Study on Path Optimization and Motion Prediction for Dragon Dance Based on Helical Models

Abstract

This paper presents a specialized motion prediction model for the complex, coordinated movements characteristic of dragon dance performance, aiming to enhance fluidity and aesthetic appeal through accurate motion forecasting. The model employs a multi-objective optimization approach, utilizing the Salp Swarm Algorithm (SSA) to effectively capture and predict intricate movement sequences. Through detailed analysis of temporal and spatial parameters inherent in dragon dance, the model can address the challenges posed by the dance’s dynamic and collective motion requirements. Experimental results verify the model’s predictive accuracy and adaptability, showing a significant improvement in forecast precision over traditional methods. These findings highlight the model’s capability to handle complex motion interactions, thereby contributing to research in both motion prediction and performance modeling. Furthermore, this approach offers broader applicability, as the insights gained here may benefit various domains where accurate, real-time movement prediction is essential, including robotics, sports analysis, and animation.