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Movement Sequence Analysis using Hidden Markov Models

Movement sequences are essential to dance and expressive movement practice; yet, they remain underexplored in movement and computing research, where the focus on short gestures prevails. We propose a method for movement sequence analysis based on motion trajectory synthesis with Hidden Markov Models. Continue reading

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The XMM Library

We released an open-source C++ library for continuous motion recognition and mapping, called XMM. XMM is a portable, cross-platform C++ library that implements Gaussian Mixture Models and Hidden Markov Models for recognition and regression. The XMM library was developed for movement interaction in creative applications and implements an interactive machine learning workflow with fast training and continuous, real-time inference. Continue reading

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