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Fish4Knowledge: collecting and analyzing massive coral reef fish video data
This book gives a start-to-finish overview of the whole Fish4Knowledge project, in 18 short chapters, each describing one aspect of the project. The Fish4Knowledge project explored the possibilities of big video data, in this case from undersea video. Recording and analyzing 90 thousand hours of vid...
Autores principales: | , , , , |
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Lenguaje: | eng |
Publicado: |
Springer
2016
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1007/978-3-319-30208-9 http://cds.cern.ch/record/2143514 |
_version_ | 1780950215582285824 |
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author | Fisher, Robert Chen-Burger, Yun-Heh Giordano, Daniela Hardman, Lynda Lin, Fang-Pang |
author_facet | Fisher, Robert Chen-Burger, Yun-Heh Giordano, Daniela Hardman, Lynda Lin, Fang-Pang |
author_sort | Fisher, Robert |
collection | CERN |
description | This book gives a start-to-finish overview of the whole Fish4Knowledge project, in 18 short chapters, each describing one aspect of the project. The Fish4Knowledge project explored the possibilities of big video data, in this case from undersea video. Recording and analyzing 90 thousand hours of video from ten camera locations, the project gives a 3 year view of fish abundance in several tropical coral reefs off the coast of Taiwan. The research system built a remote recording network, over 100 Tb of storage, supercomputer processing, video target detection and tracking, fish species recognition and analysis, a large SQL database to record the results and an efficient retrieval mechanism. Novel user interface mechanisms were developed to provide easy access for marine ecologists, who wanted to explore the dataset. The book is a useful resource for system builders, as it gives an overview of the many new methods that were created to build the Fish4Knowledge system in a manner that also allows readers to see how all the components fit together. |
id | cern-2143514 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2016 |
publisher | Springer |
record_format | invenio |
spelling | cern-21435142021-04-21T19:45:07Zdoi:10.1007/978-3-319-30208-9http://cds.cern.ch/record/2143514engFisher, RobertChen-Burger, Yun-HehGiordano, DanielaHardman, LyndaLin, Fang-PangFish4Knowledge: collecting and analyzing massive coral reef fish video dataEngineeringThis book gives a start-to-finish overview of the whole Fish4Knowledge project, in 18 short chapters, each describing one aspect of the project. The Fish4Knowledge project explored the possibilities of big video data, in this case from undersea video. Recording and analyzing 90 thousand hours of video from ten camera locations, the project gives a 3 year view of fish abundance in several tropical coral reefs off the coast of Taiwan. The research system built a remote recording network, over 100 Tb of storage, supercomputer processing, video target detection and tracking, fish species recognition and analysis, a large SQL database to record the results and an efficient retrieval mechanism. Novel user interface mechanisms were developed to provide easy access for marine ecologists, who wanted to explore the dataset. The book is a useful resource for system builders, as it gives an overview of the many new methods that were created to build the Fish4Knowledge system in a manner that also allows readers to see how all the components fit together.Springeroai:cds.cern.ch:21435142016 |
spellingShingle | Engineering Fisher, Robert Chen-Burger, Yun-Heh Giordano, Daniela Hardman, Lynda Lin, Fang-Pang Fish4Knowledge: collecting and analyzing massive coral reef fish video data |
title | Fish4Knowledge: collecting and analyzing massive coral reef fish video data |
title_full | Fish4Knowledge: collecting and analyzing massive coral reef fish video data |
title_fullStr | Fish4Knowledge: collecting and analyzing massive coral reef fish video data |
title_full_unstemmed | Fish4Knowledge: collecting and analyzing massive coral reef fish video data |
title_short | Fish4Knowledge: collecting and analyzing massive coral reef fish video data |
title_sort | fish4knowledge: collecting and analyzing massive coral reef fish video data |
topic | Engineering |
url | https://dx.doi.org/10.1007/978-3-319-30208-9 http://cds.cern.ch/record/2143514 |
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