AbstractsComputer Science

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

by Makarand Murari Tapaswi




Institution: Universit├Ąt Karlsruhe
Department:
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.