Vision-Stats

This project successfully combines multiple computer vision and machine learning techniques to provide an in-depth analysis of a soccer game. By leveraging object detection, object tracking, team classification, possession analysis, and statistical evaluation, the system is capable of extracting critical insights such as:

Goal Detection: A robust method is implemented to detect goals by measuring the proximity of the ball to the goal area. This feature is enhanced with a threshold mechanism to ensure reliable detection over consecutive frames.

Heatmap Analysis: A heatmap provides a visual representation of player movements on the field, offering a clear view of player activity and game dynamics over time.

Object Tracking: A distance-based tracking system efficiently tracks players and their movements across frames, maintaining unique IDs for individuals while updating their positions dynamically.

Team Classification: By employing K-means clustering on player colors, the system distinguishes between players from different teams and identifies outliers such as referees and goalkeepers.

Possession Tracking: The possession analysis module identifies which player and team currently possess the ball, along with their respective statistics, such as missed possessions and total possession time.

Statistics Extraction: Detailed player statistics, including mileage (in pixels and meters) and possession times, are generated to evaluate individual and team performance. This data provides meaningful insights into player efficiency and team strategy.

Plane Projection: Through perspective transformation, player positions are accurately mapped onto a top-down field view, aiding visual interpretation and tactical analysis.

Potential Applications

Sports Analytics: This system can be used by coaches and analysts to evaluate team strategies, player performance, and game dynamics.

Broadcast Enhancements: Real-time visualizations, such as heatmaps and possession statistics, can enhance viewer engagement during live broadcasts.

Training: Players can use the insights to improve their positioning, movement patterns, and overall performance.

Fan Engagement: Fans can gain a deeper understanding of their favorite teams and players through detailed analytics.