Accurately measuring the geometry and spatially-varying reflectance of real-world objects is a complex task due to their intricate shapes formed by concave features, hollow engravings and diverse surfaces, resulting in inter-reflection and occlusion when photographed. Moreover, issues like lens flare and overexposure can arise from interference from secondary reflections and limitations of hardware even in professional studios. In this paper, we propose a novel approach using polarized reflectance field capture and a comprehensive statistical analysis algorithm to obtain highly accurate surface normals (within 0.1mm/px) and spatially-varying reflectance data, including albedo, specular separation, roughness, and anisotropy parameters for realistic rendering and analysis. Our algorithm removes image artifacts via analytical modeling and further employs both an initial step and an optimization step computed on the whole image collection to further enhance the precision of per-pixel surface reflectance and normal measurement. We showcase the captured shapes and reflectance of diverse objects with a wide material range, spanning from highly diffuse to highly glossy - a challenge unaddressed by prior techniques. Our approach enhances downstream applications by offering precise measurements for realistic rendering and provides a valuable training dataset for emerging research in inverse rendering. We will release the polarized reflectance fields of several captured objects with this work.

翻译：精确测量真实世界物体的几何形状与空间变化反射率是一项复杂任务，这是由于物体表面常具有由凹形特征、空心雕刻及多样曲面构成的复杂结构，在拍摄时会产生相互反射与遮挡现象。此外，即使在专业摄影棚中，二次反射干扰与硬件限制也可能导致镜头眩光与曝光过度等问题。本文提出一种利用偏振反射场采集与综合统计算法的新方法，以获取高精度表面法向（精度达0.1mm/像素）及包含反照率、镜面反射分离、粗糙度与各向异性参数的空间变化反射率数据，用于真实感渲染与分析。我们的算法通过解析建模消除图像伪影，并采用在完整图像集上计算的初始化步骤与优化步骤，进一步提升逐像素表面反射率与法向测量的精度。我们展示了涵盖高漫反射至高光泽度广泛材质范围的多种物体的采集形状与反射率数据——这一挑战是先前技术未能解决的。本方法通过为真实感渲染提供精确测量数据来增强下游应用，并为逆向渲染的新兴研究提供有价值的训练数据集。我们将随本工作公开若干采集对象的偏振反射场数据。