Covariance functions
Share this post
Using a Gaussian Process model to model the shape variations within a shape family, we have two parameters to characterise what constitutes a likely shape: the mean function and the covariance function.
In this video we discuss the mathematical properties of a valid covariance function and show how we can define interesting covariance functions for modelling shapes, even when we have no example shapes available to learn the covariance function from data. This knowledge will greatly enhance our modelling ability and allows us to overcome limitations of classical shape models.
Share this post
Statistical Shape Modelling: Computing the Human Anatomy
Statistical Shape Modelling: Computing the Human Anatomy
Our purpose is to transform access to education.
We offer a diverse selection of courses from leading universities and cultural institutions from around the world. These are delivered one step at a time, and are accessible on mobile, tablet and desktop, so you can fit learning around your life.
We believe learning should be an enjoyable, social experience, so our courses offer the opportunity to discuss what you’re learning with others as you go, helping you make fresh discoveries and form new ideas.
You can unlock new opportunities with unlimited access to hundreds of online short courses for a year by subscribing to our Unlimited package. Build your knowledge with top universities and organisations.
Learn more about how FutureLearn is transforming access to education
Register to receive updates

Create an account to receive our newsletter, course recommendations and promotions.
Register for free