Semi-supervised kernel density estimation for video annotation

@article{Wang2009SemisupervisedKD,
  title={Semi-supervised kernel density estimation for video annotation},
  author={Meng Wang and Xian-Sheng Hua and Tao Mei and Richang Hong and Guo-Jun Qi and Yan Song and Li-Rong Dai},
  journal={Computer Vision and Image Understanding},
  year={2009},
  volume={113},
  pages={384-396}
}
Insufficiency of labeled training data is a major obstacle for automatic video annotation. Semi-supervised learning is an effective approach to this problem by leveraging a large amount of unlabeled data. However, existing semi-supervised learning algorithms have not demonstrated promising results in largescale video annotation due to several difficulties, such as large variation of video content and intractable computational cost. In this paper, we propose a novel semi-supervised learning… CONTINUE READING
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