Scalable video summarization of cultural video documents in cross-media space based on data cube approach

Video summarization has been a core problem to manage the growing amount of content in multimedia databases. An efficient video summary should display an overview of the video content and most of existing approaches fulfil this goal. However the information does not allow user to get all details of interest selectively and progressively. This paper proposes a scalable video summarization approach which provides multiple views and levels of details. Our method relies on the usage of cross media space and consensus clustering method. A video document is modelled as a data cube where the level of details is refined over nonconsensual features of the space. The method is designed for weakly structured content such as cultural documentaries and was tested on the INA corpus of cultural archives.