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Minimal BRDF Sampling for Two-Shot Near-Field Reflectance Acquisition

机译:用于两场近场反射采集的最小BRDF采样

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摘要

We develop a method to acquire the BRDF of a homogeneous flatrnsample from only two images, taken by a near-field perspectiverncamera, and lit by a directional light source. Our method usesrnthe MERL BRDF database to determine the optimal set of lightviewrnpairs for data-driven reflectance acquisition. We develop arnmathematical framework to estimate error from a given set of measurements,rnincluding the use of multiple measurements in an imagernsimultaneously, as needed for acquisition from near-field setups.rnThe novel error metric is essential in the near-field case, where wernshow that using the condition-number alone performs poorly. Werndemonstrate practical near-field acquisition of BRDFs from onlyrnone or two input images. Our framework generalizes to configurationsrnlike a fixed camera setup, where we also develop a simplernextension to spatially-varying BRDFs by clustering the materials.
机译:我们开发了一种方法,该方法仅从两个图像(由近场透视相机拍摄并由定向光源照明)中获取均质平面样品的BRDF。我们的方法使用MERL BRDF数据库确定用于数据驱动的反射率采集的最佳光视图对集合。我们开发了一种数学框架来估计给定测量值中的误​​差,包括在图像中同时使用多个测量值(根据从近场设置中获取的需要)。新颖的误差度量在近场情况下至关重要,其中证明了:仅使用条件编号的效果不佳。演示了仅从一个或两个输入图像中实际获取BRDF的方法。我们的框架可以概括为类似于固定摄像机设置的配置,在此我们还可以通过对材料进行聚类来为空间变化的BRDF开发简单的扩展。

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