Video data mining: rhythms in a movie

The task to discover useful editing patterns from a professional video, such as a movie, is one of the main purposes of video data mining. These patterns successfully convey an editor's intentions to the viewer. However, data mining on multimedia data like a movie is a challenging task, due to the complicated contents of multimedia data. Particularly, the discovered patterns need to be supported by their semantic features, because these features tell amateur editors how to use the corresponding patterns during the process of editing a new video. We focus on the rhythm in a movie, consisting of the durations of a target character's appearance and disappearance. Based on this rhythm, we divide the movie into topics. Each topic corresponds to one meaningful episode of the character. By investigating such topics, we can discover useful editing patterns of a character's rhythm, supported by their semantic features. Also, these rhythms can be used to annotate certain types of topics.