We propose a method for retargeting measured materials, where a source measured material is edited by applying the reflectance functions of a template measured dataset. The resulting dataset is a material that maintains the spatial patterns of the source dataset, while exhibiting the reflectance behaviors of the template. Compared to editing materials by subsequent selections and modifications, retargeting shortens the time required to achieve a desired look by directly using template data, just as color transfer does for editing images. With our method, users have to just mark corresponding regions of source and template with rough strokes, with no need for further input.

This paper introduces AppWarp, an algorithm that achieves retargeting as a user-constrained, appearance-space warping operation, that executes in tens of seconds. Our algorithm is independent of the measured material representation and supports retargeting of analytic and tabulated BRDFs as well as BSSRDFs. In addition, our method makes no assumption of the data distribution in appearance-space nor on the underlying correspondence between source and target. These characteristics make AppWarp the first general formulation for appearance retargeting. We validate our method on several types of materials, including leaves, metals, waxes, woods and greeting cards. Furthermore, we demonstrate how retargeting can be used to enhance diffuse texture with high quality reflectance.

The construction of polygonal meshes remains a complex task in Computer Graphics, taking tens of thousands of individual operations over several hours of modeling time. The complexity of modeling in terms of number of operations and time makes it difficult for artists to understand all details of how meshes are constructed. We present MeshFlow, an interactive system for visualizing mesh construction sequences. MeshFlow hierarchically clusters mesh editing operations to provide viewers with an overview of the model construction while still allowing them to view more details on demand. We base our clustering on an analysis of the frequency of repeated operations and implement it using substituting regular expressions. By filtering operations based on either their type or which vertices they affect, MeshFlow also ensures that viewers can interactively focus on the relevant parts of the modeling process. Automatically generated graphical annotations visualize the clustered operations. We have tested MeshFlow by visualizing five mesh sequences each taking a few hours to model, and we found it to work well for all. We have also evaluated MeshFlow with a case study using modeling students. We conclude that our system provides useful visualizations that are found to be more helpful than video or document-form instructions in understanding mesh construction.

In computer cinematography, artists routinely use non-physical lighting models to achieve desired appearances. This paper presents BendyLights, a non-physical lighting model where light travels nonlinearly along splines, allowing artists to control light direction and shadow position at different points in the scene independently. Since the light deformation is smoothly defined at all world-space positions, the resulting non-physical lighting effects remain spatially consistent, avoiding the frequent incongruences of many non-physical models. BendyLights are controlled simply by reshaping splines, using familiar interfaces, and require very few parameters. BendyLight control points can be keyframed to support animated lighting effects. We demonstrate BendyLights both in a real-time rendering system for editing and a production renderer for final rendering, where we show that BendyLights can also be used with global illumination.