Automatic generation of sports highlights from recorded audiovisual content has been object of great interest in recent years. The problem is indeed important in the production of second and third division leagues highlights videos where the quantity of raw material is significant and does not contain manual annotations. Many approaches are mostly based on the analysis of the video and disregard the important information provided by the audio track. In this paper, a new approach that combines audio and video descriptors for automatic soccer highlights generation is proposed. The approach is based on the segmentation of the video contents into shots that are further analyzed in order to determine its relevance and interest. These video-shots are scored taking into account the fusion between different audio and video features. The paper is mainly focused to emphasize the importance of audio detectors that play a key role in the analysis and scoring of the video-shots. Specifically, a new algorithm for referee's whistle detection is proposed. The algorithm has been proven to be very robust and efficiently discriminates professional whistles against other types of noises such as public cheering-up, music instruments, etc. Several results have been produced using real soccer video sequences that prove the validity of the proposed audio and video fusion scheme.

Peer Reviewed