“Scattered Data Interpolation for Computer Graphics” by Lewis, Pighin and Anjyo
Conference:
Type(s):
Title:
- Scattered Data Interpolation for Computer Graphics
Presenter(s)/Author(s):
Abstract:
Interpolation is a fundamental topic in computer graphics. While textbooks have generally focused on “regular” interpolation schemes such as B-splines, scattered interpolation approaches also have been a wide variety of applications. These include topics in facial animation, skinning, morphing, rendering, and fluid simulation.
This best-practice guide to scattered data interpolation reviews the major algorithms for scattered interpolation, shows how and where they are applied in a variety of published graphics studies, and compares and contrasts them. The algorithms include Shepard interpolation, Wiener interpolation, Laplace and thin-plate interpolation, radial basis functions (RBFs), moving least squares, and kernel regression. The course summarizes stability and computational properties with a focus on real-time applications and provides some theoretical insights to broaden the course’s engineering perspective.
Additional Information:
Prerequisites
Knowledge of linear algebra at the level required for intermediate or advanced graphics programming. The concluding section of the course requires basic calculus.
