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This code is a simple implementation of Beat Synchronous Dance Animation based on Periodic Motion and Music Tempo Analysis
based on the paper [1].
The goal of the proposed method [1] is to generate beat synchronous dance animation (bvh format) based on the analysis of both visual and audio data.
We propose and employ a new method for the temporal segmentation of such motion
data into the periods of dance. Next, we use a beats of audio. Given an
input music with its beats that is of the same genre as the one corresponding to the
visually observed dance, we automatically produce a beat synchronous
dance animation of a virtual character.
You can find more details in www.csd.uoc.gr/~cpanag and http://users.ics.forth.gr/~argyros/
It uses the toolboxes
MOCAP0p136 from http://motor-invariant-control.googlecode.com/svn/trunk/BVH/MOCAP0p136/
and NDLUTIL0p162 from https://github.com/XinweiJiang/SLLGPLVM/tree/master/NDLUTIL0p162
We will appreciate if you cite our papers [1-2] in your work:
[1] C. Panagiotakis, Andre Holzapfel, Damien Michel, and Antonis Argyros, Beat Synchronous Dance Animation based on Periodic Motion and Music Tempo Analysis, International Symposium on Visual Computing, 2013.
[2] C. Panagiotakis, Damien Michel, and Antonis Argyros, Temporal segmentation and seamless stitching of motion patterns for synthesizing novel animations of periodic dances, International Conference on Pattern Recognition, 2014.
Cite As
Costas Panagiotakis (2026). Beat Synchronous Dance Animation (https://www.mathworks.com/matlabcentral/fileexchange/54298-beat-synchronous-dance-animation), MATLAB Central File Exchange. Retrieved .
C. Panagiotakis, Andre Holzapfel, Damien Michel, and Antonis Argyros, Beat Synchronous Dance Animation based on Periodic Motion and Music Tempo Analysis, International Symposium on Visual Computing, 2013.
C. Panagiotakis, Damien Michel, and Antonis Argyros, Temporal segmentation and seamless stitching of motion patterns for synthesizing novel animations of periodic dances, International Conference on Pattern Recognition, 2014.
General Information
- Version 1.0.0.1 (1.99 MB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
