A Dictionary-Based Approach for Estimating Shape and Spatially-Varying Reflectance
A Dictionary-Based Approach for Estimating Shape and Spatially-Varying Reflectance
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DOI：
10.1109/iccphot.2015.7168363
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发表时间：
2015-03
期刊：
影响因子：
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通讯作者：
Zhuo Hui;Aswin C. Sankaranarayanan
中科院分区：
文献类型：
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作者：
Zhuo Hui;Aswin C. Sankaranarayanan
我们提出了一种根据物体表面法线和空间变化的 BRDF 来估计物体形状和反射率的技术。我们假设在固定视点和变化光照下获得物体的多个图像，即光度立体的设置。假设每个像素处的 BRDF 位于已知 BRDF 字典的非负范围内，我们推导出每像素表面法线和 BRDF 估计框架，该框架既不需要迭代优化技术，也不需要仔细的初始化，这两者都是大多数最先进技术所特有的。我们展示了我们的技术在各种模拟和真实场景中的性能，在这些场景中我们的表现优于竞争方法。
We present a technique for estimating the shape and reflectance of an object in terms of its surface normals and spatially-varying BRDF. We assume that multiple images of the object are obtained under fixed view-point and varying illumination, i.e, the setting of photometric stereo. Assuming that the BRDF at each pixel lies in the non-negative span of a known BRDF dictionary, we derive a per-pixel surface normal and BRDF estimation framework that requires neither iterative optimization techniques nor careful initialization, both of which are endemic to most state-of the-art techniques. We showcase the performance of our technique on a wide range of simulated and real scenes where we outperform competing methods.