Segmenting TV Series into Scenes using Speaker Diarization

Abstract : In this paper, we propose a novel approach to perform scene segmentation of TV series. Using the output of our existing speaker diarization system, any temporal segment of the video can be described as a binary feature vector. A straightforward segmentation algorithm then allows to group similar contiguous speaker segments into scenes. An additional visual-only color-based segmentation is then used to refine the first segmentation. Experiments are performed on a subset of the Ally McBeal TV series and show promising results, obtained with a rule-free and generic method. For comparison purposes, test corpus annotations and description are made available to the community.