Dataset Open Access

Pollen Video Library for Benchmarking Detection, Classification, Tracking and Novelty Detection Tasks

Nam Cao; Matthias Meyer; Lothar Thiele; Olga Saukh


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  <identifier identifierType="DOI">10.5281/zenodo.4120033</identifier>
  <creators>
    <creator>
      <creatorName>Nam Cao</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-2058-1335</nameIdentifier>
      <affiliation>Institute of Technical Informatics, Graz University of Technology, Austria</affiliation>
    </creator>
    <creator>
      <creatorName>Matthias Meyer</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-6895-2823</nameIdentifier>
      <affiliation>Computer Engineering and Networks Lab, ETH Zurich</affiliation>
    </creator>
    <creator>
      <creatorName>Lothar Thiele</creatorName>
      <affiliation>Computer Engineering and Networks Lab, ETH Zurich</affiliation>
    </creator>
    <creator>
      <creatorName>Olga Saukh</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-7849-3368</nameIdentifier>
      <affiliation>Institute of Technical Informatics, Graz University of Technology, Austria, Complexity Science Hub Vienna, Austria</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Pollen Video Library for Benchmarking Detection, Classification, Tracking and Novelty Detection Tasks</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <dates>
    <date dateType="Issued">2020-10-23</date>
  </dates>
  <resourceType resourceTypeGeneral="Dataset"/>
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    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4120033</alternateIdentifier>
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  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;&lt;strong&gt;Dataset description&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;This dataset contains microscopic images and videos of pollen gathered between Feb. and Aug. 2020 in Graz, Austria.&lt;/p&gt;

&lt;ul&gt;
	&lt;li&gt;
	&lt;p&gt;Pollen images of 16 types:&amp;nbsp;&lt;code&gt;...images_16_types.zip&lt;/code&gt;&lt;/p&gt;

	&lt;ul&gt;
		&lt;li&gt;Acer Pseudoplatanus&lt;/li&gt;
		&lt;li&gt;Aesculus Carnea&lt;/li&gt;
		&lt;li&gt;Alnus&lt;/li&gt;
		&lt;li&gt;Anthoxanthum&lt;/li&gt;
		&lt;li&gt;Betula Pendula&lt;/li&gt;
		&lt;li&gt;Brassica&lt;/li&gt;
		&lt;li&gt;Carpinus&lt;/li&gt;
		&lt;li&gt;Corylus&lt;/li&gt;
		&lt;li&gt;Dactylis Glomerata&lt;/li&gt;
		&lt;li&gt;Fraxinus&lt;/li&gt;
		&lt;li&gt;Pinus Nigra&lt;/li&gt;
		&lt;li&gt;Platanus&lt;/li&gt;
		&lt;li&gt;Populus Nigra&lt;/li&gt;
		&lt;li&gt;Prunus Avium&lt;/li&gt;
		&lt;li&gt;Sequoiadendron Giganteum&lt;/li&gt;
		&lt;li&gt;Taxus Baccata&lt;/li&gt;
	&lt;/ul&gt;
	&lt;/li&gt;
	&lt;li&gt;
	&lt;p&gt;Pollen video library&amp;nbsp;&lt;code&gt;...pollen_video_library.zip&lt;/code&gt;&lt;/p&gt;

	&lt;ul&gt;
		&lt;li&gt;Each type of pollen is in a separate folder, there may be multiple videos per type.&lt;/li&gt;
		&lt;li&gt;In each pollen folder, we included images cropped from the videos by YOLO object detection algorithm trained on a subset of pollen images as described in [1].&lt;/li&gt;
		&lt;li&gt;Cropped file name structure&amp;nbsp;&lt;code&gt;[Video file name]_[TrackingID]_[Image index of a grain]_[Frame index in video]&lt;/code&gt;
		&lt;ul&gt;
			&lt;li&gt;Example, if a grain has 5 images, the file name would be:
			&lt;pre&gt;&lt;code&gt; Anthoxanthum-grass-20200530-122652_0000000_001_00001.jpg
 Anthoxanthum-grass-20200530-122652_0000000_002_00002.jpg
 ...
 Anthoxanthum-grass-20200530-122652_0000000_005_00005.jpg
&lt;/code&gt;&lt;/pre&gt;
			&lt;/li&gt;
		&lt;/ul&gt;
		&lt;/li&gt;
	&lt;/ul&gt;
	&lt;/li&gt;
	&lt;li&gt;
	&lt;p&gt;Field data over 3 days are gathered in Graz in spring 2020.&amp;nbsp;&lt;code&gt;...pollen_field_data.zip&lt;/code&gt;&lt;/p&gt;
	&lt;/li&gt;
	&lt;li&gt;
	&lt;p&gt;Sample code to load the data and visualize the images is in&amp;nbsp;&lt;code&gt;...plot_pollen_sample.py&lt;/code&gt;. Download and extract the file&amp;nbsp;&lt;code&gt;...images_16_types.zip&lt;/code&gt;&amp;nbsp;in the same folder as&amp;nbsp;&lt;code&gt;...plot_pollen_sample.py&lt;/code&gt;&amp;nbsp;to run the example.&lt;/p&gt;
	&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;&lt;strong&gt;Dependecies:&lt;/strong&gt;&lt;/p&gt;

&lt;ul&gt;
	&lt;li&gt;opencv&lt;/li&gt;
	&lt;li&gt;numpy&lt;/li&gt;
	&lt;li&gt;matplotlib&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;&lt;strong&gt;Credit&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;[1] N. Cao, M. Meyer, L. Thiele, and O. Saukh. 2020. Automated Pollen Detection with an Affordable Technology. In Proceedings of the International Conference on Embedded Wireless Systems and Networks (EWSN). 108&amp;ndash;119.&lt;/p&gt;

&lt;pre&gt;&lt;code&gt;@inproceedings{namcao2020pollen,
  title = {Automated Pollen Detection with an Affordable Technology},
  author = {Nam Cao and Matthias Meyer and Lothar Thiele and Olga Saukh},
  booktitle = {Proceedings of the International Conference on Embedded Wireless Systems and Networks (EWSN)},
  pages={108–119}
  month = {2},	
  year = {2020},
}&lt;/code&gt;&lt;/pre&gt;</description>
    <description descriptionType="Other">Appears in the Proceedings of the 3rd Workshop on Data Acquisition To Analysis (DATA '20)</description>
  </descriptions>
</resource>
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