3D Tennis Complete Analysis

Project Overview #

Developed an end-to-end computer vision pipeline for comprehensive 3D tennis match analysis. The system detects players, tracks the tennis ball, reconstructs the court in 3D, and analyzes player movements and poses to extract meaningful game insights.

Key Features #

• Player Detection: Accurate detection and tracking of tennis players throughout the match.
• Ball Tracking: High-speed tennis ball detection and trajectory estimation across video frames.
• 3D Court Reconstruction: Built a 3D understanding of the tennis court using court keypoints and geometric transformations.
• Pose Estimation: Classified and analyzed player poses to understand movement patterns and playing techniques.
• Performance Analytics: Extracted spatial and temporal information for match analysis and visualization.

Technologies Used #

• Python: Core programming language for implementation.
• OpenCV: Video processing, image manipulation, and computer vision operations.
• Deep Learning: Object detection and pose estimation models.
• 3D Computer Vision: Camera geometry, perspective transformation, and 3D scene understanding.
• NumPy & Pandas: Data processing and numerical computation.
• Matplotlib: Visualization of trajectories and analytical results.

Software Architecture #

• Video Processing Pipeline: Frame extraction, preprocessing, and sequential analysis.
• Object Detection: Detection of players and tennis ball using deep learning models.
• Tracking Module: Multi-frame object tracking for players and ball trajectories.
• 3D Reconstruction: Court calibration and spatial reconstruction using computer vision techniques.
• Analytics Engine: Generation of movement statistics and performance metrics.

Impact and Applications #

• Sports Analytics: Provides detailed insights into player positioning, movement, and match dynamics.
• Performance Evaluation: Supports coaches and players with objective performance analysis.
• Broadcast Enhancement: Enables advanced visualizations and statistics for tennis broadcasts.
• Computer Vision Research: Demonstrates practical applications of 3D vision and deep learning in sports analysis.