Visual Computing

We present a theoretical analysis of error of many combinations of Monte Carlo estimators used in image synthesis.

We present a solution for generating high-quality stereo panoramas at megapixel resolutions.

This paper provides measurement and fitting methods that allow nonlinear models to be fit to the observed deformation of a particular cloth sample.

This project presents a finer scale technique to demonstrate for the first time the processing of densely leafed foliage – computation of 3D structure, plus extraction of statistics for leaf shape and the configuration of neighboring leaves.

We present a method for consistent automatic transfer of edits applied to one image to many other images of the same object or scene.

In this project, we developed a model of internal friction based on a reparameterization of Dahl’s model and validated that this model provides a good match to important features of cloth hysteresis even with a minimal set of parameters.

We present a technique for adding fine-scale details and expressiveness to low-resolution art-directed facial performances, such as those created manually using a rig, via marker-based capture, by fitting a morphable model to a video, or through Kinect reconstruction using recent faceshift technology.

We propose a complete process for augmenting physical avatars using projector-based illumination, significantly increasing their expressiveness.

We propose second-order Taylor expansion from cache points, which results in more accurate irradiance reconstruction.

We organize this complex and active research area in a structure tailored to academic researchers, graduate students, and industry professionals alike.