Long-term underwater camera surveillance for monitoring and analysis of fish populations

Bastiaan Boom; Phoenix X. Huang; C. Beyan; Concetto Spampinato; Simone Palazzo; Jiyin He; Emmanuelle Beauxis-Aussalet; Sun-In Lin; Hsiu-Mei Chou; Gayathri Nadarajan; Jessica Chen-Burger; Jacco van Ossenbruggen; Daniela Giordano; Lynda Hardman; Fang-Pang Lin; Bob Fisher

Long-term underwater camera surveillance for monitoring and analysis of fish populations

Bastiaan Boom, Phoenix X. Huang, C. Beyan, Concetto Spampinato, Simone Palazzo, Jiyin He, Emmanuelle Beauxis-Aussalet, Sun-In Lin, Hsiu-Mei Chou, Gayathri Nadarajan, Jessica Chen-Burger, Jacco van Ossenbruggen, Daniela Giordano, Lynda Hardman, Fang-Pang Lin, Bob Fisher

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Long-term monitoring of the underwater environment is still labour intensive work. Using underwater surveillance cameras to monitor this environment has
the potential advantage to make the task become less labour intensive. Also, the obtained data can be stored making the research reproducible. In this work, a system to analyse long-term underwater camera footage (more than 3 years of 12 hours a day underwater camera footage from 10 cameras) is described. This system uses video processing software to detect and recognise fish species. This footage is processed on supercomputers, which allow marine biologists to request automatic processing on these videos and afterwards analyse the results using a web-interface that allows them to display counts of fish species in the camera footage.

Original language	English
Title of host publication	2012 21st international conference on pattern recognition (ICPR 2012)
Publisher	Red Hook : Curran Associates, Inc.
Number of pages	4
ISBN (Print)	9781467322164
Publication status	Published - 2012

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Boom Huang et al 2012 Long-term underwater camera surveillance for monitoring and analysis of fish populationsSubmitted manuscript, 2.96 MB

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Boom, B., Huang, P. X., Beyan, C., Spampinato, C., Palazzo, S., He, J., Beauxis-Aussalet, E., Lin, S-I., Chou, H-M., Nadarajan, G., Chen-Burger, J., van Ossenbruggen, J., Giordano, D., Hardman, L., Lin, F-P., & Fisher, B. (2012). Long-term underwater camera surveillance for monitoring and analysis of fish populations. In 2012 21st international conference on pattern recognition (ICPR 2012) Red Hook : Curran Associates, Inc.. http://homepages.inf.ed.ac.uk/rbf/VAIB12PAPERS/boom.pdf

@inproceedings{6df9fc60a46e40b2a2d46b93daaa1b9b,

title = "Long-term underwater camera surveillance for monitoring and analysis of fish populations",

abstract = "Long-term monitoring of the underwater environment is still labour intensive work. Using underwater surveillance cameras to monitor this environment hasthe potential advantage to make the task become less labour intensive. Also, the obtained data can be stored making the research reproducible. In this work, a system to analyse long-term underwater camera footage (more than 3 years of 12 hours a day underwater camera footage from 10 cameras) is described. This system uses video processing software to detect and recognise fish species. This footage is processed on supercomputers, which allow marine biologists to request automatic processing on these videos and afterwards analyse the results using a web-interface that allows them to display counts of fish species in the camera footage.",

author = "Bastiaan Boom and Huang, {Phoenix X.} and C. Beyan and Concetto Spampinato and Simone Palazzo and Jiyin He and Emmanuelle Beauxis-Aussalet and Sun-In Lin and Hsiu-Mei Chou and Gayathri Nadarajan and Jessica Chen-Burger and {van Ossenbruggen}, Jacco and Daniela Giordano and Lynda Hardman and Fang-Pang Lin and Bob Fisher",

year = "2012",

language = "English",

isbn = " 9781467322164",

booktitle = "2012 21st international conference on pattern recognition (ICPR 2012)",

publisher = "Red Hook : Curran Associates, Inc.",

}

Boom, B, Huang, PX, Beyan, C, Spampinato, C, Palazzo, S, He, J, Beauxis-Aussalet, E, Lin, S-I, Chou, H-M, Nadarajan, G, Chen-Burger, J, van Ossenbruggen, J, Giordano, D, Hardman, L, Lin, F-P & Fisher, B 2012, Long-term underwater camera surveillance for monitoring and analysis of fish populations. in 2012 21st international conference on pattern recognition (ICPR 2012). Red Hook : Curran Associates, Inc. <http://homepages.inf.ed.ac.uk/rbf/VAIB12PAPERS/boom.pdf>

TY - GEN

T1 - Long-term underwater camera surveillance for monitoring and analysis of fish populations

AU - Boom, Bastiaan

AU - Huang, Phoenix X.

AU - Beyan, C.

AU - Spampinato, Concetto

AU - Palazzo, Simone

AU - He, Jiyin

AU - Beauxis-Aussalet, Emmanuelle

AU - Lin, Sun-In

AU - Chou, Hsiu-Mei

AU - Nadarajan, Gayathri

AU - Chen-Burger, Jessica

AU - van Ossenbruggen, Jacco

AU - Giordano, Daniela

AU - Hardman, Lynda

AU - Lin, Fang-Pang

AU - Fisher, Bob

PY - 2012

Y1 - 2012

N2 - Long-term monitoring of the underwater environment is still labour intensive work. Using underwater surveillance cameras to monitor this environment hasthe potential advantage to make the task become less labour intensive. Also, the obtained data can be stored making the research reproducible. In this work, a system to analyse long-term underwater camera footage (more than 3 years of 12 hours a day underwater camera footage from 10 cameras) is described. This system uses video processing software to detect and recognise fish species. This footage is processed on supercomputers, which allow marine biologists to request automatic processing on these videos and afterwards analyse the results using a web-interface that allows them to display counts of fish species in the camera footage.

AB - Long-term monitoring of the underwater environment is still labour intensive work. Using underwater surveillance cameras to monitor this environment hasthe potential advantage to make the task become less labour intensive. Also, the obtained data can be stored making the research reproducible. In this work, a system to analyse long-term underwater camera footage (more than 3 years of 12 hours a day underwater camera footage from 10 cameras) is described. This system uses video processing software to detect and recognise fish species. This footage is processed on supercomputers, which allow marine biologists to request automatic processing on these videos and afterwards analyse the results using a web-interface that allows them to display counts of fish species in the camera footage.

M3 - Conference contribution

SN - 9781467322164

BT - 2012 21st international conference on pattern recognition (ICPR 2012)

PB - Red Hook : Curran Associates, Inc.

ER -

Long-term underwater camera surveillance for monitoring and analysis of fish populations

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