Automatic Image Tagging Using Community-Driven Online Image Databases

被引：0
|
作者：
Renn, Marius [1 ]
van Beusekom, Joost [1 ]
Keysers, Daniel [1 ]
Breuel, Thomas M. [1 ]
机构：
[1] Tech Univ Kaiserslautern, IUPR Grp, Kaiserslautern, Germany
来源：
ADAPTIVE MULTIMEDIA RETRIEVAL: IDENTIFYING, SUMMARIZING, AND RECOMMENDING IMAGE AND MUSIC | 2010年 / 5811卷
关键词：
FEATURES;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Automatic image tagging is becoming increasingly important to organize large amounts of image data. To identify concepts in images, these tagging systems rely on large sets of annotated image training sets. In this work we analyze image sets taken from online community-driven image databases, such as Flickr, for use in concept identification. Real-world performance is measured using our flexible tagging system, Tagr.
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页码：112 / 126
页数：15
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