Movie genre classification by exploiting audio-visual features of previews

Abstract

We present a method to classify movies on the basis of audio-visual cues present in previews. A preview summarizes the main idea of a movie providing a suitable amount of information to perform genre classification. In our approach movies are initially classified into action and non-action by computing the visual disturbance feature and average shot length of every movie. Visual disturbance is defined as a measure of motion content in a clip. Next we use color, audio and cinematic principles for further classification into comedy, horror drama/other and movies containing explosions and gunfire. This work is a step towards automatically building and updating a video database, thus resulting in minimum human intervention. Other potential applications include browsing and retrieval of videos on the Internet (video-on-demand), video libraries, and rating of movies.