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Story Understanding through Semantic Analysis and Automatic Alignment of Text and Video

by Makarand Murari Tapaswi

Institution:	Universität Karlsruhe
Year:	2016
Posted:	02/05/2017
Record ID:	2133832
Full text PDF:	http://digbib.ubka.uni-karlsruhe.de/volltexte/documents/3870072

Abstract

Humans spend a large amount of time listening, watching, and reading stories. We argue that the ability to model, analyze, and create new stories is a stepping stone towards strong AI. We thus work on teaching AI to understand stories in films and TV series. To obtain a holistic view of the story, we align videos with plot synopses and books; visualize character interactions as a chart; and finally, test machine understanding of stories by asking it to answer questions.