FN Archimer Export Format
PT C
TI FishTrack22: An Ensemble Dataset for Multi-Object Tracking Evaluation
BT 
AF Dawkins, Matt
   Campbell, Matthiew
   Prior, Jack
   FAILLETTAZ, Robin
   SIMON, Julien
   Lucero, Matthew
   Banez, Thompson
   Richards, Benjamin
   Rollo, Audrey
   Salvi, Mary
   Lewis, Byron
   Davis, Brandon
   Blue, Rusty
   Hoogs, Anthony
   Chaudhary, Aashish
AS 1:1;2:2;3:2;4:3;5:3;6:4;7:4;8:2;9:2;10:1;11:1;12:1;13:1;14:1;15:1;
FF 1:;2:;3:;4:PDG-RBE-HALGO-LTBH;5:PDG-RBE-HALGO-LTBH;6:;7:;8:;9:;10:;11:;12:;13:;14:;15:;
C1 Kitware Inc, USA
   NOAA Fisheries, USA
   Ifremer, France
   California Department of Fish and Wildlife, USA
C2 KITWARE INC, USA
   NOAA, USA
   IFREMER, FRANCE
   CALIF DEPARTM FISH WILDLIFE, USA
SI LORIENT
SE PDG-RBE-HALGO-LTBH
UM DECOD
UR https://archimer.ifremer.fr/doc/00783/89523/105926.pdf
LA English
DT Poster
AB Tracking fish in optical underwater imagery contains a number of challenges not encountered in terrestrial domains. Video may contain large schools comprised of many individuals, dynamic natural backgrounds, variable target scales, volatile collection conditions, and non-fish moving confusors including debris, marine snow, and other organisms. Lastly, there is a lack of public datasets for algorithm evaluation available in this domain. FishTrack22 aims to address these challenges by providing a large quantity of expert-annotated fish groundtruth tracks, in imagery and video collected across a range of different backgrounds, locations, collection conditions, and organizations. Approximately 1 million bounding boxes across 45k tracks are included in the release of the ensemble, with potential for future growth in later releases. 
PY 2022
PD JUL
ID 89523
ER

EF