Abstract

Educational documentary videos play an important role in enriching learning experience. However, due to unstructured and linear features, documentary videos are much more difficult to access than text-based documents and have not been effectively utilized. In this paper, we propose a multimodal, hierarchical documentary video segmentation procedure based on image, audio and text understanding. The coincidence of scene-level audio breaks and text (transcript) breaks from domain independent text segmentation determines documentary video scenes/paragraphs. Each video scene/paragraph is further segmented into video shots based on video visual features. To effectively utilize composite documentary video learning materials generated, we propose a documentary video access platform that supports hierarchical organization of video content, multimodal presentation of information, augmented video content and multi-level flexible search. A prototype platform is implemented to demonstrate the idea

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