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.
The library includes a number of classes for probabilistic models, from GMMs to Hierarchical HMMs, implemented for continuous real-time recognition and generation, following my PhD work on motion-sound mapping by demonstration. It comes with Python bindings, and is also implemented as a set of externals for Cycling’74 Max, that are released within Mubu (see this article).
The full documentation is available on Github Pages: http://ircam-rnd.github.io/xmm/
XMM is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
XMM is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with XMM. If not, see http://www.gnu.org/licenses/.
Citing this work
If you use this code for research purposes, please cite one of the following publications: