Automatic Hierarchical Table of Contents Generation for Educational Videos

Debabrata Mahapatra, Ragunathan Mariappan, Vaibhav Rajan

Abstract: The number of freely available online educational videos from universities and other organizations is growing rapidly. Accurate indexing and summarization are essential for efficient search, recommendation and effective consumption of videos. In this paper, we describe a new method of automatically creating a hierarchical table of contents for a video. It provides a summary of the video content along with a textbook--like facility for nonlinear navigation and search through the video. Our multimodal approach combines new methods for shot level video segmentation and for hierarchical summarization. Empirical results demonstrate the efficacy of our approach on many educational videos.