Multimodal Video-to-Video Linking: Turning to the Crowd for Insight and Evaluation

Maria Eskevich, Martha Larson, Robin Aly, Serwah Sabetghadam, Gareth J.F. Jones, Roeland Ordelman, Benoit Huet

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

3 Citations (Scopus)


Video-to-video linking systems allow users to explore and exploit the content of a large-scale multimedia collection interactively and without the need to formulate specific queries. We present a short introduction to video-to-video linking (also called ‘video hyperlinking’), and describe the latest edition of the Video Hyperlinking (LNK) task at TRECVid 2016. The emphasis of the LNK task in 2016 is on multimodality as used by videomakers to communicate their intended message. Crowdsourcing makes three critical contributions to the LNK task. First, it allows us to verify the multimodal nature of the anchors (queries) used in the task. Second, it enables us to evaluate the performance of video-to-video linking systems at large scale. Third, it gives us insights into how people understand the relevance relationship between two linked video segments. These insights are valuable since the relationship between video segments can manifest itself at different levels of abstraction.
Original languageEnglish
Title of host publicationMultiMedia Modeling
Subtitle of host publication23rd International Conference, MMM 2017, proceedings
EditorsLaurent Amsaleg, Gylfi Þór Guðmundsson, Cathal Gurrin , Björn Þór Jónsson , Shin’ichi Satoh
Place of PublicationCham
Number of pages13
EditionPart II
ISBN (Electronic)978-3-319-51814-5
ISBN (Print)978-3-319-51813-8
Publication statusPublished - 2017
EventMMM 2017: 23rd International Conference on Multimedia Modeling - Reykjavik, Iceland
Duration: 4 Jan 20176 Jan 2017

Publication series

NameLecture Notes in Computer Science
PublisherSpringer International Publishing
ISSN (Electronic)0302-9743


ConferenceMMM 2017


  • Crowdsourcing
  • Video-to-video linking
  • Link evaluation
  • Verbal-visual information

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