Dynamic social network for narrative video analysis

Narrative video analysis has attracted much research attention, for narrative scenes can provide meaningful representations of multimedia contents. To go beyond the limitations of content based appraoches, social network techniques was introduced in the literature to explore the high-level narrative structures by mining the relations between video characters. Taking into account the fact that such a social network is not static but changes over time as the video narrative evolves, in this work, we develop a novel social network model, namely dynamic social network, for capturing the spatiotemporal dynamics in the social network of video characters so as to enable the automatic segmentation of a video into a sequence of narrative scenes. The proposed approach is experimented with various genres of movies and the results demonstrate our effectiveness.