Atomic topical segments detection for instructional videos

Abstract

This paper presents our latest work on structuring instructional videos into units of atomic topical segment so as to facilitate topic-based video browsing and offer efficient video authoring. Specifically, we developed a comprehensive text analysis component to first extract informative text cues such as keyword synonym set and sentence boundary information, from a video's transcript. These text cues are then applied with various audiovisual cues such as silence/music break and speech similarity, to identify topical segments. Early experiments carried out on collections of real data from targeted user communities have yielded good results, and the user feedback on using the generated topical segment information is very encouraging.