Deep Understanding of Soccer Match Videos

TL;DR

This paper presents a comprehensive computer vision system that analyzes soccer match videos to detect objects, track movements, recognize players, classify scenes, and generate highlights, thereby enriching viewer understanding and engagement.

Contribution

The novel system integrates multiple vision techniques to provide detailed, real-time analysis and summaries of soccer matches from live video streams.

Findings

Effective detection of key objects like players and ball

Accurate tracking of player and ball movements

Generation of highlights and tactical visualizations

Abstract

Soccer is one of the most popular sport worldwide, with live broadcasts frequently available for major matches. However, extracting detailed, frame-by-frame information on player actions from these videos remains a challenge. Utilizing state-of-the-art computer vision technologies, our system can detect key objects such as soccer balls, players and referees. It also tracks the movements of players and the ball, recognizes player numbers, classifies scenes, and identifies highlights such as goal kicks. By analyzing live TV streams of soccer matches, our system can generate highlight GIFs, tactical illustrations, and diverse summary graphs of ongoing games. Through these visual recognition techniques, we deliver a comprehensive understanding of soccer game videos, enriching the viewer's experience with detailed and insightful analysis.