Data from: Processing citizen science- and machine-annotated time-lapse imagery for biologically meaningful metrics
Time-lapse cameras facilitate remote and high-resolution monitoring of wild animal and plant communities, but the image data produced require further processing to be useful. Here we publish pipelines to process raw time-lapse imagery, resulting in count data (number of penguins per image) and '...
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ftzenodo:oai:zenodo.org:5105142 2023-05-15T18:03:50+02:00 Data from: Processing citizen science- and machine-annotated time-lapse imagery for biologically meaningful metrics Jones, Fiona M. Arteta, Carlos Zisserman, Andrew Lempitsky, Victor Lintott, Chris J. Hart, Tom 2020-03-26 https://zenodo.org/record/5105142 https://doi.org/10.5061/dryad.94sp17b unknown doi:10.1038/s41597-020-0442-6 https://zenodo.org/communities/dryad https://zenodo.org/record/5105142 https://doi.org/10.5061/dryad.94sp17b oai:zenodo.org:5105142 info:eu-repo/semantics/openAccess https://creativecommons.org/publicdomain/zero/1.0/legalcode computer vision Time-lapse Southern Ocean Spheniscidae Pygoscelis Pygoscelis adeliae Pygoscelis papua Ecological monitoring remote monitoring info:eu-repo/semantics/other dataset 2020 ftzenodo https://doi.org/10.5061/dryad.94sp17b10.1038/s41597-020-0442-6 2023-03-10T14:52:51Z Time-lapse cameras facilitate remote and high-resolution monitoring of wild animal and plant communities, but the image data produced require further processing to be useful. Here we publish pipelines to process raw time-lapse imagery, resulting in count data (number of penguins per image) and 'nearest neighbour distance' measurements. The latter provide useful summaries of colony spatial structure (which can indicate phenological stage) and can be used to detect movement – metrics which could be valuable for a number of different monitoring scenarios, including image capture during aerial surveys. We present two alternative pathways for producing counts: 1) via the Zooniverse citizen science project Penguin Watch and 2) via a computer vision algorithm (Pengbot), and share a comparison of citizen science-, machine learning-, and expert- derived counts. We provide example files for 14 Penguin Watch cameras, generated from 63,070 raw images annotated by 50,445 volunteers. We encourage the use of this large open-source dataset, and the associated processing methodologies, for both ecological studies and continued machine learning and computer vision development. Penguin Watch ManifestThis file contains metadata for each of the 63,070 different images, captured by 14 Penguin Watch time-lapse cameras, included in the repository found at: DOI: https://doi.org/10.5061/dryad.vv36g. The following variables are provided: image name, date/time, Zooniverse ID, path, classification count, state, temperature in Fahrenheit, lunar phase, and a URL link to a thumbnail image. Please see the associated paper for an explanation of these variables.PW_Manifest.csvKraken FilesThis folder contains 14 'Kraken Files' - one for each of the time-lapse cameras described in Jones et al. (2018); DOI: https://doi.org/10.1038/sdata.2018.124. These 'Kraken Files' contain filtered Penguin Watch 'consensus click' data combined with metadata (date/time, temperature in Fahrenheit, lunar phase, and a URL link to a thumbnail image) for the 63,070 ... Dataset Pygoscelis adeliae Pygoscelis papua Southern Ocean Zenodo Southern Ocean Kraken ENVELOPE(14.070,14.070,77.470,77.470) |
institution |
Open Polar |
collection |
Zenodo |
op_collection_id |
ftzenodo |
language |
unknown |
topic |
computer vision Time-lapse Southern Ocean Spheniscidae Pygoscelis Pygoscelis adeliae Pygoscelis papua Ecological monitoring remote monitoring |
spellingShingle |
computer vision Time-lapse Southern Ocean Spheniscidae Pygoscelis Pygoscelis adeliae Pygoscelis papua Ecological monitoring remote monitoring Jones, Fiona M. Arteta, Carlos Zisserman, Andrew Lempitsky, Victor Lintott, Chris J. Hart, Tom Data from: Processing citizen science- and machine-annotated time-lapse imagery for biologically meaningful metrics |
