Semi-automated image analysis for the assessment of megafaunal densities at the Arctic deep-sea observatory HAUSGARTEN
Schoening T, Bergmann M, Purser A, Dannheim J, Gutt J, Nattkemper TW. Semi-automated image analysis for the assessment of megafaunal densities at the Arctic deep-sea observatory HAUSGARTEN. PLoS ONE . 2012;7(6): e38179. Megafauna play an important role in benthic ecosystem function and are sensitive...
Published in: | PLoS ONE |
---|---|
Main Authors: | , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Public Library of Science (PLoS)
2012
|
Subjects: | |
Online Access: | https://nbn-resolving.org/urn:nbn:de:0070-pub-24944580 https://pub.uni-bielefeld.de/record/2494458 https://pub.uni-bielefeld.de/download/2494458/2509590 |
id |
ftubbiepub:oai:pub.uni-bielefeld.de:2494458 |
---|---|
record_format |
openpolar |
spelling |
ftubbiepub:oai:pub.uni-bielefeld.de:2494458 2023-05-15T14:55:39+02:00 Semi-automated image analysis for the assessment of megafaunal densities at the Arctic deep-sea observatory HAUSGARTEN Schoening, Timm Bergmann, Melanie Purser, Autun Dannheim, Jennifer Gutt, Julian Nattkemper, Tim Wilhelm 2012 https://nbn-resolving.org/urn:nbn:de:0070-pub-24944580 https://pub.uni-bielefeld.de/record/2494458 https://pub.uni-bielefeld.de/download/2494458/2509590 eng eng Public Library of Science (PLoS) info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0038179 info:eu-repo/semantics/altIdentifier/issn/1932-6203 info:eu-repo/semantics/altIdentifier/wos/000305343900020 info:eu-repo/semantics/altIdentifier/pmid/22719868 https://nbn-resolving.org/urn:nbn:de:0070-pub-24944580 https://pub.uni-bielefeld.de/record/2494458 https://pub.uni-bielefeld.de/download/2494458/2509590 info:eu-repo/semantics/openAccess https://rightsstatements.org/vocab/InC/1.0/ ddc:570 http://purl.org/coar/resource_type/c_6501 info:eu-repo/semantics/article doc-type:article text 2012 ftubbiepub https://doi.org/10.1371/journal.pone.0038179 2022-02-08T22:32:37Z Schoening T, Bergmann M, Purser A, Dannheim J, Gutt J, Nattkemper TW. Semi-automated image analysis for the assessment of megafaunal densities at the Arctic deep-sea observatory HAUSGARTEN. PLoS ONE . 2012;7(6): e38179. Megafauna play an important role in benthic ecosystem function and are sensitive indicators of environmental change. Non-invasive monitoring of benthic communities can be accomplished by seafloor imaging. However, manual quantification of megafauna in images is labor-intensive and therefore, this organism size class is often neglected in ecosystem studies. Automated image analysis has been proposed as a possible approach to such analysis, but the heterogeneity of megafaunal communities poses a non-trivial challenge for such automated techniques. Here, the potential of a generalized object detection architecture, referred to as iSIS (intelligent Screening of underwater Image Sequences), for the quantification of a heterogenous group of megafauna taxa is investigated. The iSIS system is tuned for a particular image sequence (i.e. a transect) using a small subset of the images, in which megafauna taxa positions were previously marked by an expert. To investigate the potential of iSIS and compare its results with those obtained from human experts, a group of eight different taxa from one camera transect of seafloor images taken at the Arctic deep-sea observatory HAUSGARTEN is used. The results show that inter- and intra-observer agreements of human experts exhibit considerable variation between the species, with a similar degree of variation apparent in the automatically derived results obtained by iSIS. Whilst some taxa (e. g. Bathycrinus stalks, Kolga hyalina, small white sea anemone) were well detected by iSIS (i. e. overall Sensitivity: 87%, overall Positive Predictive Value: 67%), some taxa such as the small sea cucumber Elpidia heckeri remain challenging, for both human observers and iSIS. Article in Journal/Newspaper Arctic White Sea PUB - Publications at Bielefeld University Arctic White Sea PLoS ONE 7 6 e38179 |
institution |
Open Polar |
collection |
PUB - Publications at Bielefeld University |
op_collection_id |
ftubbiepub |
language |
English |
topic |
ddc:570 |
spellingShingle |
