Fast Dialogue Indexing Based on Structure Information

In this paper we propose a fast and simple method to index and search for dialogues in a video database. Dialogues are indexed relying only on the typical dialogue scene structure, which has been modeled using a statistical framework. The related entropy rate is chosen as a compact index for capturing the specificity of the scene structure. Specifically, entropy rate effectively represents the number of expressed visual concepts and the alternating pattern in which concepts appear inside dialogue scenes. As demonstrated on a large video data set, modern video management systems would benefit from integrating such structure information for effective content organization and dialogue search task.