topic_facet |
computer vision Time-lapse Southern Ocean Spheniscidae Pygoscelis Pygoscelis adeliae Pygoscelis papua Ecological monitoring remote monitoring |
description |
Time-lapse cameras facilitate remote and high-resolution monitoring of wild animal and plant communities, but the image data produced require further processing to be useful. Here we publish pipelines to process raw time-lapse imagery, resulting in count data (number of penguins per image) and 'nearest neighbour distance' measurements. The latter provide useful summaries of colony spatial structure (which can indicate phenological stage) and can be used to detect movement – metrics which could be valuable for a number of different monitoring scenarios, including image capture during aerial surveys. We present two alternative pathways for producing counts: 1) via the Zooniverse citizen science project Penguin Watch and 2) via a computer vision algorithm (Pengbot), and share a comparison of citizen science-, machine learning-, and expert- derived counts. We provide example files for 14 Penguin Watch cameras, generated from 63,070 raw images annotated by 50,445 volunteers. We encourage the use of this large open-source dataset, and the associated processing methodologies, for both ecological studies and continued machine learning and computer vision development. Penguin Watch ManifestThis file contains metadata for each of the 63,070 different images, captured by 14 Penguin Watch time-lapse cameras, included in the repository found at: DOI: https://doi.org/10.5061/dryad.vv36g. The following variables are provided: image name, date/time, Zooniverse ID, path, classification count, state, temperature in Fahrenheit, lunar phase, and a URL link to a thumbnail image. Please see the associated paper for an explanation of these variables.PW_Manifest.csvKraken FilesThis folder contains 14 'Kraken Files' - one for each of the time-lapse cameras described in Jones et al. (2018); DOI: https://doi.org/10.1038/sdata.2018.124. These 'Kraken Files' contain filtered Penguin Watch 'consensus click' data combined with metadata (date/time, temperature in Fahrenheit, lunar phase, and a URL link to a thumbnail image) for the 63,070 ... |
format |
Dataset |
author |
Jones, Fiona M. Arteta, Carlos Zisserman, Andrew Lempitsky, Victor Lintott, Chris J. Hart, Tom |
author_facet |
Jones, Fiona M. Arteta, Carlos Zisserman, Andrew Lempitsky, Victor Lintott, Chris J. Hart, Tom |
author_sort |
Jones, Fiona M. |
title |
Data from: Processing citizen science- and machine-annotated time-lapse imagery for biologically meaningful metrics |
title_short |
Data from: Processing citizen science- and machine-annotated time-lapse imagery for biologically meaningful metrics |
title_full |
Data from: Processing citizen science- and machine-annotated time-lapse imagery for biologically meaningful metrics |
title_fullStr |
Data from: Processing citizen science- and machine-annotated time-lapse imagery for biologically meaningful metrics |
title_full_unstemmed |
Data from: Processing citizen science- and machine-annotated time-lapse imagery for biologically meaningful metrics |
title_sort |
data from: processing citizen science- and machine-annotated time-lapse imagery for biologically meaningful metrics |
publishDate |
2020 |
url |
https://zenodo.org/record/5105142 https://doi.org/10.5061/dryad.94sp17b |
long_lat |
ENVELOPE(14.070,14.070,77.470,77.470) |
geographic |
Southern Ocean Kraken |
geographic_facet |
Southern Ocean Kraken |
genre |
Pygoscelis adeliae Pygoscelis papua Southern Ocean |
genre_facet |
Pygoscelis adeliae Pygoscelis papua Southern Ocean |
op_relation |
doi:10.1038/s41597-020-0442-6 https://zenodo.org/communities/dryad https://zenodo.org/record/5105142 https://doi.org/10.5061/dryad.94sp17b oai:zenodo.org:5105142 |
op_rights |
info:eu-repo/semantics/openAccess https://creativecommons.org/publicdomain/zero/1.0/legalcode |
op_doi |
https://doi.org/10.5061/dryad.94sp17b10.1038/s41597-020-0442-6 |
_version_ |
1766174854397034496 |