Repository - Algorithms

Algorithms

A list of algorithms developed within the framework of the EU SIEMPRE project. Once you have recorded your multimodal data set, there is a need to extract segment of different channels, to maintain access through specific timestamps, in order to have clear repository.


  • Siempre Matlab Toolbox (UNIGE)

    A set of MATLAB scripts to process and analyze audio and MoCap data.

  • EyesWeb Applications for real-time visualization and analysis of multimodal data (UNIGE)

    A set of EyesWeb interactive applications to read and visualize multimodal data of musicians in synchronous way by using the smpte timecode (see documentation on the SIEMPRE EyesWeb Library). Multimodal data can include Video, Motion Capture (MoCap), audio from stereophonic ambient recording or piezo-electric microphones attached to single instrument, and physiological measures:
    • EyesWeb interactive application to visualize MoCap data of the musician with ambient stereo recordings: EyesWeb Application
    • EyesWeb interactive application to visualize behavioral features of individual and ensemble performance (e.g., distance from musicians'head to the center of the string quartet). MoCap data are synchronized with ambient stereo and single microphones recordings. EyesWeb Application
    • Sample multimodal data (audio, MoCap, smpte) to test the algorithms: test_eyesweb

  • Physiological feature extraction tools (QUB)

    These tools consist in a set of algorithms for processing and analyzing physiological measures.

  • Synchronization Tools (QUB)

    These tools allow to build the raw data in the format accepted by RepoVizz
    • A set of MATLAB functions for synchronization of multimodal signals: Download
    • Front END for the SyncTools, communication with the SIEMPRE XML structure and writing of SIEMPRE BWF: Download

  • ThermoGUI – A Matlab Graphical User Interface for visualization and analysis of thermographic data (IIT)

    ThermoGUI is a Graphical User Interface created to (i) visualize and compare signals extracted from different thermographic recordings; (ii) identify significant events in the thermographic signals; (iii) and facilitate the identification of audio stimuli that caused the thermographic events.