A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Segmentation of Color-Texture Regions in Images and Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple-Instance Learning for Natural Scene Classification
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Robust Face Recognition via Sparse Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 18th international conference on World wide web
Unified video annotation via multigraph learning
IEEE Transactions on Circuits and Systems for Video Technology
NUS-WIDE: a real-world web image database from National University of Singapore
Proceedings of the ACM International Conference on Image and Video Retrieval
Beyond distance measurement: constructing neighborhood similarity for video annotation
IEEE Transactions on Multimedia - Special section on communities and media computing
Learning social tag relevance by neighbor voting
IEEE Transactions on Multimedia
Proceedings of the ACM International Conference on Image and Video Retrieval
Proceedings of the ACM International Conference on Image and Video Retrieval
Image annotation by kNN-sparse graph-based label propagation over noisily tagged web images
ACM Transactions on Intelligent Systems and Technology (TIST)
A two-view learning approach for image tag ranking
Proceedings of the fourth ACM international conference on Web search and data mining
Content-based tag processing for Internet social images
Multimedia Tools and Applications
Fast Solution of -Norm Minimization Problems When the Solution May Be Sparse
IEEE Transactions on Information Theory
Assistive tagging: A survey of multimedia tagging with human-computer joint exploration
ACM Computing Surveys (CSUR)
Towards relevance and saliency ranking of image tags
Proceedings of the 20th ACM international conference on Multimedia
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Social image tag ranking has emerged as an important research topic due to its application on web image search. This paper presents an adaptive all-season tag ranking algorithm which can handle the images with and without distinct object(s) using different tag ranking strategies. Firstly, based on saliency map derived from the visual attention model, a linear SVM is trained to pre-classify an image as attentive or non-attentive category by using the gray histogram descriptor on the corresponding saliency map. Then, an image with distinct object is processed by the tag saliency ranking algorithm emphasizing distinct object, which combines image saliency map with sparse representation based multi-instance learning algorithm. On the other hand, an image without distinct object can be processed by the tag relevance ranking algorithm via the sparse representation based neighbor-voting strategy. Such adaptive all-season tag ranking strategy can be regarded as taking full advantage of existing tag ranking paradigms. Experiments conducted on well-known image data sets demonstrate the effectiveness of the proposed framework.