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从头部特征预测视野边界。

Predicting visual field boundaries from head features.

作者信息

Nakade Uday, Spitschan Manuel

出版信息

J Opt Soc Am A Opt Image Sci Vis. 2025 Jun 1;42(6):C19-C26. doi: 10.1364/JOSAA.551858.

DOI:10.1364/JOSAA.551858
PMID:40792929
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12310551/
Abstract

Light exposure profoundly affects human physiology, including circadian rhythms and hormonal regulation. Current methods to assess light exposure often ignore anatomical factors that influence how much light reaches the retina. This study introduces a novel simulation pipeline to model visual field (VF) boundaries as a function of head anatomy. Using the parametric ICT Face Model and the Mitsuba 3 rendering engine, we generated diverse 3D head shapes and simulated light interactions to predict VF boundaries. The results reveal significant variability in VF boundaries, influenced by anatomical features such as the nose, cheeks, and eyebrows. This leads to differences in projected solid angles of the VF of up to 18.7%. This study highlights the importance of individual approaches in estimating light exposure.

摘要

光照对人体生理有深远影响,包括昼夜节律和激素调节。当前评估光照的方法往往忽略了影响到达视网膜光线量的解剖学因素。本研究引入了一种新颖的模拟流程,将视野(VF)边界建模为头部解剖结构的函数。利用参数化ICT面部模型和Mitsuba 3渲染引擎,我们生成了多样的3D头部形状并模拟光线相互作用以预测VF边界。结果显示,受鼻子、脸颊和眉毛等解剖特征影响,VF边界存在显著差异。这导致VF投影立体角的差异高达18.7%。本研究强调了个体方法在估计光照方面的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/d309200253e1/josaa-42-6-C19-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/25ad075f73a0/josaa-42-6-C19-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/f9165cb05e58/josaa-42-6-C19-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/4f7f38a49cb8/josaa-42-6-C19-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/0c95cc3c2184/josaa-42-6-C19-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/64d32e4313eb/josaa-42-6-C19-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/0526a90dd8b9/josaa-42-6-C19-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/65c5b6b4d770/josaa-42-6-C19-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/da45d0267e95/josaa-42-6-C19-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/565291d580c8/josaa-42-6-C19-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/fa0fb244a433/josaa-42-6-C19-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/d309200253e1/josaa-42-6-C19-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/25ad075f73a0/josaa-42-6-C19-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/f9165cb05e58/josaa-42-6-C19-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/4f7f38a49cb8/josaa-42-6-C19-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/0c95cc3c2184/josaa-42-6-C19-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/64d32e4313eb/josaa-42-6-C19-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/0526a90dd8b9/josaa-42-6-C19-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/65c5b6b4d770/josaa-42-6-C19-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/da45d0267e95/josaa-42-6-C19-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/565291d580c8/josaa-42-6-C19-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/fa0fb244a433/josaa-42-6-C19-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb2/12310551/d309200253e1/josaa-42-6-C19-g011.jpg

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