ddc:570 Schoening, Timm Bergmann, Melanie Purser, Autun Dannheim, Jennifer Gutt, Julian Nattkemper, Tim Wilhelm Semi-automated image analysis for the assessment of megafaunal densities at the Arctic deep-sea observatory HAUSGARTEN |
topic_facet |
ddc:570 |
description |
Schoening T, Bergmann M, Purser A, Dannheim J, Gutt J, Nattkemper TW. Semi-automated image analysis for the assessment of megafaunal densities at the Arctic deep-sea observatory HAUSGARTEN. PLoS ONE . 2012;7(6): e38179. Megafauna play an important role in benthic ecosystem function and are sensitive indicators of environmental change. Non-invasive monitoring of benthic communities can be accomplished by seafloor imaging. However, manual quantification of megafauna in images is labor-intensive and therefore, this organism size class is often neglected in ecosystem studies. Automated image analysis has been proposed as a possible approach to such analysis, but the heterogeneity of megafaunal communities poses a non-trivial challenge for such automated techniques. Here, the potential of a generalized object detection architecture, referred to as iSIS (intelligent Screening of underwater Image Sequences), for the quantification of a heterogenous group of megafauna taxa is investigated. The iSIS system is tuned for a particular image sequence (i.e. a transect) using a small subset of the images, in which megafauna taxa positions were previously marked by an expert. To investigate the potential of iSIS and compare its results with those obtained from human experts, a group of eight different taxa from one camera transect of seafloor images taken at the Arctic deep-sea observatory HAUSGARTEN is used. The results show that inter- and intra-observer agreements of human experts exhibit considerable variation between the species, with a similar degree of variation apparent in the automatically derived results obtained by iSIS. Whilst some taxa (e. g. Bathycrinus stalks, Kolga hyalina, small white sea anemone) were well detected by iSIS (i. e. overall Sensitivity: 87%, overall Positive Predictive Value: 67%), some taxa such as the small sea cucumber Elpidia heckeri remain challenging, for both human observers and iSIS. |
format |
Article in Journal/Newspaper |
author |
Schoening, Timm Bergmann, Melanie Purser, Autun Dannheim, Jennifer Gutt, Julian Nattkemper, Tim Wilhelm |
author_facet |
Schoening, Timm Bergmann, Melanie Purser, Autun Dannheim, Jennifer Gutt, Julian Nattkemper, Tim Wilhelm |
author_sort |
Schoening, Timm |
title |
Semi-automated image analysis for the assessment of megafaunal densities at the Arctic deep-sea observatory HAUSGARTEN |
title_short |
Semi-automated image analysis for the assessment of megafaunal densities at the Arctic deep-sea observatory HAUSGARTEN |
title_full |
Semi-automated image analysis for the assessment of megafaunal densities at the Arctic deep-sea observatory HAUSGARTEN |
title_fullStr |
Semi-automated image analysis for the assessment of megafaunal densities at the Arctic deep-sea observatory HAUSGARTEN |
title_full_unstemmed |
Semi-automated image analysis for the assessment of megafaunal densities at the Arctic deep-sea observatory HAUSGARTEN |
title_sort |
semi-automated image analysis for the assessment of megafaunal densities at the arctic deep-sea observatory hausgarten |
publisher |
Public Library of Science (PLoS) |
publishDate |
2012 |
url |
https://nbn-resolving.org/urn:nbn:de:0070-pub-24944580 https://pub.uni-bielefeld.de/record/2494458 https://pub.uni-bielefeld.de/download/2494458/2509590 |
geographic |
Arctic White Sea |
geographic_facet |
Arctic White Sea |
genre |
Arctic White Sea |
genre_facet |
Arctic White Sea |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0038179 info:eu-repo/semantics/altIdentifier/issn/1932-6203 info:eu-repo/semantics/altIdentifier/wos/000305343900020 info:eu-repo/semantics/altIdentifier/pmid/22719868 https://nbn-resolving.org/urn:nbn:de:0070-pub-24944580 https://pub.uni-bielefeld.de/record/2494458 https://pub.uni-bielefeld.de/download/2494458/2509590 |
op_rights |
info:eu-repo/semantics/openAccess https://rightsstatements.org/vocab/InC/1.0/ |
op_doi |
https://doi.org/10.1371/journal.pone.0038179 |
container_title |
PLoS ONE |
container_volume |
7 |
container_issue |
6 |
container_start_page |
e38179 |
_version_ |
1766327676874784768 |