Tailoring Platform for Private On-Device 3D Body Scanning
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Solution Overview
Problem
Existing body scanning systems face significant disadvantages in terms of privacy, compliance, and performance due to the upload of sensitive user information to the cloud and reliance on limited cloud-based GPU resources.
Innovation Solution
A tailoring platform that performs body scanning and measurement on a user device using depth sensors, LiDAR sensors, and AI neural engines, generating a 3D point cloud without uploading data to the cloud, ensuring privacy and utilizing local GPU resources for enhanced performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If body scanning data is uploaded to the cloud for processing, then processing power and computational resources are improved, but user privacy and data security deteriorate
Solution Approach 1:
Instead of uploading data to the cloud for processing, the patent inverts the approach by bringing the processing power to the data through on-device machine learning models. The body scanning data is processed locally on the user's device using embedded neural networks, eliminating the need to transmit sensitive information to external servers while still achieving accurate 3D body model generation and garment size recommendations.
2Power
If cloud-based GPU resources are used for body scanning processing, then computational capability is improved, but system dependency and response time deteriorate
Solution Approach 1:
The patent implements self-service by equipping user devices with on-device machine learning capabilities that can independently process body scanning data without requiring external cloud resources. The embedded neural networks perform all necessary computations locally, from generating depth maps to creating 3D body models and recommending garment sizes, enabling the system to serve itself without external computational dependency.
3Ease of operation
If sensitive user information is stored in the cloud, then data accessibility is improved, but security compliance and user trust deteriorate
Solution Approach 1:
The patent extracts the sensitive user information from the cloud storage model entirely. By processing and analyzing body scanning data locally on the user's device, the system eliminates the need to store, transmit, or access sensitive personal information through external cloud services. Only anonymized or aggregated results (such as garment size recommendations) are retained, while the raw biometric data remains exclusively on the user's device.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables secure, accurate, and efficient garment sizing recommendations without exposing sensitive data, providing immediate user feedback and infinite scalability, while maintaining privacy and compliance with data protection regulations.
Implementation Method 1
generating the one or more depth maps of the body using light detection and ranging (LiDAR)
Data Source
AI summary
Embodiments generally relate to a tailoring platform. In some embodiments, a method includes scanning a body of a user using a camera device, where the scanning captures images of the body from a predetermined pattern of perspectives. The method further includes computing one or more depth maps of the body based on the movement of the camera device. The method further includes constructing a three-dimensional (3D) point cloud that models the body based at least in part on the one or more depth maps. The method further includes identifying candidate garments for the user based on the 3D point cloud and one or more garment selection policies.