Base materials for photometric stereo

Image-based capture of material appearance has been extensively studied, but the quality of the results and generality of the applied methods leave a lot of room for improvement. Most existing methods rely on parametric models of reflectance and require complex hardware systems or accurate geometric models that are not always available or practical. Rather than independently estimating reflectance properties for each surface point, it is common to express the reflectance as a combination of base materials inherent to each particular object or scene. We propose a method for efficient and automatic extraction of base materials in a photometric stereo system. After jointly estimating per-pixel reflectances and refined surface normals using these materials, we can render photo-realistic images of complex objects under novel lighting conditions in real time.