Automated video imaging system for counting deep-sea bioluminescence organisms events

Luca Mazzei; Simone Marini; Jessica Craig; Jacopo Aguzzi; Emanuela Fanelli; Imants G. Priede

doi:10.1109/CVAUI.2014.15

Automated video imaging system for counting deep-sea bioluminescence organisms events

Luca Mazzei, Simone Marini, Jessica Craig, Jacopo Aguzzi, Emanuela Fanelli, Imants G. Priede

Aberdeen Centre For Environmental Sustainability

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

10 Citations (Scopus)

Abstract

Bioluminescence refers to the production of ecologically functional light by living organisms. It is widespread in the marine environment, where it occurs in a broad range of phyla. The deep pelagic ocean is the largest biome on earth and is chronically under-sampled. Underwater camera systems offer a rapid sampling method for this zone. In the current study, the ICDeep (Image Intensied Charge Coupled Device for Deep-sea research) profiler was used to record digital video of bioluminescent organisms through the deep water column. This work proposes a new automatic detection and counting methods for bioluminescent organisms represented as ashes within video data acquired through the camera based on computer vision algorithms. The proposed method has been validated by a ground truthed sequence of bioluminescent events resulting in a high correct detection rate and real time processing execution.

Original language	English
Title of host publication	Proceedings
Subtitle of host publication	2014 ICPR Workshop on Computer Vision for Analysis of Underwater Imagery (CVAUI)
Publisher	IEEE Explore
Pages	57-64
Number of pages	8
ISBN (Electronic)	9781479967131
ISBN (Print)	9781479967148
DOIs	https://doi.org/10.1109/CVAUI.2014.15
Publication status	Published - 20 Nov 2014
Event	2014 ICPR Workshop on Computer Vision for Analysis of Underwater Imagery - Stockholm, Sweden Duration: 24 Aug 2014 → 24 Aug 2014

Conference

Conference	2014 ICPR Workshop on Computer Vision for Analysis of Underwater Imagery
Abbreviated title	CVAUI 2014
Country/Territory	Sweden
City	Stockholm
Period	24/08/14 → 24/08/14

Bibliographical note

Acknowledgment
The authors would like to thank BIOFUN and 3DStereoMonitor projects. Jacopo
Aguzzi is a Postdoctoral Fellow of the Ram´on y Cajal Program (MICINN).

Keywords

bioluminescent organisms
deep sea
under- water computer vision
underwater object recognition.
video tracking

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/CVAUI.2014.15Licence: Unspecified

Cite this

Mazzei, L, Marini, S, Craig, J, Aguzzi, J, Fanelli, E & Priede, IG 2014, Automated video imaging system for counting deep-sea bioluminescence organisms events. in Proceedings: 2014 ICPR Workshop on Computer Vision for Analysis of Underwater Imagery (CVAUI). IEEE Explore, pp. 57-64, 2014 ICPR Workshop on Computer Vision for Analysis of Underwater Imagery, Stockholm, Sweden, 24/08/14. https://doi.org/10.1109/CVAUI.2014.15

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abstract = "Bioluminescence refers to the production of ecologically functional light by living organisms. It is widespread in the marine environment, where it occurs in a broad range of phyla. The deep pelagic ocean is the largest biome on earth and is chronically under-sampled. Underwater camera systems offer a rapid sampling method for this zone. In the current study, the ICDeep (Image Intensied Charge Coupled Device for Deep-sea research) profiler was used to record digital video of bioluminescent organisms through the deep water column. This work proposes a new automatic detection and counting methods for bioluminescent organisms represented as ashes within video data acquired through the camera based on computer vision algorithms. The proposed method has been validated by a ground truthed sequence of bioluminescent events resulting in a high correct detection rate and real time processing execution.",

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author = "Luca Mazzei and Simone Marini and Jessica Craig and Jacopo Aguzzi and Emanuela Fanelli and Priede, {Imants G.}",

note = "Acknowledgment The authors would like to thank BIOFUN and 3DStereoMonitor projects. Jacopo Aguzzi is a Postdoctoral Fellow of the Ram´on y Cajal Program (MICINN).; 2014 ICPR Workshop on Computer Vision for Analysis of Underwater Imagery, CVAUI 2014 ; Conference date: 24-08-2014 Through 24-08-2014",

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AU - Marini, Simone

AU - Craig, Jessica

AU - Aguzzi, Jacopo

AU - Fanelli, Emanuela

AU - Priede, Imants G.

N1 - Acknowledgment The authors would like to thank BIOFUN and 3DStereoMonitor projects. Jacopo Aguzzi is a Postdoctoral Fellow of the Ram´on y Cajal Program (MICINN).

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N2 - Bioluminescence refers to the production of ecologically functional light by living organisms. It is widespread in the marine environment, where it occurs in a broad range of phyla. The deep pelagic ocean is the largest biome on earth and is chronically under-sampled. Underwater camera systems offer a rapid sampling method for this zone. In the current study, the ICDeep (Image Intensied Charge Coupled Device for Deep-sea research) profiler was used to record digital video of bioluminescent organisms through the deep water column. This work proposes a new automatic detection and counting methods for bioluminescent organisms represented as ashes within video data acquired through the camera based on computer vision algorithms. The proposed method has been validated by a ground truthed sequence of bioluminescent events resulting in a high correct detection rate and real time processing execution.

AB - Bioluminescence refers to the production of ecologically functional light by living organisms. It is widespread in the marine environment, where it occurs in a broad range of phyla. The deep pelagic ocean is the largest biome on earth and is chronically under-sampled. Underwater camera systems offer a rapid sampling method for this zone. In the current study, the ICDeep (Image Intensied Charge Coupled Device for Deep-sea research) profiler was used to record digital video of bioluminescent organisms through the deep water column. This work proposes a new automatic detection and counting methods for bioluminescent organisms represented as ashes within video data acquired through the camera based on computer vision algorithms. The proposed method has been validated by a ground truthed sequence of bioluminescent events resulting in a high correct detection rate and real time processing execution.

KW - bioluminescent organisms

KW - deep sea

KW - under- water computer vision

KW - underwater object recognition.

KW - video tracking

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AN - SCOPUS:84916631933

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BT - Proceedings

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T2 - 2014 ICPR Workshop on Computer Vision for Analysis of Underwater Imagery

Y2 - 24 August 2014 through 24 August 2014

ER -

Automated video imaging system for counting deep-sea bioluminescence organisms events

Abstract

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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