Introduction to Machine Learning for Computer Graphics

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. 2014 Copyright held by the Owner/Author.