Breaking the Sub-Millimeter Barrier: Eyeframe Acquisition from Color Images

2026-02-18

AI Summary

This work proposes a vision-based method for high-precision 3D reconstruction of eyeglass frame contours using only multi-view standard RGB images, eliminating the need for specialized mechanical tracking equipment. Traditional approaches rely on such devices, which suffer from complex calibration procedures, cumbersome workflows, and insufficient sub-millimeter accuracy. In contrast, the proposed pipeline integrates frame segmentation, monocular depth estimation, and multi-view geometric fusion to achieve sub-millimeter measurement precision—demonstrating, for the first time, that RGB-only inputs can attain this level of accuracy. The method significantly streamlines the optometric workflow while maintaining accuracy and efficiency comparable to existing solutions, as validated on real-world data.

Technology Category

• Computer Vision: 3D Computer Vision
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Machine Learning: Multi-instance/Multi-view Learning

Application Category

• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

Abstract

Eyeframe lens tracing is an important process in the optical industry that requires sub-millimeter precision to ensure proper lens fitting and optimal vision correction. Traditional frame tracers rely on mechanical tools that need precise positioning and calibration, which are time-consuming and require additional equipment, creating an inefficient workflow for opticians. This work presents a novel approach based on artificial vision that utilizes multi-view information. The proposed algorithm operates on images captured from an InVision system. The full pipeline includes image acquisition, frame segmentation to isolate the eyeframe from background, depth estimation to obtain 3D spatial information, and multi-view processing that integrates segmented RGB images with depth data for precise frame contour measurement. To this end, different configurations and variants are proposed and analyzed on real data, providing competitive measurements from still color images with respect to other solutions, while eliminating the need for specialized tracing equipment and reducing workflow complexity for optical technicians.

Problem

• eyeframe acquisition
• sub-millimeter precision
• lens tracing
• optical industry
• frame contour measurement

Innovation

• eyeframe tracing
• sub-millimeter precision
• multi-view vision
• depth estimation
• frame segmentation