A Multimedia Based Movie Style Model

Movie style is one abstract representation of a movie and is used in recommendation systems. In this paper, we argue that movie style model is more than just emotional attribute represented by genre, but also includes visual, auditory and compositional attributes. We propose a movie model that takes all these attributes into account and generate a comprehensive movie model by automatically analyzing the contents of the movie. The proposed model does not require manual tagging and is independent of the length of the movie. Using a case study of a set of Hollywood directors we show that the attributes proposed by us are important to model a movie style. We show that predictor using these features recognize the correct director with an accuracy of 76.4%.