Introduction to Machine Learning for Computer Graphics


Hall, P.M., 2014. Introduction to Machine Learning for Computer Graphics. In: ACM SIGGRAPH 2014 Courses, SIGGRAPH 2014. ACM.

Related documents:

This repository does not currently have the full-text of this item.
You may be able to access a copy if URLs are provided below.

Official URL:

Related URLs:


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.


Item Type Book Sections
CreatorsHall, P.M.
Related URLs
DepartmentsFaculty of Science > Computer Science
Research CentresMedia Technology Research Centre
ID Code41075


Actions (login required)

View Item