Audiovisual integration for tennis broadcast structuring

This paper focuses on the integration of multimodal features for sport video structure analysis. The method relies on a statistical model which takes into account both the shot content and the interleaving of shots. This stochastic modelling is performed in the global framework of Hidden Markov Models (HMMs) that can be efficiently applied to merge audio and visual cues. Our approach is validated in the particular domain of tennis videos. The model integrates prior information about tennis content and editing rules. The basic temporal unit is the video shot. Visual features are used to characterize the type of shot view. Audio features describe the audio events within a video shot. As a result, typical tennis scenes are simultaneously segmented and identified.

• Type: Journal
• Year: 2006
• Where: MTA
• Authors: Ewa Kijak, Guillaume Gravier, Lionel Oisel, Patrick Gros
• Keywords: Hidden Markov Models, MTA 2006, Shot Content, Sport Video Structure