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. 

Key words: surface material modeling, spatially varying material, image-based rendering, bidirectional reflectance distribution function, pixel clustering