Visual-based plant species identification from crowdsourced data

Hervé Goëau 1 Alexis Joly 1, 2, * Souheil Selmi 1 Pierre Bonnet 3 Elise Mouysset 4 Laurent Joyeux 1
* Corresponding author
2 ZENITH - Scientific Data Management
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : This demo presents a crowdsourcing web application ded- icated to the access of botanical knowledge through auto- mated identi cation of plant species by visual content. In- spired by citizen sciences, our aim is to speed up the collec- tion and integration of raw botanical observation data, while providing to potential users an easy and e cient access to this botanical knowledge. The result presented during the demo is an enjoying application where anyone can play to shoot fresh cut leaves and observe the relevance of species suggested in spite of various visual di cult queries.
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Hervé Goëau, Alexis Joly, Souheil Selmi, Pierre Bonnet, Elise Mouysset, et al.. Visual-based plant species identification from crowdsourced data. MM'11 - ACM Multimedia 2011, Nov 2011, Scottsdale, United States. pp.0-0, ⟨10.1145/2072298.2072472⟩. ⟨hal-00642236⟩

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