| 基于像素聚类的空间变化表面材质建模 |
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| 作者姓名： | 冯洁 李博 周秉锋 |
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| 作者单位： | 北京大学王选计算机研究所,北京100871;大数据分析与应用技术国家工程实验室,北京100871;北京大学王选计算机研究所,北京100871 |
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| 基金项目： | 国家重点研发计划项目(2018YFB1403900);国家自然科学基金项目(61872014)。 |
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| 摘 要： | 针对空间变化表面材质的反射属性提出了一种基于图像的轻量化建模方法。仅需利用消费级手
机，在环境光和点光源下分别对平面材质样本拍摄一幅图像，即可计算重建其表面的双向反射分布函数
(svBRDFs)参数图、法向量图、切向量图等材质属性。其中对 BRDF 参数的拟合采用了一种基于像素聚类的策
略，即假定具有相似外观和结构特征的像素属于同种材质、共用一组参数，从而大幅降低参数拟合的难度。
在此基础上，通过一种新的迭代多步优化方案对全局和空间变化的参数进行拟合，产生高分辨率的 BRDF 参
数纹理图。该方法不依赖特殊设备，也无需采集海量数据，就能够为包括金属材质、各向异性材质等在内的
多种类表面材质产生高质量的 BRDF 参数图，以及高真实感的基于物理的绘制结果，因此更易于实现和应用。
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| 关 键 词： | 表面材质建模 空间变化材质 基于图像的绘制 双向反射分布函数 像素聚类 |
A svBRDF modeling pipeline using pixel clustering |
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| Authors: | FENG Jie LI Bo ZHOU Bing-feng |
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| Affiliation: | 1. Wangxuan Institute of Computer Technology, Peking University, Beijing 100871, China;
2. National Engineering Laboratory for Big Data Analysis and Applications, Beijing 100871, China |
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| Abstract: | We presented a lightweight pipeline for modeling spatially varying bidirectional reflectance distribution functions(svBRDFs)of planar materials,which only required a mobile phone for data acquisition.With a minimum of two photos under an ambient and a point light source,the proposed pipeline produced svBRDF parameters,a normal map,and a tangent map for the material sample.The BRDF fitting was achieved via a pixel clustering strategy to reduce the complexity,namely,the pixels with similar appearance and structural characteristics were assumed to be the same material.Then,with a multi-stage optimization scheme,the parameters were fitted and formed a group of high-resolution BRDF texture maps.This method was not reliant on special equipment or massive data collection.The result shows that the proposed method is easy-to-use and capable of producing high-quality BRDF textures for a wide range of materials,including metallic or anisotropic materials. |
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| Keywords: | surface material modeling spatially varying material image-based rendering bidirectional reflectance distribution function pixel clustering |
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