The Journal of Machine Learning Research
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Large-Scale Concept Ontology for Multimedia
IEEE MultiMedia
NNk networks and automated annotation for browsing large image collections from the world wide web
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
A survey of content-based image retrieval with high-level semantics
Pattern Recognition
Proceedings of the 6th ACM international conference on Image and video retrieval
Random walk with restart: fast solutions and applications
Knowledge and Information Systems
Automatic image tagging as a random walk with priors on the canonical correlation subspace
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Learning tag relevance by neighbor voting for social image retrieval
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Collaborative learning for image and video annotation
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Proceedings of the 18th international conference on World wide web
Proceedings of the 18th international conference on World wide web
Automatic video tagging using content redundancy
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Descriptive visual words and visual phrases for image applications
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Distance metric learning from uncertain side information with application to automated photo tagging
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Active tagging for image indexing
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Multi-label boosting for image annotation by structural grouping sparsity
Proceedings of the international conference on Multimedia
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Automatic image tagging automatically label images with semantic tags, which significantly facilitate image search and organization. Existing tagging methods often derive the probabilistic or co-occurring tags from the visually similar images, which based on the image level similarity between images. It may result in many noisy tags due to the problem of semantic gap. In this paper, we propose a novel automatic tagging algorithm. It represents each test image with a bag of visual words and a measure to estimate the correlation between visual words and tags is designed. Then, for each test image, its visual words are weighted based on their importance, and the more important visual word contributes more to tag the test image. To tag a test image, we select the tags which have strong correlation with the greatly weighted visual words. We conduct extensive experiments on the real-world image dataset downloaded from Flickr. The results confirm the effectiveness of our algorithm.