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Towards Automated Annotation of Benthic Survey Images: Variability of Human Experts and Operational Modes of Automation
by
Gamst, Anthony
, Moriarty, Vincent
, Dunlap, Matthew J.
, Mitchell, B. Greg
, Fan, Tung-Yung
, Chan, Stephen
, Edmunds, Peter J.
, Beijbom, Oscar
, Kline, David I.
, Tan, Chih-Jui
, Smith, Jennifer
, Kriegman, David
, Treibitz, Tali
, Roelfsema, Chris
, Neal, Benjamin P.
in
Accuracy
/ Algae
/ Algorithms
/ Animals
/ Annotations
/ Anthozoa
/ Anthropogenic factors
/ Automation
/ Benthic communities
/ Classification
/ Climate Change
/ Computer science
/ Control theory
/ Coral Reefs
/ Digital imaging
/ Digital photography
/ Ecosystem
/ Ecosystem biology
/ Ecosystems
/ Environmental Monitoring - methods
/ Experts
/ Feasibility studies
/ Functional groups
/ Global climate
/ Humans
/ Hypotheses
/ Image annotation
/ Image Processing, Computer-Assisted - methods
/ Imaging systems
/ Marine biology
/ Marine ecology
/ Models, Statistical
/ Museums
/ Observer Variation
/ Oceanography
/ Organisms
/ Pattern Recognition, Automated
/ Photography
/ Polls & surveys
/ Reefs
/ Reproducibility of Results
/ Seaweed - physiology
/ Surveys
/ Taxonomy
/ Turf
/ Variability
2015
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Towards Automated Annotation of Benthic Survey Images: Variability of Human Experts and Operational Modes of Automation
by
Gamst, Anthony
, Moriarty, Vincent
, Dunlap, Matthew J.
, Mitchell, B. Greg
, Fan, Tung-Yung
, Chan, Stephen
, Edmunds, Peter J.
, Beijbom, Oscar
, Kline, David I.
, Tan, Chih-Jui
, Smith, Jennifer
, Kriegman, David
, Treibitz, Tali
, Roelfsema, Chris
, Neal, Benjamin P.
in
Accuracy
/ Algae
/ Algorithms
/ Animals
/ Annotations
/ Anthozoa
/ Anthropogenic factors
/ Automation
/ Benthic communities
/ Classification
/ Climate Change
/ Computer science
/ Control theory
/ Coral Reefs
/ Digital imaging
/ Digital photography
/ Ecosystem
/ Ecosystem biology
/ Ecosystems
/ Environmental Monitoring - methods
/ Experts
/ Feasibility studies
/ Functional groups
/ Global climate
/ Humans
/ Hypotheses
/ Image annotation
/ Image Processing, Computer-Assisted - methods
/ Imaging systems
/ Marine biology
/ Marine ecology
/ Models, Statistical
/ Museums
/ Observer Variation
/ Oceanography
/ Organisms
/ Pattern Recognition, Automated
/ Photography
/ Polls & surveys
/ Reefs
/ Reproducibility of Results
/ Seaweed - physiology
/ Surveys
/ Taxonomy
/ Turf
/ Variability
2015
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Towards Automated Annotation of Benthic Survey Images: Variability of Human Experts and Operational Modes of Automation
by
Gamst, Anthony
, Moriarty, Vincent
, Dunlap, Matthew J.
, Mitchell, B. Greg
, Fan, Tung-Yung
, Chan, Stephen
, Edmunds, Peter J.
, Beijbom, Oscar
, Kline, David I.
, Tan, Chih-Jui
, Smith, Jennifer
, Kriegman, David
, Treibitz, Tali
, Roelfsema, Chris
, Neal, Benjamin P.
in
Accuracy
/ Algae
/ Algorithms
/ Animals
/ Annotations
/ Anthozoa
/ Anthropogenic factors
/ Automation
/ Benthic communities
/ Classification
/ Climate Change
/ Computer science
/ Control theory
/ Coral Reefs
/ Digital imaging
/ Digital photography
/ Ecosystem
/ Ecosystem biology
/ Ecosystems
/ Environmental Monitoring - methods
/ Experts
/ Feasibility studies
/ Functional groups
/ Global climate
/ Humans
/ Hypotheses
/ Image annotation
/ Image Processing, Computer-Assisted - methods
/ Imaging systems
/ Marine biology
/ Marine ecology
/ Models, Statistical
/ Museums
/ Observer Variation
/ Oceanography
/ Organisms
/ Pattern Recognition, Automated
/ Photography
/ Polls & surveys
/ Reefs
/ Reproducibility of Results
/ Seaweed - physiology
/ Surveys
/ Taxonomy
/ Turf
/ Variability
2015
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Towards Automated Annotation of Benthic Survey Images: Variability of Human Experts and Operational Modes of Automation
Journal Article
Towards Automated Annotation of Benthic Survey Images: Variability of Human Experts and Operational Modes of Automation
2015
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Overview
Global climate change and other anthropogenic stressors have heightened the need to rapidly characterize ecological changes in marine benthic communities across large scales. Digital photography enables rapid collection of survey images to meet this need, but the subsequent image annotation is typically a time consuming, manual task. We investigated the feasibility of using automated point-annotation to expedite cover estimation of the 17 dominant benthic categories from survey-images captured at four Pacific coral reefs. Inter- and intra- annotator variability among six human experts was quantified and compared to semi- and fully- automated annotation methods, which are made available at coralnet.ucsd.edu. Our results indicate high expert agreement for identification of coral genera, but lower agreement for algal functional groups, in particular between turf algae and crustose coralline algae. This indicates the need for unequivocal definitions of algal groups, careful training of multiple annotators, and enhanced imaging technology. Semi-automated annotation, where 50% of the annotation decisions were performed automatically, yielded cover estimate errors comparable to those of the human experts. Furthermore, fully-automated annotation yielded rapid, unbiased cover estimates but with increased variance. These results show that automated annotation can increase spatial coverage and decrease time and financial outlay for image-based reef surveys.
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
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