Semantic event detection in soccer video by integrating multi-features using Bayesian network

Soccer is the most popular game in the world and people are far more interested in the scoring plays in the game. In this paper, we use a Bayesian network to statistically model the scoring event detection based on the recording and editing rules of soccer video. The Bayesian network fuses the five low-level video content cues (evidences) with the graphical model and probability theory. Thus the problem of event detection is converted to the one of statistical pattern classification. And the learning and inference of the Bayesian network are given in the paper. The experimental results indicate that our method is effective and robust.