Exquisitor at the Lifelog Search Challenge 2019
- ,
- ,
- Jan Zahálka,
- Stevan Rudinac,
- Marcel Worring
- ,
- Czech Technical University in Prague,
- University of Amsterdam
Publikation:
Konference artikel i Proceeding eller bog/rapport kapitel
Konferencebidrag i proceedings
Peer-reviewOpen Access
Publikation information
Produktionstype
Publikation:
Konference artikel i Proceeding eller bog/rapport kapitel
Konferencebidrag i proceedings
Peer-reviewOriginalsprog
EngelskSider fra-til (Antal sider)
Sider 7-11 (5 sider)Publikationsmilepæle
- Udgivet - 06/2019
Publikationsstatus
Udgivet - 06/2019
Udgivelsessted
Ottawa, CanadaForlag
Association for Computing Machinery, USAISBN (Elektronisk)
978-1-4503-6781-3Publication IDs
- Scopus: 85067972838
Titel på værtspublikation
Proceedings of the ACM Workshop on Lifelog Search Challenge, LSC@ICMR 2019Resume
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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