It is important to properly organize the unstructured video data for content-based video analysis and retrieval. In this paper

we propose a unified approach for film video summarization based on the analysis of video structure and motion attention model. Video shots are firstly grouped into shot clusters. Afterwards

according to the characterization of film video scene

a temporally and spatially integrated strategy is presented to parse shot clusters into semantic scenes in terms of the definition of temporal relationships between two shot clusters. Finally

representative frames and highlight shots are selected from scenes by using motion attention model. The scheme offers an efficient mean for browsing and effectively retrieving film video.