TY - GEN
T1 - Exquisitor: Breaking the Interaction Barrier for Exploration of 100 Million Images
AU - Ragnarsdóttir, Hanna
AU - Þorleiksdóttir, Þórhildur
AU - Khan, Omar Shahbaz
AU - Jónsson, Björn Thór
AU - Guðmundsson, Gylfi Þór
AU - Zahálka, Jan
AU - Rudinac, Stevan
AU - Amsaleg, Laurent
AU - Worring, Marcel
PY - 2019/10
Y1 - 2019/10
N2 - 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.
AB - 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.
KW - Interactive multimodal learning
KW - Scalability
KW - 100 million images
U2 - 10.1145/3343031.3350580
DO - 10.1145/3343031.3350580
M3 - Article in proceedings
SP - 1029
EP - 1031
BT - Proceedings of the ACM Multimedia Conference
PB - Association for Computing Machinery
CY - Nice, France
ER -