Human Movement Recognition in Dancesport Video Images Based on Chaotic System Equations

Abstract

This paper presents an in-depth study and analysis of human action recognition in dancesport video images through chaotic system equations. A novel fractional-order chaotic system model with hidden multistability is constructed. Since this fractional-order chaotic system has no equilibrium point, the equilibrium point stability analysis is not required. The effect of system parameters on the multistability characteristics of the fractional-order chaotic system is investigated in depth by using the control variable method and nonlinear dynamic tools. In addition, the system has a special property of offset incremental control, which makes the system more widely and practically useful in engineering applications. Finally, circuit simulation experiments and hardware circuit experiments are conducted for the fractional-order chaotic system, and the results are consistent with the corresponding theoretical analysis. The system architecture of the mobile augmented reality-based ethnic dynamic art display system is designed, and the system architecture adopts a hierarchical design. The experimental results show that the design method of the mobile augmented reality-based dynamic art display system proposed in this thesis can meet the purpose of expanding the ways of dancesport display, and the system designed in this thesis is customizable and the synthesized images have a high sense of realism.