MediaEval 2016 predicting media interestingness task

Claire-Hélène Demarty, Mats Sjöberg, Bogdan Ionescu, Thanh-Toan Do, Hanli Wang, Ngoc Q.K. Duong, Frédéric Lefebvre

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

19 Citations (Scopus)

Abstract

This paper provides an overview of the Predicting Media Interestingness task that is organized as part of the Media-Eval 2016 Benchmarking Initiative for Multimedia Evaluation. The task, which is running for the first year, expects participants to create systems that automatically select images and video segments that are considered to be the most interesting for a common viewer. In this paper, we present the task use case and challenges, the proposed data set and ground truth, the required participant runs and the evaluation metrics.

Original languageEnglish
Title of host publication2016 Multimedia Benchmark Workshop, MediaEval 2016
EditorsGuillaume Gravier, Claire-Hélène Demarty, Hervé Bredin, Hervé Bredin, Christina Boididou, Emmanuel Dellandrea, Jaeyong Choi, Michael Riegler, Richard Sutcliffe, Igor Szoke, Gareth J.F. Jones, Martha Larson
Place of PublicationAachen Germany
PublisherCEUR-WS
Number of pages3
Publication statusPublished - 2016
Externally publishedYes
EventMultimedia Benchmark Workshop 2016 - Hilversum, Netherlands
Duration: 20 Oct 201621 Oct 2016
http://ceur-ws.org/Vol-1739/ (Proceedings)

Publication series

NameCEUR Workshop Proceedings
PublisherCEUR-WS.org
Volume1739
ISSN (Print)1613-0073

Conference

ConferenceMultimedia Benchmark Workshop 2016
Abbreviated titleMediaEval 2016
CountryNetherlands
CityHilversum
Period20/10/1621/10/16
Internet address

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