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

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Open access

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 1029-1031 (3 pages)

Publication milestones

  • Published - 10/2019

Publication status

Published - 10/2019

Place of publication

Nice, France

Publisher

Association for Computing Machinery, United States

ISBN (Electronic)

978-1-4503-6889-6

Publication IDs

  • Scopus: 85074825936

Host publication title

Proceedings of the ACM Multimedia Conference

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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