Dance Motion Segmentation Method based on Choreographic Primitives

Data-driven animation using a large human motion database enables the programing of various natural human motions. While the development of a motion capture system allows the acquisition of realistic human motion, segmenting the captured motion into a series of primitive motions for the construction of a motion database is necessary. Although most segmentation methods have focused on periodic motion, e.g., walking and jogging, segmenting non-periodic and asymmetrical motions such as dance performance, remains a challenging problem. In this paper, we present a specialized segmentation approach for human dance motion. Our approach consists of three steps based on the assumption that human dance motion is composed of consecutive choreographic primitives. First, we perform an investigation based on dancer perception to determine segmentation components. After professional dancers have selected segmentation sequences, we use their selected sequences to define rules for the segmentation of choreographic primitives. Finally, the accuracy of our approach is verified by a user-study, and we thereby show that our approach is superior to existing segmentation methods. Through three steps, we demonstrate automatic dance motion synthesis based on the choreographic primitives obtained.