Correlative Linear Neighborhood Propagation for Video Annotation
- 16 December 2008
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)
- Vol. 39 (2), 409-416
- https://doi.org/10.1109/tsmcb.2008.2006045
Abstract
Recently, graph-based semi-supervised learning methods have been widely applied in multimedia research area. However, for the application of video semantic annotation in multi-label setting, these methods neglect an important characteristic of video data: The semantic concepts appear correlatively and interact naturally with each other rather than exist in isolation. In this paper, we adapt this semantic correlation into graph-based semi-supervised learning and propose a novel method named correlative linear neighborhood propagation to improve annotation performance. Experiments conducted on the Text REtrieval Conference VIDeo retrieval evaluation data set have demonstrated its effectiveness and efficiency.Keywords
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