Exquisitor: Breaking the Interaction Barrier for Exploration of 100 Million Images

Hanna Ragnarsdóttir 1 Þórhildur Þorleiksdóttir 1 Omar Shahbaz Khan 2 Björn Þór Jónsson 2 Gylfi Þór Guðmundsson 1 Jan Zahálka 3 Stevan Rudinac 4 Laurent Amsaleg 5 Marcel Worring 6
1 Reykjavík University
2 IT University of Copenhagen
3 bohem.ai [Prague]
4 Informatics Institute [Amsterdam]
5 LinkMedia - Creating and exploiting explicit links between multimedia fragments
Inria Rennes – Bretagne Atlantique , IRISA-D6 - MEDIA ET INTERACTIONS
6 UvA - University of Amsterdam [Amsterdam]
Abstract : In this demonstration, we present Exquisitor, a media explorer capable of learning user preferences in real-time during interactions with the 99.2 million images of YFCC100M. Exquisitor owes its efficiency to innovations in data representation, compression, and indexing. Exquisitor can complete each interaction round, including learning preferences and presenting the most relevant results, in less than 30 ms using only a single CPU core and modest RAM. In short, Exquisitor can bring large-scale interactive learning to standard desktops and laptops, and even high-end mobile devices.
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Hanna Ragnarsdóttir, Þórhildur Þorleiksdóttir, Omar Shahbaz Khan, Björn Þór Jónsson, Gylfi Þór Guðmundsson, et al.. Exquisitor: Breaking the Interaction Barrier for Exploration of 100 Million Images. MM 2019 - 27th ACM International Conference on Multimedia, Oct 2019, Nice, France. pp.1029-1031, ⟨10.1145/3343031.3350580⟩. ⟨hal-02378272⟩

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