The ImageCLEF 2012 Plant Identification Task

International audienceThe ImageCLEF's plant identification task provides a testbed for the system-oriented evaluation of plant identification, more precisely on the 126 tree species identification based on leaf images. Three types of image content are considered: Scan, Scan-like (leaf photographs with a white uniform background), and Photograph (unconstrained leaf with natural background). The main originality of this data is that it was specifically 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 real-world 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 eleven groups from eight countries and with a total of 30 runs submitted, involving distinct and original methods, this second year pilot task confirms Image Retrieval community interest for biodiversity and botany, and highlights further challenging studies in plant identification

Velocity profiles in shear-banding wormlike micelles

Using Dynamic Light Scattering in heterodyne mode, we measure velocity profiles in a much studied system of wormlike micelles (CPCl/NaSal) known to exhibit both shear-banding and stress plateau behavior. Our data provide evidence for the simplest shear-banding scenario, according to which the effective viscosity drop in the system is due to the nucleation and growth of a highly sheared band in the gap, whose thickness linearly increases with the imposed shear rate. We discuss various details of the velocity profiles in all the regions of the flow curve and emphasize on the complex, non-Newtonian nature of the flow in the highly sheared band.Comment: 4 pages, 5 figures, submitted to Phys. Rev. Let

The ImageCLEF 2013 Plant Identification Task

International audienceThe ImageCLEF's plant identification task provides a testbed for a system-oriented evaluation of plant identification about 250 species trees and herbaceous plants based on detailed views of leaves, flowers, fruits, stems and bark or some entire views of the plants. Two types of image content are considered: SheetAsBackgroud which contains only leaves in a front of a generally white uniform background, and NaturalBackground which contains the 5 kinds of detailed views with unconstrained conditions, directly photographed on the plant. The main originality of this data is that it was specifically 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 real-world 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 twelve groups from nine countries and with a total of thirty three runs submitted, involving distinct and original methods, this third year task confirms Image Retrieval community interest for biodiversity and botany, and highlights further challenging studies in plant identification

PlantNet Participation at LifeCLEF2014 Plant Identification Task

International audienceThis paper describes the participation of Inria within the Pl@ntNet project7 at the LifeCLEF2014 plant identication task. The aim of the task was to produce a list of relevant species for each plant observation in a test dataset according to a training dataset. Each plant observation contains several annotated pictures with organ/view tags: Flower, Leaf, Fruit, Stem, Branch, Entire, Scan (exclusively of leaf). Our system treated independently each category of organ/view and then a late hierarchical fusion is used in order to combine the results on visual content analysis from the most local level analysis in pictures to the highest level related to a plant observation. For the photographs of flowers, leaves, fruits, stems, branches and entire views of plants, a large scale matching approach of local features extracted using different spatial constraints is used. For scans, the method combines the large scale matching approach with shape descriptors and geometric parameters on shape boundary. Then, several fusion methods are experimented through the four submitted runs in order to combine hierarchically the local responses to the final response at the plant observation level. The four submitted runs obtained good results and got the 4th to the 7th place over 27 submitted runs by 10 participating team

The ImageCLEF 2013 Plant Identification Task

International audienceThe ImageCLEF's plant identification task provides a testbed for a system-oriented evaluation of plant identification about 250 species trees and herbaceous plants based on detailed views of leaves, flowers, fruits, stems and bark or some entire views of the plants. Two types of image content are considered: SheetAsBackgroud which contains only leaves in a front of a generally white uniform background, and NaturalBackground which contains the 5 kinds of detailed views with unconstrained conditions, directly photographed on the plant. The main originality of this data is that it was specifically 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 real-world 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 twelve groups from nine countries and with a total of thirty three runs submitted, involving distinct and original methods, this third year task confirms Image Retrieval community interest for biodiversity and botany, and highlights further challenging studies in plant identification