Polarization multiplexing for bidirectional imaging - Cula, O.G.; Dana, K.J.; Pai, D.K.; Wang, D. (2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005)
Our goal is to incorporate polarization in appearance-based modeling in an efficient and meaningful way. Polarization has been used in numerous prior studies for separating diffuse and specular reflectance components, but in this work we show that it also can be used to separate surface reflectance contributions from individual light sources. Our approach is called polarization multiplexing and it has significant impact in appearance modeling and bidirectional imaging where the image as a function of illumination direction is needed. Multiple unknown light sources can illuminate the scene simultaneously, and the individual contributions to the overall surface reflectance can be estimated. To develop the method of polarization multiplexing, we use a relationship between light source direction and intensity modulation. Inverting this transformation enables the individual intensity contributions to be estimated. In addition to polarization multiplexing, we show that phase histograms from the intensity modulations can be used to estimate scene properties including the number of light sources.