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Motion Commotion: Using Hidden Markov Models in Gesture Recognition

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If you have a question about this talk, please contact John Wickerson .

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The challenge of classifying large and confusing amounts of data is an ever-present challenge in today’s society, as cheap networks and sensors become increasingly available. Hidden Markov Models (HMM’s) represent an easy to understand, yet provably powerful way of modelling time-varying processes. In my presentation, I will introduce the concept of the HMM , outline a number of associated algorithms, and explain the role of HMM ’s in gesture recognition – particularly in my Part II project. Finally, I will apologise for the terrible catchphrase in the title.

This talk is part of the Churchill CompSci Talks series.

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FW11, William Gates Building. Zoom link: https://cl-cam-ac-uk.zoom.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&from=addon Hybrid: in-person in Cambridge & online via Teams Maxwell Centre, West Cambridge

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