Physically-Based Shading at Disney

Following our success with physically-based hair shading on Tangled [27], we began considering physicallybased shading models for a broader range of materials. With the physically-based hair model, we were able to achieve a great degree of visual richness while maintaining artistic control. However, it proved challenging to integrate the lighting of the hair with the rest of the scene which had still used traditional “ad-hoc” shading models and punctual lights. For subsequent films we wanted to increase the richness of all of our materials while making lighting responses more consistent between materials and environments and also wanted to improve artist productivity through the use of simplified controls. When we began our investigation it wasn’t obvious which models to use or even how physicallybased we wanted to be. Should we be perfectly energy conserving? Should we favor physical parameters like index-of-refraction? For diffuse, Lambert seemed to be the accepted norm, while specular seemed to get most of the attention in the literature. Some models such as Ashikhmin-Shirley (2000) [3] aimed to be intuitive and practical while physically plausible, while others such as He et al. (1991) [12] provided a more comprehensive physical model. Still others aimed at improved data fitting [15, 14, 22, 17, 4], but few of these are appropriate for direct manipulation. We could have implemented several models and let the artists choose and combine them, but then we’d have been back to the parameter explosion we were trying to get away from. One study of a large variety of measured materials was Ngan et al. (2005) [21] which compared five popular models. Some models fared better than others overall, but interestingly, there was a strong correlation between the models’ performances – some materials were well represented by all the models, and for others, no model proved suitable. Adding an additional specular lobe helped in only a few of the cases. This begs the question, what is not being represented in the difficult materials? To answer this question and to evaluate BRDF models more intuitively we developed a new BRDF viewer that could display and compare both measured and analytic BRDFs. We discovered new, intuitive ways to view measured BRDF data and we found interesting features in the measured materials that weren’t well-represented by known models. In these course notes we will share observations from studying measured materials along with insights we’ve gleaned about which models fit the measured data and where they fall short. We will then present our new model which is now being used on all current productions. We will also describe our experience of adopting this new model in production and discuss how we were able to add the right level of artistic control while preserving simplicity and robustness.