The Method of Dance Movement Segmentation and Labanotation Generation Based on Rhythm

Abstract

Labanotation is a widely used dance recording system, which plays an important role in inheriting and protecting folk dances. However, manual drawing of dance notation is time-consuming and labor-intensive. Therefore, research on the automatic generation of Labanotation has received extensive attention. In this article, a method to automatically generate Labanotation based on motion capture data is proposed. Firstly, in order to facilitate the calculation of the bending angle and motion feature sequences, the BVH-formatted Euler angle data is converted into a sequence of the 3D Cartesian world coordinates according to the analysis of human bones. Secondly, a motion segmentation method based on kinematics features and rhythms is proposed, which can segment different styles of motion into fragments for further identification. Finally, we generate the Labanotation with the platform we developed. Experiments show that our segmentation method has good accuracy in segmenting action sequences, which makes the generated Labanotation more reliable.

Keywords

• Principal component analysis
• discrete wavelet transform
• rhythm
• labanotation