Video Table-of-Content Generation

This chapter presents a novel framework for scene-level video table of contents (ToC) construction. It presents an effective scene-level ToC construction technique based on intelligent, unsupervised clustering. It has the characteristics of better modeling the time locality and scene structure. Scene-level ToC has the advantage over other techniques. This chapter reviews and evaluates the video parsing techniques at various levels. There are four parameters in the proposed video ToC construction algorithm: W c , W A , groupThreshold , and sceneThreshold. In the proposed algorithm, Gaussian normalization is used for determining these four parameters. Experiments over real-world movie videos validate the effectiveness of the proposed approach. Examples are presented to demonstrate the use of the scene-based ToC to facilitate the user's access to the video. The proposed approach provides an open framework for structure analysis of video features. It has four major modules: shot boundary detection and key frame extraction, spatiotemporal feature extraction, time-adaptive grouping, and scene structure construction.