基于公民科学数据的植物识别任务，评估500种植物的多视角图像检索性能。
LifeCLEF Plant Identification Task 2014
- 采用7类真实场景图像（含花、果、叶等）构建数据集
- 10支团队参与，27次提交，覆盖多种检索方法
- 适合关注生物多样性与图像检索交叉研究的学者
LifeCLEF植物识别任务为500种树木和草本植物的识别提供了一个系统评估平台。共考虑七类图像内容：叶片扫描图及近似扫描图，以及六类在非受限条件下直接拍摄的细节视图——花、果实、茎与树皮、枝条、叶片和整体视图。该数据集由法国植物学社交网络Tela Botanica组织的公民科学项目构建，更贴近真实应用场景。本文详述了任务资源与评估标准，总结了参赛团队采用的检索方法，并分析了主要结果。来自六个国家的10支团队参与，共提交27次运行，展示了图像与多媒体检索领域对生物多样性与植物识别的持续兴趣，并指出了未来研究的挑战方向。
原文摘要 · Abstract (English)
The LifeCLEFs plant identification task provides a testbed for a system-oriented evaluation of plant identification 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: flower, fruit, stem & bark, branch, leaf and entire view. 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 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 identification.
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