Using physically Based Rendering to Benchmark Structured Light Scanners
Using physically Based Rendering to Benchmark Structured Light Scanners
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使用基于物理的渲染对结构光扫描仪进行基准测试
DOI：
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发表时间：
2014
期刊：
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通讯作者：
Cláudio T. Silva
中科院分区：
文献类型：
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作者：
Esdras Medeiros;Harish Doraiswamy;M. Berger;Cláudio T. Silva
结构光扫描在3D获取中无处不在。它能够在各种具有挑战性的场景条件下以低成本捕捉高几何细节。近期的方法在存在由全局光照引起的伪影（如多次反射和次表面散射）以及由投影仪散焦导致的缺陷时表现出了鲁棒性。然而，对于比较各种方法而言，由于获取真实数据存在困难，结构光方案的定量评估受到阻碍，导致对这些方法在各种形状、材料和光照配置下的理解不足。在本文中，我们提出了一个基准来研究在存在由场景的上述特性导致的误差时结构光算法的性能。为此，我们构建了一个合成结构光扫描仪，它使用先进的基于物理的渲染技术来模拟点云获取过程。我们表明，在与真实扫描仪相似的条件下，我们的合成扫描仪能够复现真实扫描仪输出中发现的相同伪影。使用这个合成扫描仪，我们对四种不同的结构光技术——格雷码图案、微相移、集成码和非结构光扫描进行了定量评估。在各种场景下进行的评估表明，没有一种方法能够充分处理所有误差源——每种方法都适用于解决不同的误差源。
Structured light scanning is ubiquituous in 3D acquisition. It is capable of capturing high geometric detail at a low cost under a variety of challenging scene conditions. Recent methods have demonstrated robustness in the presence of artifacts due to global illumination, such as inter‐reflections and sub‐surface scattering, as well as imperfections caused by projector defocus. For comparing approaches, however, the quantitative evaluation of structured lighting schemes is hindered by the challenges in obtaining ground truth data, resulting in a poor understanding for these methods across a wide range of shapes, materials, and lighting configurations. In this paper, we present a benchmark to study the performance of structured lighting algorithms in the presence of errors caused due to the above properties of the scene. In order to do this, we construct a synthetic structured lighting scanner that uses advanced physically based rendering techniques to simulate the point cloud acquisition process. We show that, under conditions similar to that of a real scanner, our synthetic scanner replicates the same artifacts found in the output of a real scanner. Using this synthetic scanner, we perform a quantitative evaluation of four different structured lighting techniques – gray‐code patterns, micro‐phase shifting, ensemble codes, and unstructured light scanning. The evaluation, performed on a variety of scenes, demonstrate that no one method is capable of adequately handling all sources of error – each method is appropriate for addressing distinct sources of error.