Decision level fusion-based team tactics estimation in soccer videos

Abstract

A decision-level fusion (DLF)-based team tactics estimation method in soccer videos is newly presented. In our method, tactics estimation based on audio-visual and formation features is newly adopted since the tactics of the soccer game are closely related to the audio-visual sequences and player positions. Therefore, by using these features, we classify the tactics via Support Vector Machine (SVM). Furthermore, by applying DLF to the SVM-based classification results, the two modalities are integrated to obtain more accurate tactics estimation results. Some results of experiments verify the superiority of our method.