“Machine Learning for Graphics” by Hall
Conference:
Type(s):
Entry Number: 20
Title:
- Machine Learning for Graphics
Course Organizer(s):
Presenter(s)/Author(s):
Abstract:
Description
Computer Graphics is increasingly using techniques from Machine Learning. The trend is motivated by several factors, but the difficulties and expense of modelling is a major driving force. Here ‘modelling’ is used very broadly to include models of reflection (learn the BRDF of a real material), animation (learn the motion of real objects), as well as three-dimensional models (learn to model complex things). Building around a few examples, we will explore the whys and hows of Machine Learning within Computer Graphics. The course will outline the basics of data-driven modelling, introduce the foundations of probability and statistics, describe some useful distributions, and differentiate between ML and MAP problems. The ideas are illustrated using examples drawn from previous SIGGRAPHs; we’ll help non-artists to draw, animate traffic flow from sensor data, and model moving trees from video.
