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虚拟现实场景中的光谱颜色管理。

Spectral Color Management in Virtual Reality Scenes.

机构信息

Department of Computer and Network Systems Engineering, University of Extremadura, E06800 Mérida, Spain.

Department of Physics, University of Extremadura, E06071 Badajoz, Spain.

出版信息

Sensors (Basel). 2020 Oct 3;20(19):5658. doi: 10.3390/s20195658.

DOI:10.3390/s20195658
PMID:33022952
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7582600/
Abstract

Virtual reality has reached a great maturity in recent years. However, the quality of its visual appearance still leaves room for improvement. One of the most difficult features to represent in real-time 3D rendered virtual scenes is color fidelity, since there are many factors influencing the faithful reproduction of color. In this paper we introduce a method for improving color fidelity in virtual reality systems based in real-time 3D rendering systems. We developed a color management system for 3D rendered scenes divided into two levels. At the first level, color management is applied only to light sources defined inside the virtual scene. At the second level, we applied spectral techniques over the hyperspectral textures of 3D objects to obtain a higher degree of color fidelity. To illustrate the application of this color management method, we simulated a virtual version of the Ishihara test for color blindness deficiency detection.

摘要

虚拟现实近年来已经发展得相当成熟。然而,其视觉外观的质量仍有改进的空间。在实时 3D 渲染的虚拟场景中,最难表现的特征之一是色彩逼真度,因为有许多因素会影响色彩的忠实再现。在本文中,我们介绍了一种基于实时 3D 渲染系统的虚拟现实系统中提高色彩逼真度的方法。我们开发了一种针对 3D 渲染场景的颜色管理系统,将其分为两个层次。在第一层,仅对虚拟场景中定义的光源应用颜色管理。在第二层,我们对 3D 对象的高光谱纹理应用光谱技术,以获得更高的色彩逼真度。为了说明这种颜色管理方法的应用,我们模拟了一个用于检测色盲缺陷的石原氏测试的虚拟版本。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/f0ee81ae1a32/sensors-20-05658-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/f9541dcb85ea/sensors-20-05658-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/3f116c607480/sensors-20-05658-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/48de47bc6f43/sensors-20-05658-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/80ed3eacb8c1/sensors-20-05658-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/0da95eda0d66/sensors-20-05658-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/d7bf7ed5fc22/sensors-20-05658-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/56877ee6103d/sensors-20-05658-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/8cae38153699/sensors-20-05658-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/f0ee81ae1a32/sensors-20-05658-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/f9541dcb85ea/sensors-20-05658-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/9b8ff99877b0/sensors-20-05658-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/d44b5f57e63c/sensors-20-05658-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/3f116c607480/sensors-20-05658-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/48de47bc6f43/sensors-20-05658-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/80ed3eacb8c1/sensors-20-05658-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/0da95eda0d66/sensors-20-05658-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/d7bf7ed5fc22/sensors-20-05658-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/56877ee6103d/sensors-20-05658-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/8cae38153699/sensors-20-05658-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0778/7582600/f0ee81ae1a32/sensors-20-05658-g011.jpg

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