Pupillary Distance Measurement Using 2D and 3D Depth Maps
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Solution Overview
Problem
Current methods for measuring pupillary distance (PD) are inaccurate, cumbersome, and resource-intensive, often requiring human intervention and can violate social distancing guidelines, leading to discomfort and inefficiencies in eyewear fitting and e-commerce processes.
Innovation Solution
A system and method using image processing algorithms to localize pupils in 2D images and 3D data, calculating PD with improved accuracy and convenience, allowing for contactless measurements that can be stored for virtual try-on and product recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional PD measurement methods (ruler, corneal reflection pupillometer) are used, then PD measurement can be obtained, but measurement precision and reliability are poor due to human error and calibration issues
Solution Approach 1:
The patent replaces manual mechanical measurement methods (ruler alignment, corneal reflection pupillometer) with an automated image processing system that uses 2D images and 3D depth maps to calculate PD. This substitution eliminates human error in measurement and calculation, providing consistent and reliable results through algorithmic processing rather than manual intervention.
Solution Approach 2:
The patent creates a digital copy of the subject's facial features through image capture and 3D depth mapping. By working with digital representations rather than physical measurements, the system can accurately locate pupils and calculate PD without the errors inherent in physical ruler-based methods, improving both precision and reliability.
2Ease of operation
If corneal reflection pupillometer is used for PD measurement, then PD can be measured, but the method requires close proximity between subject and measurer, violating social distancing guidelines
Solution Approach 1:
The patent uses digital image copying technology to capture facial features from a distance. By creating and processing digital representations of the subject's face through 2D images and 3D depth maps, the system eliminates the need for close physical contact, enabling contactless PD measurement that complies with social distancing requirements.
Solution Approach 2:
The patent replaces the mechanical corneal reflection pupillometer with an optical-digital system using cameras and image processing algorithms. This substitution allows measurement to be performed remotely through image capture and computational analysis, eliminating the need for close proximity between measurer and subject.
3Productivity
If manual PD measurement with ruler is used, then PD can be obtained, but the method is cumbersome and time-consuming requiring subject positioning and manual alignment
Solution Approach 1:
The patent enables the measurement system to automatically perform all operations without manual intervention. The image processing algorithms autonomously locate pupils, calculate distances, and generate PD measurements, eliminating the need for operators to manually position rulers or align measurement tools, thereby dramatically improving efficiency and convenience.
Solution Approach 2:
The patent replaces manual mechanical measurement operations with automated computational processes. Image processing algorithms automatically identify facial features and calculate PD, substituting the cumbersome manual ruler-based method with an efficient digital system that requires minimal user input and delivers rapid results.
4Adaptability or versatility
If e-commerce customers submit photos for remote PD measurement, then PD can be obtained without store visit, but the method lacks accuracy due to variable photo quality and processing challenges
Solution Approach 1:
The patent transitions from 2D photo analysis to 3D depth map processing for PD measurement. By incorporating third-dimensional depth information, the system overcomes the limitations of flat image processing, achieving accurate pupil localization and PD calculation even with photos taken in various e-commerce settings, thereby maintaining precision while enabling remote measurement.
Solution Approach 2:
The patent replaces manual photo processing methods with automated image and depth map processing algorithms. These computational methods systematically analyze facial features and calculate PD, eliminating the variability and errors associated with manual processing of e-commerce customer photos while maintaining adaptability to different submission formats.
Data Source
AI summary
A method of operating a pupillary distance system is disclosed. The method comprises the steps of capturing, with at least one camera of the pupillary distance system a 2D image and a corresponding 3D depth map of a face of a subject. A determination of pupil localization information is made using the 2D image and corresponding 3D depth map. The pupil location is further refined based on the pupil localization information. Pupil center coordinates are determined and the pupillary distance is calculated for a subject between centers of each pupil. Processes and uses thereof are also disclosed.