Résumé : In this paper, we investigate new ways to understand and to analyze human gesture in a research
context applied on co-verbal gesture across language. The research project focuses on the quality of
the movement and consider the gesture “pulse of effort.“ We propose a workflow for real-time
gesture analysis to visualize gesture kinematics features (Velocity, Acceleration, Jerk) from
heterogeneous data (Video, Motion Capture and Gesture Annotations) at the same time base. The
tools designed here provide immersive and interactive explorations of data: users can test
hypotheses and embody gesture visualization and descriptors adopting different Frames of
Reference using augmented reality. We have conducted an evaluation protocol in the field of
linguistics that compares 496 annotated gestures to benchmark the workflow.
https://hal.archives-ouvertes.fr/hal-02474193
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Jean-François Jégo, Vincent Meyrueis, Dominique Boutet. A Workflow for Real-time Visualization and Data Analysis of Gesture using Motion Capture. MOCO '19: 6th International Conference on Movement and Computing, Oct 2019, TEMPE AZ, United States. pp.1-6, ⟨10.1145/3347122.3359598⟩. ⟨hal-02474193⟩
