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Modelling the Human Eye: A look at statistical and machine learning techniques

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If you have a question about this talk, please contact Mr Simone Parisotto.

Modelling and predicting the complex movements of the human eye when it is presented with an image to observe has been a challenging task for vision researchers, computer scientists, and statisticians. In 2015, the Royal Statistical Society presented a data set of eye movements as a challenge problem to young researchers. Using this data as a foundation, we will present an expository look at a variety of machine learning and statistics techniques in the context of this data. Methods include spatial clustering algorithms, nearest-neighbour classifiers, non-parametric density estimation, mixture models, Bayesian model selection, and (not-quite-hidden) Markov models. There will also be a lot of pretty pictures.

This talk is part of the Cambridge Analysts' Knowledge Exchange series.

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