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Towards Confirmable Automated Plant Cover Determination

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Computer Vision – ECCV 2020 Workshops (ECCV 2020)

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Abstract

Changes in plant community composition reflect environmental changes like in land-use and climate. While we have the means to record the changes in composition automatically nowadays, we still lack methods to analyze the generated data masses automatically.

We propose a novel approach based on convolutional neural networks for analyzing the plant community composition while making the results explainable for the user. To realize this, our approach generates a semantic segmentation map while predicting the cover percentages of the plants in the community. The segmentation map is learned in a weakly supervised way only based on plant cover data and therefore does not require dedicated segmentation annotations.

Our approach achieves a mean absolute error of 5.3% for plant cover prediction on our introduced dataset with 9 herbaceous plant species in an imbalanced distribution, and generates segmentation maps, where the location of the most prevalent plants in the dataset is correctly indicated in many images.

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Notes

  1. 1.

    https://www.idiv.de/en/research/platforms_and_networks/idiv_ecotron/experiments/insect_armageddon.html

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Acknowledgements

Matthias Körschens thanks the Carl Zeiss Foundation for the financial support. In addition, we would like to thank Mirco Migliavacca for additional comments on the manuscript.

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Authors and Affiliations

  1. Friedrich Schiller University Jena, Jena, Germany

    Matthias Körschens, Paul Bodesheim, Christine Römermann, Solveig Franziska Bucher, Josephine Ulrich & Joachim Denzler

  2. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany

    Christine Römermann & Joachim Denzler

  3. Michael Stifel Center Jena, Jena, Germany

    Christine Römermann, Solveig Franziska Bucher & Joachim Denzler

Authors
  1. Matthias Körschens
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  2. Paul Bodesheim
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  3. Christine Römermann
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  4. Solveig Franziska Bucher
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  5. Josephine Ulrich
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  6. Joachim Denzler
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Correspondence to Matthias Körschens .

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Editors and Affiliations

  1. University of Clermont Auvergne, Clermont Ferrand, France

    Adrien Bartoli

  2. Università degli Studi di Udine, Udine, Italy

    Andrea Fusiello

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Körschens, M., Bodesheim, P., Römermann, C., Bucher, S.F., Ulrich, J., Denzler, J. (2020). Towards Confirmable Automated Plant Cover Determination. In: Bartoli, A., Fusiello, A. (eds) Computer Vision – ECCV 2020 Workshops. ECCV 2020. Lecture Notes in Computer Science(), vol 12540. Springer, Cham. https://doi.org/10.1007/978-3-030-65414-6_22

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  • DOI: https://doi.org/10.1007/978-3-030-65414-6_22

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