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

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Détails bibliographiques
Auteurs principaux:	Guzmán, Manel, Agudo, Antonio
Format:	Preprint
Publié:	2026
Sujets:	Computer Vision and Pattern Recognition
Accès en ligne:	Acceder al recurso
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_version_	1866908839518928896
author	Guzmán, Manel Agudo, Antonio
author_facet	Guzmán, Manel Agudo, Antonio
contents	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.
format	Preprint
id	arxiv_https___arxiv_org_abs_2602_16281
institution	arXiv
publishDate	2026
record_format	arxiv
spellingShingle	Breaking the Sub-Millimeter Barrier: Eyeframe Acquisition from Color Images Guzmán, Manel Agudo, Antonio Computer Vision and Pattern Recognition 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.
title	Breaking the Sub-Millimeter Barrier: Eyeframe Acquisition from Color Images
topic	Computer Vision and Pattern Recognition
url	https://arxiv.org/abs/2602.16281

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