Highlights' recognition and learning in soccer video by using Hidden Markov Models and the Bayesian theorem
Rajae El Ouazzani, Rachid Oulad Haj Thami · 2009
Our paper presents a new approach for the recognition of highlights in soccer video. Our contribution consists of the combination of Bayesian theorem inferences and Hidden Markov Models (HMMs). We build HMMs to calculate probabilities that a test video segment belongs to highlight and non highlight classes. Then, we apply the Bayesian theorem on the two previous probabilities. Our system has achieved an accuracy of 95.6% which is a good result of highlights detection in comparison with other methods.