Plant identification: Man vs. Machine

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 2 Pierre Bonnet et al. systems are very promising and may open the door to a new generation of ecological surveillance systems.
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Soumis le : mardi 11 août 2015 - 16:01:52
Dernière modification le : mercredi 5 décembre 2018 - 14:26:05
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Pierre Bonnet, Alexis Joly, Hervé Goëau, Julien Champ, Christel Vignau, et al.. Plant identification: Man vs. Machine. Multimedia Tools and Applications, Springer Verlag, 2016, LifeCLEF 2014 plant identification challenge, 75 (3), pp.1647-1665. 〈10.1007/s11042-015-2607-4〉. 〈hal-01182778〉



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