Gesture networks and DTW (Python)
This module shows an implementation of gesture networks and gesture spaces, utilizing dynamic time warping.
This module shows an implementation of gesture networks and gesture spaces, utilizing dynamic time warping.
This module provides an example of a dynamic dashboard with audio-visual and static data.
In this module an overview is provided how to track facial, hands, and body using Mediapipe, with the optionally of masking the individual in the video.
In this module an overview is provided how to wrangle multiple data streams (motion tracking, acoustics, annotations) and preprocess them (smoothing) so that you end up with one long timeseries dataset ready for further processing.
In this module an overview is provided how to wrangle multiple data streams (motion tracking, acoustics, annotations) and preprocess them (smoothing) so that you end up with one long timeseries dataset ready for further processing.
This module provides an example of extracting a smoothed amplitude envelope from a sound file.
This module provides an example of how to analyze motion tracking data using kinematic feature extraction.