Multimedia Tools and Applications

, Volume 75, Issue 3, pp 1647–1665 | Cite as

Plant identification: man vs. machine

LifeCLEF 2014 plant identification challenge
  • Pierre Bonnet
  • Alexis Joly
  • Hervé Goëau
  • Julien Champ
  • Christel Vignau
  • Jean-François Molino
  • Daniel Barthélémy
  • Nozha Boujemaa
Article

Abstract

This paper reports a large-scale experiment aimed at evaluating how state-of-art computer vision systems perform in identifying plants compared to human expertise. A subset of the evaluation dataset used within LifeCLEF 2014 plant identification challenge was therefore shared with volunteers of diverse expertise, ranging from the leading experts of the targeted flora to inexperienced test subjects. In total, 16 human runs were collected and evaluated comparatively to the 27 machine-based runs of LifeCLEF challenge. One of the main outcomes of the experiment is that machines are still far from outperforming the best expert botanists at the image-based plant identification competition. On the other side, the best machine runs are competing with experienced botanists and clearly outperform beginners and inexperienced test subjects. This shows that the performances of automated plant identification systems are very promising and may open the door to a new generation of ecological surveillance systems.

Keywords

Visual plant identification Human evaluation Digital data Image analysis 

Notes

Acknowledgments

Part of this work was funded by the Agropolis foundation through the project Pl@ntNet ( http://www.plantnet-project.org/).

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Pierre Bonnet
    • 1
  • Alexis Joly
    • 2
    • 3
  • Hervé Goëau
    • 3
  • Julien Champ
    • 2
    • 4
  • Christel Vignau
    • 5
  • Jean-François Molino
    • 6
  • Daniel Barthélémy
    • 7
  • Nozha Boujemaa
    • 8
  1. 1.CIRADUMR AMAPMontpellierFrance
  2. 2.LIRMMMontpellierFrance
  3. 3.Inria ZENITH teamMontpellierFrance
  4. 4.INRA UMR AGAPMontpellierFrance
  5. 5.Tela BotanicaMontpellierFrance
  6. 6.IRDMontpellierFrance
  7. 7.CIRADBIOS Direction and INRA, UMR AMAPMontpellierFrance
  8. 8.Direction of Saclay CenterINRIAParisFrance

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