Constructing table-of-content for videos

A fundamental task in video analysis is to extract structures from the video to facilitate user's access (browsing and retrieval). Motivated by the important 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 approaches 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 which the user may wish to browse/retrieve. To address these limitations, in this paper, we present an effective semantic-level ToC construction technique 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 approach. Examples are given to demonstrate the usage of the scene-based ToC in facilitating user's access to the video.