LifeCLEF 2016: Multimedia Life Species Identification Challenges

被引:33
作者
Joly, Alexis [1 ]
Goeau, Hervve [2 ]
Glotin, Herve [3 ]
Spampinato, Concetto [4 ]
Bonnet, Pierre [5 ]
Vellinga, Willem-Pier [6 ]
Champ, Julien [1 ]
Planque, Robert [6 ]
Palazzo, Simone [4 ]
Mueller, Henning [7 ]
机构
[1] Inria, LIRMM, Montpellier, France
[2] IRD, UMR AMAP, Montpellier, France
[3] Univ Toulon & Var, AMU, CNRS LSIS, IUF,ENSAM, Toulon, France
[4] Univ Catania, Catania, Italy
[5] CIRAD, UMR AMAP, Montpellier, France
[6] Xeno Canto Fdn, Breskens, Netherlands
[7] HES SO, Sierre, Switzerland
来源
EXPERIMENTAL IR MEETS MULTILINGUALITY, MULTIMODALITY, AND INTERACTION, CLEF 2016 | 2016年 / 9822卷
关键词
SHAPE;
D O I
10.1007/978-3-319-44564-9_26
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Using multimedia identification tools is considered as one of the most promising solutions to help bridge the taxonomic gap and build accurate knowledge of the identity, the geographic distribution and the evolution of living species. Large and structured communities of nature observers (e.g., iSpot, Xeno-canto, Tela Botanica, etc.) as well as big monitoring equipment have actually started to produce outstanding collections of multimedia records. Unfortunately, the performance of the state-of-the-art analysis techniques on such data is still not well understood and is far from reaching real world requirements. The LifeCLEF lab proposes to evaluate these challenges around 3 tasks related to multimedia information retrieval and fine-grained classification problems in 3 domains. Each task is based on large volumes of real-world data and the measured challenges are defined in collaboration with biologists and environmental stakeholders to reflect realistic usage scenarios. For each task, we report the methodology, the data sets as well as the results and the main outcomes.
引用
收藏
页码:286 / 310
页数:25
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