Material Representation
The goal of this research is to develop representations of measured surface appearance that enable efficient rendering and intuitive editing. This involves developing mathematical models and inference algorithms for representing the types of high-dimensional functions that characterize the way light is scattered at
a material's surface. Our past work has introduced new representations and techniques that achieve compression of an input material necessary to achieve interactive rendering; allow importance sampling in the context of physically-based rendering systems; and enable a human to edit the measured data. More recent work has investigated richer editing metaphors and stroke-based interfaces for material design along with the new Bayesian inference techniques. This research is partially supported by the National Science Foundation through a CAREER grant CCF-0747220 ("The Inverse Shade Tree Framework for Material Acquisition, Analysis, and Design").
Recent Publications
- Interactive Editing of Lighting and Materials using a Bivariate BRDF Representation, Pitchaya Sitthi-Amorn, Fabiano Romeiro, Todd Zickler, Jason Lawrence, Eurographics Symposium on Rendering, June 2010.
- Principles of Appearance Acquisition and Representation, Tim Weyrich, Jason Lawrence, Hendrik P. A. Lensch, Szymon Rusinkiewicz, Todd Zickler. In Foundations and Trends in Computer Graphics and Vision, Vol. 4, No. 2, pp. 75-191, 2008 (appeared in 2009).
- An Empirical BSSRDF Model, Craig Donner, Jason Lawrence, Ravi Ramamoorthi, Toshiya Hachisuka, Henrik Wann Jensen, and Shree Nayar, ACM Transactions on Graphics (Proc. SIGGRAPH), 28(3), August 2009.
- AppWand: Editing Measured Materials using Appearance-Driven Optimization, Fabio Pellacini and Jason Lawrence, ACM Transactions on Graphics (Proc. SIGGRAPH), 26(3), July 2007.
- Efficient Basis Decomposition for Scattered Reflectance Data, R. Peter Weistroffer, Kristen R. Walcott, Greg Humphreys, and Jason Lawrence, Eurographics Symposium on Rendering, June 2007.