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Modelling human motion with Gaussian processes

Thursday 7th February 2008 - 11:00 to 12:00
INI Seminar Room 2

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.

Presentation Material: 
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons