LifeCLEF Plant Identification Task 2014
2014
Goëau, Hervé | Joly, Alexis | Bonnet, Pierre | Selmi, Souheil | Molino, Jean-François | Barthélémy, Daniel | Boujemaa, Nozha | Scientific Data Management (ZENITH) ; Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM) ; Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Centre Inria d'Université Côte d'Azur ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria) | Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [Occitanie]) | Centre Inria de Saclay ; Institut National de Recherche en Informatique et en Automatique (Inria) | Agropolis Fondation | University of Scheffield. GBR. | L. Cappellato | N. Ferro | M. Halvey | W. Kraaij
Parti IV. LifeCLEF 2. LifeCLEF Plant Identification Task 2014
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Show more [+] Less [-]English. The LifeCLEFs plant identication task provides a testbed for a system-oriented evaluation of plant identication about 500 species trees and herbaceous plants. Seven types of image content are considered: scan and scan-like pictures of leaf, and 6 kinds of detailed views with unconstrained conditions, directly photographed on the plant: ower, fruit, stem & bark, branch, leaf and entire view. The main originality of this data is that it was specically built through a citizen sciences initiative conducted by Tela Botanica, a French social network of amateur and expert botanists. This makes the task closer to the conditions of a realworld application. This overview presents more precisely the resources and assessments of task, summarizes the retrieval approaches employed by the participating groups, and provides an analysis of the main evaluation results. With a total of ten groups from six countries and with a total of twenty seven submitted runs, involving distinct and original methods, this fourth year task confirms Image & Multimedia Retrieval community interest for biodiversity and botany, and highlights further challenging studies in plant identication
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