In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
We introduce a novel parametric BRDF model that can
accurately encode a wide variety of real-world isotropic
BRDFs with a small number of parameters. The key observation
we make...
A goal of image-based rendering is to synthesize as realistically as possible man made and natural objects. This paper presents a method for image-based modeling and rendering of ...
Melissa L. Koudelka, Peter N. Belhumeur, Sebastian...
Standard practices in background modeling learn a separate model for every pixel in the image. However, in dynamic scenes the connection between an observation and the place where...
Formal languages for probabilistic modeling enable re-use, modularity, and descriptive clarity, and can foster generic inference techniques. We introduce Church, a universal langu...
Noah Goodman, Vikash K. Mansinghka, Daniel M. Roy,...