用彩色图像实现亚毫米级镜框测量，无需专用设备。
Breaking the Sub-Millimeter Barrier: Eyeframe Acquisition from Color Images
- 基于多视角视觉，融合图像与深度信息进行镜框轮廓重建。
- 在真实数据上实现亚毫米级精度，优于传统机械测量方法。
- 适合光学验配师快速获取精准镜框数据，简化工作流程。
镜框轮廓追踪是光学行业中的关键环节，需达到亚毫米级精度以确保镜片适配和最佳视力矫正。传统追踪依赖机械工具，需精确对位与校准，耗时且需额外设备，导致验光师工作流程效率低下。本文提出一种基于人工视觉的新方法，利用InVision系统采集的多视角图像。完整流程包括图像获取、镜框分割以分离背景、深度估计获得三维空间信息，以及多视角处理，将分割后的RGB图像与深度数据融合，实现高精度镜框轮廓测量。通过多种配置与变体在真实数据上的分析，该方法仅使用静态彩色图像即可达成媲美现有方案的测量精度，同时省去专用追踪设备，显著降低光学技师的工作复杂度。
原文摘要 · Abstract (English)
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.
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