FIRE in ImageCLEF 2007: Support Vector Machines and Logistic Models to Fuse Image Descriptors for Photo Retrieval

被引：0

作者：

Gass, Tobias ^{[1
]}

Weyand, Tobias ^{[1
]}

Deselaers, Thomas ^{[1
]}

Ney, Hermann ^{[1
]}

机构：

[1] Rhein Westfal TH Aachen, Human Language Technol & Pattern Recognit Grp, Aachen, Germany

来源：

ADVANCES IN MULTILINGUAL AND MULTIMODAL INFORMATION RETRIEVAL | 2008年 / 5152卷

关键词：

content-based image retrieval; feature combination; SIFT features;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Submissions to the photographic retrieval task of the ImageCLEF 2007 evaluation and improvements of our methods that were tested and evaluated after the official benchmark. We use our image retrieval system FIRE to combine a set of different image descriptors. The most important step in combining descriptors is to find a suitable weighting. Here, we evaluate empirically tuned linear combinations, a trained logistic regression model, and support vector machines to fuse the different descriptors. Additionally, clustered SIFT histograms are evaluated for the given task and show very good results - both, alone and in combination with other features. A clear improvement over our evaluation performance is shown consistently over different combination schemes and feature sets.

引用

页码：492 / 499

页数：8