Tag features for geo-aware image classification

Liao, Shuai, Li, Xirong, Shen, Heng Tao, Yang, Yang and Du, Xiaoyong (2015) Tag features for geo-aware image classification. IEEE Transactions on Multimedia, 17 7: 1058-1067. doi:10.1109/TMM.2015.2436057

Author Liao, Shuai
Li, Xirong
Shen, Heng Tao
Yang, Yang
Du, Xiaoyong
Title Tag features for geo-aware image classification
Journal name IEEE Transactions on Multimedia   Check publisher's open access policy
ISSN 1520-9210
Publication date 2015-07
Sub-type Article (original research)
DOI 10.1109/TMM.2015.2436057
Open Access Status Not yet assessed
Volume 17
Issue 7
Start page 1058
End page 1067
Total pages 10
Place of publication Piscataway, NJ, United States
Publisher Institute of Electrical and Electronics Engineers
Collection year 2016
Language eng
Abstract The use of geo tags in recording the location at which a picture was taken is becoming part of image metadata . Therefore , studying approaches to image classification that can favorably exploit both geo tags and the underlying geo context has become an emerging topic. This paper contributes to geo-aware image classification by studying how to encode geo information into image representation. Given a geo-tagged image, we propose to extract geo-aware tag features by tag propagation from the geo and visual neighbors of the given image. Depending on what neighbors are used and how they are weighted, we present and compare eight variants of geo-aware tag features. Using millions of Flickr images as source data for tag feature extraction, experiments on a popular benchmark set justify the effectiveness and robustness of the proposed tag features for geo-aware image classification.
Keyword Geo tags
Geo-aware image classification
Tag features
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Information Technology and Electrical Engineering Publications
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Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
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