SPIDeRS：面向不可见深度与反射率感知的结构化偏振
SPIDeRS: Structured Polarization for Invisible Depth and Reflectance Sensing
AI总结：
SPIDeRS首次利用投影线偏振角图案实现隐蔽的深度、表面法线与反射率感知，通过SLM和偏振相机稳健重建多种材料形状，并对漫反射和环境光鲁棒。
摘要：
我们能否以隐蔽方式捕获形状和反射率？这种能力对视觉、xR、机器人学和人机交互（HCI）中的许多应用领域都很有价值。我们提出了面向不可见深度与反射率感知的结构化偏振（SPIDeRS），这是第一种使用偏振光图案的深度与反射率感知方法。其核心思想是在每个像素处调制投影光的线偏振角（AoLP）。偏振的使用使其不可见，并使我们不仅能恢复深度，还能直接恢复表面法线甚至反射率。我们使用液晶空间光调制器（SLM）和偏振相机实现了SPIDeRS。我们推导了一种新方法，用于从偏振物体外观中稳健地提取投影的结构化偏振图案。我们通过将SPIDeRS应用于多个真实世界物体来评估其有效性。结果表明，我们的方法成功重建了各种材料的物体形状，并且对漫反射和环境光具有鲁棒性。我们还演示了利用恢复的表面法线和反射率进行重新光照。我们相信SPIDeRS为偏振在视觉感知中的应用开辟了一条新途径。
英文摘要：
Can we capture shape and reflectance in stealth? Such capability would be valuable for many application domains in vision, xR, robotics, and HCI. We introduce structured polarization for invisible depth and reflectance sensing (SPIDeRS), the first depth and reflectance sensing method using patterns of polarized light. The key idea is to modulate the angle of linear polarization (AoLP) of projected light at each pixel. The use of polarization makes it invisible and lets us recover not only depth but also directly surface normals and even reflectance. We implement SPIDeRS with a liquid crystal spatial light modulator (SLM) and a polarimetric camera. We derive a novel method for robustly extracting the projected structured polarization pattern from the polarimetric object appearance. We evaluate the effectiveness of SPIDeRS by applying it to a number of real-world objects. The results show that our method successfully reconstructs object shapes of various materials and is robust to diffuse reflection and ambient light. We also demonstrate relighting using recovered surface normals and reflectance. We believe SPIDeRS opens a new avenue of polarization use in visual sensing.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
