Interactive exploration of journalistic video footage through multimodal semantic matching

Conference Paper (2019)
Author(s)

Sarah Ibrahimi (Universiteit van Amsterdam)

Shuo Chen (Universiteit van Amsterdam)

Devanshu Arya (Universiteit van Amsterdam)

Arthur Câmara (TU Delft - Web Information Systems)

Yunlu Chen (Universiteit van Amsterdam)

Tanja Crijns (RTL Nederland)

Maurits Van Der Goes (RTL Nederland)

Thomas Mensink (Google LLC)

Emiel Van Miltenburg (Tilburg University)

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Research Group
Web Information Systems
DOI related publication
https://doi.org/10.1145/3343031.3350597 Final published version
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Publication Year
2019
Language
English
Research Group
Web Information Systems
Pages (from-to)
2196-2198
ISBN (electronic)
9781450368896
Event
27th ACM International Conference on Multimedia, MM 2019 (2019-10-21 - 2019-10-25), Nice, France
Downloads counter
338
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Abstract

This demo presents a system for journalists to explore video footage for broadcasts. Daily news broadcasts contain multiple news items that consist of many video shots and searching for relevant footage is a labor intensive task. Without the need for annotated video shots, our system extracts semantics from footage and automatically matches these semantics to query terms from the journalist. The journalist can then indicate which aspects of the query term need to be emphasized, e.g. the title or its thematic meaning. The goal of this system is to support the journalists in their search process by encouraging interaction and exploration with the system.

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