Modelling human motion with Gaussian processes
Seminar Room 2, Newton Institute Gatehouse
Human motion capture data is a high dimensional time series. Probabilistic modelling of this high dimensional data is affected by problems of dimensionality. In this talk we will show how Gaussian processes can be used to reduce the dimensionality and construct accurate models of human motion. The main application will be three dimensional human pose reconstruction from images.