Multimodal dance choreography model

Abstract

We target to learn correlation models between music and dance performances to synthesize music driven dance choreographies. The proposed framework learns statistical mappings from musical measures to dance figures using musical measure models, exchangeable figures model, choreography model and dance figure models. Alternative dance choreographies are synthesized based on these statistical mappings. Objective and subjective evaluation results demonstrate that the proposed framework successfully synthesize music-driven choreographies.