Salient Event Detection in Basketball Mobile Videos

Modern smartphones have become the most popular means for recording videos. In fact, thanks to their portability, smartphones allow for recording anything and at any moment of our everyday life. One common occasion is represented by sport happenings, where people often record their favourite team or players. Automatic analysis of such videos is important for enabling applications such as automatic organization, browsing and summarization of the content. This paper proposes novel algorithms for the detection of salient events in videos recorded at basketball games. The novel approach consists of jointly analyzing visual data and magnetometer data. The magnetometer data provides information about the horizontal orientation of the camera. The proposed joint analysis allows for a reduced number of false positives and for a reduced computational complexity. The algorithms are tested on data captured during real basketball games. The experimental results clearly show the advantages of the proposed approach.