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

Hanna Ragnarsdóttir, Þórhildur Þorleiksdóttir, Omar Shahbaz Khan, Björn Thór Jónsson, Gylfi Þór Guðmundsson, Jan Zahálka, Stevan Rudinac, Laurent Amsaleg, Marcel Worring

Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer review

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.
OriginalsprogEngelsk
TitelProceedings of the ACM Multimedia Conference
Antal sider3
UdgivelsesstedNice, France
ForlagAssociation for Computing Machinery
Publikationsdatookt. 2019
Sider1029-1031
ISBN (Elektronisk)978-1-4503-6889-6
DOI
StatusUdgivet - okt. 2019

Emneord

  • Interactive multimodal learning
  • Scalability
  • 100 million images

Fingeraftryk

Dyk ned i forskningsemnerne om 'Exquisitor: Breaking the Interaction Barrier for Exploration of 100 Million Images'. Sammen danner de et unikt fingeraftryk.

Citationsformater