transactions are used for consumer-specific products, then users can purchase items online, but multiple interactions and redundant user inputs are required, increasing cognitive burden and processor/battery usage
Solution Approach 1:
The system performs preliminary actions by capturing 3D body measurements and creating a digital body model in advance, storing it in a database. This pre-processing eliminates the need for repeated measurements and inputs during subsequent transactions, reducing both cognitive burden and energy consumption.
Solution Approach 2:
The system creates a digital copy (3D body model) of the user's physical characteristics and uses this copy for matching with products. This eliminates the need for the user to repeatedly provide physical inputs, reducing processor usage and battery consumption while simplifying the transaction process.
2Productivity
If conventional electronic transactions are used for consumer-specific products, then users can purchase items online, but multiple interactions and transmission of sensitive information are required, reducing transaction efficiency
Solution Approach 1:
The system performs preliminary actions by capturing 3D body measurements and creating a digital body model in advance, storing it in a database. This pre-processing eliminates the need for repeated measurements and inputs during subsequent transactions, reducing both cognitive burden and energy consumption.
Solution Approach 2:
The system creates a digital copy (3D body model) of the user's physical characteristics and uses this copy for matching with products. This eliminates the need for the user to repeatedly provide physical inputs, reducing processor usage and battery consumption while simplifying the transaction process.
3Measurement precision
If 3D body scanning is implemented for personalized transactions, then item matching accuracy is improved, but device complexity increases
Solution Approach 1:
The system uses a universal 3D body model that can be applied across multiple product categories and vendors. This multi-functional approach allows the same scanning and modeling infrastructure to serve various personalized transaction needs, reducing overall system complexity while maintaining high measurement precision.
Solution Approach 2:
The patent introduces a server-based 3D body model database as an intermediary between the user's mobile device and the vendor systems. This intermediary handles the complex 3D scanning, processing, and storage operations, allowing the mobile device to remain relatively simple while still achieving high measurement precision through the centralized infrastructure.
Data Source
AI summary
The disclosed systems, components, methods, and processing steps are directed to determining user-item fit characteristics of an item for a user body part by accessing a three-dimensional (3D) reconstructed model of the user body part, accessing information about one or more 3D reference models of the item, the information for each 3D reference model including respective dimensional measurement, spatial, and geometrical attributes, performing a 3D matching process based on the 3D reconstructed model and the accessed information of the one or more 3D reference models to determine a best-fitting 3D reference model from the one or more 3D reference models, integrating the best-fitting 3D reference model with the 3D reconstructed model to provide a 3D best fit representation and displaying the 3D best fit representation along with visual indications of user-item fit characteristics.


