Computer Vision Eyewear Sizing for Pupil and Frame Measurement
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Solution Overview
Problem
The challenge of accurately determining eyewear specifications, including pupil and frame dimensions, for online eyewear purchases without physical try-on, is difficult due to the lack of effective computer vision techniques for analyzing user images.
Innovation Solution
A computer vision process involving image preprocessing, facial detection, eyewear edge and pupil localization, and frame dimension computation using neural networks and edge detection algorithms to generate precise eyewear specifications from user images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If computer vision techniques are used to determine eyewear specifications from images, then the convenience of online eyewear purchasing is improved, but the measurement precision of pupil and frame dimensions deteriorates due to lack of physical contact
Solution Approach 1:
The patent introduces an intermediary optical system consisting of a camera lens and image processing algorithms that mediates between the user's face and the eyewear specification data. The system uses the camera as an intermediary tool to capture facial features and eyewear positions, then applies computational methods to extract precise measurements without physical contact, thus maintaining convenience while improving measurement accuracy.
Solution Approach 2:
The system changes the parameter of measurement from direct physical contact to indirect optical measurement. By transforming the measurement approach from tactile (requiring physical try-on) to optical (using image analysis), the system enables online purchasing convenience while maintaining measurement capability through mathematical parameter extraction from images.
2Measurement precision
If traditional brick-and-mortar store try-on method is used, then the measurement precision of eyewear fit is improved, but the loss of time for purchasing increases due to travel and fitting requirements
Solution Approach 1:
The patent creates a digital copy of the user's face and eyewear configuration through image capture and processing. Instead of requiring physical presence in a store, the system captures an image copy that contains all necessary geometric information, processes it to extract measurements, and uses these measurements to determine eyewear fit accuracy, thereby eliminating travel time while maintaining measurement precision.
Solution Approach 2:
The system replaces the mechanical process of physical try-on with an optical and computational process. The camera-based imaging system and image processing algorithms substitute for the mechanical act of physically placing frames on the face and adjusting them, achieving the same measurement objective without the time-consuming physical interaction.
3Productivity
If image processing algorithms are implemented for eyewear analysis, then the productivity of online eyewear customization is improved, but the device complexity increases due to multiple detection steps
Solution Approach 1:
The patent segments the complex image analysis task into distinct functional modules: facial feature detection, eyewear edge detection, pupil location identification, and measurement calculation. Each module performs a specific function and can be independently optimized, which manages the overall system complexity while enabling high-speed processing through parallel or sequential execution of specialized sub-routines.
Data Source
AI summary
Provided is a process for generating specifications for lenses of eyewear based on locations of extents of the eyewear determined through a pupil location determination process. Some embodiments capture an image and determine, using computer vision image recognition functionality, the pupil locations of a human's eyes based on the captured image depicting the human wearing eyewear.