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使用消费级硬件快速获取材料外观

Rapid material appearance acquisition using consumer hardware.

作者信息

Filip Jiří, Vávra Radomír, Krupička Mikuláš

机构信息

Institute of Information Theory and Automation of the ASCR, Prague 182 08 , Czech Republic.

出版信息

Sensors (Basel). 2014 Oct 22;14(10):19785-805. doi: 10.3390/s141019785.

Abstract

A photo-realistic representation of material appearance can be achieved by means of bidirectional texture function (BTF) capturing a material's appearance for varying illumination, viewing directions, and spatial pixel coordinates. BTF captures many non-local effects in material structure such as inter-reflections, occlusions, shadowing, or scattering. The acquisition of BTF data is usually time and resource-intensive due to the high dimensionality of BTF data. This results in expensive, complex measurement setups and/or excessively long measurement times. We propose an approximate BTF acquisition setup based on a simple, affordable mechanical gantry containing a consumer camera and two LED lights. It captures a very limited subset of material surface images by shooting several video sequences. A psychophysical study comparing captured and reconstructed data with the reference BTFs of seven tested materials revealed that results of our method show a promising visual quality. Speed of the setup has been demonstrated on measurement of human skin and measurement and modeling of a glue dessication time-varying process. As it allows for fast, inexpensive, acquisition of approximate BTFs, this method can be beneficial to visualization applications demanding less accuracy, where BTF utilization has previously been limited.

摘要

通过双向纹理函数(BTF)可以实现对材料外观的逼真呈现,该函数能够捕捉材料在不同光照、观察方向和空间像素坐标下的外观。BTF能够捕捉材料结构中的许多非局部效应,如相互反射、遮挡、阴影或散射。由于BTF数据的高维度性,BTF数据的采集通常需要耗费大量时间和资源。这导致测量设置昂贵、复杂,和/或测量时间过长。我们提出了一种基于简单、经济的机械龙门架的近似BTF采集设置,该龙门架包含一台消费级相机和两个LED灯。它通过拍摄几个视频序列来捕捉材料表面图像的一个非常有限的子集。一项将捕获和重建的数据与七种测试材料的参考BTF进行比较的心理物理学研究表明,我们方法的结果显示出了有前景的视觉质量。该设置的速度已在人体皮肤测量以及胶水干燥时变过程的测量和建模中得到了证明。由于它能够快速、廉价地获取近似BTF,因此该方法对于要求较低精度的可视化应用可能是有益的,在这些应用中,BTF的使用此前一直受到限制。

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