Principles of Appearance Acquisition and Representation
By Tim Weyrich, Princeton University, USA and University College London, UK, tweyrich@cs.princeton.edu | Jason Lawrence, University of Virginia, USA, jdl@cs.virginia.edu | Hendrik P. A. Lensch, Ulm University, Institute for Media Informatics, Germany, hendrik.lensch@uni-ulm.de | Szymon Rusinkiewicz, Princeton University, USA, smr@cs.princeton.edu | Todd Zickler, Harvard University, USA, zickler@eecs.harvard.edu
Abstract
Algorithms for scene understanding and realistic image synthesis require accurate models of the way real-world materials scatter light. This study describes recent work in the graphics community to measure the spatially- and directionally-varying reflectance and subsurface scattering of complex materials, and to develop efficient representations and analysis tools for these datasets. We describe the design of acquisition devices and capture strategies for reflectance functions such as BRDFs and BSSRDFs, efficient factored representations, and a case study of capturing the appearance of human faces.
Principles of Appearance Acquisition and Representation
Algorithms for scene understanding and realistic image synthesis require accurate models of the way real-world materials scatter light. Principles of Appearance Acquisition and Representation presents an introduction to appearance capture and suitable representations, together with a description of selected work that measures the spatially- and directionally-varying reflectance and subsurface scattering properties of complex materials. It covers the basic principles of how materials are described, how the appearance of real-world objects may be measured, and how a knowledge of appearance aids in a variety of applications.
Principles of Appearance Acquisition and Representation is an ideal reference for students, researchers and professionals needing a primer on the topic. It can also be used as a basis for a short course on the topic, as it concludes with a case study on appearance acquisition of human faces and an extensive bibliography of over 200 references.
