Oct 13, 2009
Semantic Analysis of Field Sports Video using a Petri-Net of Audio-Visual Concepts
The most common approach to automatic summarization and highlight detection in sports video is to train an automatic classifier to detect semantic highlights based on occurrences of low-level features such as action replays, excited commentators or changes in a scoreboard. We propose an alternative approach based on the detection of perception concepts (PCs) and the construction of Petri-Nets, which can be used for both semantic description and event detection within sports videos