A Novel Role-Based Movie Scene Segmentation Method

Semantic scene segmentation is a crucial step in movie video analysis and extensive research efforts have been devoted to this area. However, previous methods are heavily relying on video content itself, which are lack of objective evaluation criterion and necessary semantic link due to the semantic gap. In this paper, we propose a novel role-based approach for movie scene segmentation using script. Script is a text description of movie content that contains the scene structure information and related character names, which can be regarded as an objective evaluation criterion and useful external reference. The main novelty of our approach is that we convert the movie scene segmentation into a movie-script alignment problem and propose a HMM alignment algorithm to map the script scene structure to the movie content. The promising results obtained from three Hollywood movies demonstrate the effectiveness of our proposed approach.