Résumé
This paper presents a new interactive web application for the visual identification of plants based on collaborative pictures. Contrary to previous content-based identification methods and systems developed for plants that mainly relied on leaves, or in few other cases on flowers, it makes use of five different organs and plant's views including habit, flowers, fruits, leaves and bark. Thanks to an interactive and visual query widget, the tagging process of the different organs and views is as simple as drag-and-drop operations and does not require any expertise in botany. All training pictures used by the system were continuously collected during one year through a crowdsourcing application that was set up in the scope of a citizen sciences initiative. System-oriented and human-centered evaluations of the application show that the results are already satisfactory and therefore very promising in the long term to identify a richer flora.