Matching Items (2)
Description
This thesis surveys and analyzes applications of machine learning techniques to the fields of animation and computer graphics. Data-driven techniques utilizing machine learning have in recent years been successfully applied to many subfields of animation and computer graphics. These include, but are not limited to, fluid dynamics, kinematics, and character modeling. I argue that such applications offer significant advantages which will be pivotal in advancing the fields of animation and computer graphics. Further, I argue these advantages are especially relevant in real-time implementations when working with finite computational resources.
ContributorsSaba, Raphael Lucas (Author) / Foy, Joseph (Thesis director) / Olson, Loren (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Inspired by the great film editor Walter Murch, and his book In the Blink of an Eye, I decided to take a deep dive into understanding one powerful filmmaking technique: seamless transitions. I started by studying the impressive work of professional directors and editors and then applied the information I learned in practice to ultimately boil the technique down to its essence and understand how to make seamless transitions regularly in my own creative work. As film editing is my major and career path, the choice to present the culmination of my study in practice in the form of a video-essay felt natural and appropriate for this project.
ContributorsBaker, Ian Q (Author) / Cedanna, Janaki (Thesis director) / DeNigris, Paul (Committee member) / The New American Film School (Contributor) / Barrett, The Honors College (Contributor)
Created2020-12