Constructing table-of-content for videos

A fundamental task in video analysis is to extract structures from the vide o to facilitate user's access (browsing and retrieval). Motivated by the im portant role that the table of content (ToC) plays in a book, in this paper , we introduce the concept of ToC in the video domain. Some existing approa ches implicitly use the ToC, but are mainly limited to low-level entities ( e.g., shots and key frames). The drawbacks are that low-level structures (1 ) contain too many entries to be efficiently presented to the user; and (2) do not capture the underlying semantic structure of the video based on whi ch the user may wish to browse/retrieve. To address these limitations, in t his paper, we present an effective semantic-level ToC construction techniqu e based on intelligent unsupervised clustering. It has the characteristics of better modeling the time locality and scene structure. Experiments based on real-world movie videos validate the effectiveness of the proposed appr oach. Examples are given to demonstrate the usage of the scene-based ToC in facilitating user's access to the video.