Cross-domain video concept detection using adaptive svms
Proceedings of the 15th international conference on Multimedia
The MIR flickr retrieval evaluation
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
NUS-WIDE: a real-world web image database from National University of Singapore
Proceedings of the ACM International Conference on Image and Video Retrieval
Flexible manifold embedding: a framework for semi-supervised and unsupervised dimension reduction
IEEE Transactions on Image Processing
IEEE Transactions on Multimedia
Local image tagging via graph regularized joint group sparsity
Pattern Recognition
Effective transfer tagging from image to video
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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Nowadays massive amount of web video datum has been emerging on the Internet. To achieve an effective and efficient video retrieval, it is critical to automatically assign semantic keywords to the videos via content analysis. However, most of the existing video tagging methods suffer from the problem of lacking sufficient tagged training videos due to high labor cost of manual tagging. Inspired by the observation that there are much more well-labeled data in other yet relevant types of media (e.g. images), in this paper we study how to build a "cross-media tunnel" to transfer external tag knowledge from image to video. Meanwhile, the intrinsic data structures of both image and video spaces are well explored for inferring tags. We propose a Cross-Media Tag Transfer (CMTT) paradigm which is able to: 1) transfer tag knowledge between image and video by minimizing their distribution difference; 2) infer tags by revealing the underlying manifold structures embedded within both image and video spaces. We also learn an explicit mapping function to handle unseen videos. Experimental results have been reported and analyzed to illustrate the superiority of our proposal.