TY - GEN
T1 - Towards more precise social image-tag alignment
AU - Zhou, Ning
AU - Peng, Jinye
AU - Feng, Xiaoyi
AU - Fan, Jianping
PY - 2011
Y1 - 2011
N2 - Large-scale user contributed images with tags are increasingly available on the Internet. However, the uncertainty of the relatedness between the images and the tags prohibit them from being precisely accessible to the public and being leveraged for computer vision tasks. In this paper, a novel algorithm is proposed to better align the images with the social tags. First, image clustering is performed to group the images into a set of image clusters based on their visual similarity contexts. By clustering images into different groups, the uncertainty of the relatedness between images and tags can be significantly reduced. Second, random walk is adopted to re-rank the tags based on a cross-modal tag correlation network which harnesses both image visual similarity contexts and tag co-occurrences. We have evaluated the proposed algorithm on a large-scale Flickr data set and achieved very positive results.
AB - Large-scale user contributed images with tags are increasingly available on the Internet. However, the uncertainty of the relatedness between the images and the tags prohibit them from being precisely accessible to the public and being leveraged for computer vision tasks. In this paper, a novel algorithm is proposed to better align the images with the social tags. First, image clustering is performed to group the images into a set of image clusters based on their visual similarity contexts. By clustering images into different groups, the uncertainty of the relatedness between images and tags can be significantly reduced. Second, random walk is adopted to re-rank the tags based on a cross-modal tag correlation network which harnesses both image visual similarity contexts and tag co-occurrences. We have evaluated the proposed algorithm on a large-scale Flickr data set and achieved very positive results.
KW - Image-tag alignment
KW - relevance re-ranking
KW - tag correlation network
UR - http://www.scopus.com/inward/record.url?scp=78751659358&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-17829-0_5
DO - 10.1007/978-3-642-17829-0_5
M3 - 会议稿件
AN - SCOPUS:78751659358
SN - 3642178286
SN - 9783642178283
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 46
EP - 56
BT - Advances in Multimedia Modeling - 17th International Multimedia Modeling Conference, MMM 2011, Proceedings
T2 - 17th Multimedia Modeling Conference, MMM 2011
Y2 - 5 January 2011 through 7 January 2011
ER -