Performance Automatic Evaluation of Volleyball Reception by Video Analysis

This study proposes an automatic evaluation method for volleyball reception performance using video analysis techniques. The method analyzes volleyball matches recorded from the end line using computer vision and machine learning. First, the court and net are detected, and then the ball is tracked throughout the rally. Based on the ball trajectory, the system detects toss and spike events. The setter's position is identified through player detection, and the reception performance is automatically classified into three levels (A, B, C pass) according to the setter's movement distance. Experiments using volleyball match videos from YouTube achieved a court detection accuracy of 60%, ball tracking recall of 95%, toss and spike event detection recall of 85%, and reception performance evaluation accuracy of 63%. The proposed method provides objective evaluation of reception performance, which can assist coaches and players in improving techniques and strategies. Future work includes enhancing detection accuracy and introducing skeleton-based action recognition for more comprehensive analysis.