Multi-physical and Temporal Feature Based Self-correcting Approximation Model for Monocular 3D Volleyball Trajectory Analysis

Abstract

Benefiting from the low venue requirements and deployment cost, analysis of 3D volleyball trajectory from monocular vision sensor is of important significance to volleyball game analysis and training assisting. Because of the monocular vision limitation, complicated ball trajectory caused by physical factors and model drifting owing to distance information loss are two governing challenges. This paper proposes a multi-physical factors and self-cor-recting trajectory approximation model. Also, a trajectory correction algorithm based on temporal motion features is proposed. For the first challenge, air resistance factor and gravity factor which mostly impact volleyball during flying are considered to simulate ball motion status. The approximation model parameters are evaluated and corrected during model calculating to reduce calculation error. To limiting model drifting, volleyball movement characteristics based on temporal motion feature is applied to correct approximated trajectory. The success rate of proposed monocular 3D trajectory approximation method achieves 82.5% which has 47.0% improvement comparing with conventional work.