Exquisitor at the Lifelog Search Challenge 2019
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- ,
- Jan Zahálka,
- Stevan Rudinac,
- Marcel Worring
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- Czech Technical University in Prague,
- University of Amsterdam
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOpen access
Publication Information
Output type
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOriginal language
EnglishPages from-to (Number of pages)
Pages 7-11 (5 pages)Publication milestones
- Published - 06/2019
Publication status
Published - 06/2019
Place of publication
Ottawa, CanadaPublisher
Association for Computing Machinery, United StatesISBN (Electronic)
978-1-4503-6781-3Publication IDs
- Scopus: 85067972838
Host publication title
Proceedings of the ACM Workshop on Lifelog Search Challenge, LSC@ICMR 2019Abstract
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.
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Citations
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Captures
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Access to documents
Submitted manuscript, 5.76 MB
