Exquisitor at the Lifelog Search Challenge 2019

Omar Shahbaz Khan, Björn Thór Jónsson, Jan Zahálka, Stevan Rudinac, Marcel Worring

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Abstract

Interactive learning is an umbrella term for methods that attempt to understand the information need of the user and formulate queries that satisfy that information need. We propose to apply the state of the art in interactive multimodal learning to visual lifelog exploration and search, using the Exquisitor system. Exquisitor is a highly scalable interactive learning system, which uses semantic features extracted from visual content and text to suggest relevant media items to the user, based on user relevance feedback on previously suggested items. Findings from our initial experiments indicate that interactive multimodal learning will likely work well for some LSC tasks, but also suggest some potential enhancements.
Original languageEnglish
Title of host publicationProceedings of the ACM Workshop on Lifelog Search Challenge, LSC@ICMR 2019
Number of pages5
Place of PublicationOttawa, Canada
PublisherAssociation for Computing Machinery
Publication dateJun 2019
Pages7-11
ISBN (Electronic)978-1-4503-6781-3
DOIs
Publication statusPublished - Jun 2019

Keywords

  • Lifelogging
  • Interactive learning
  • Exquisitor

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