Low-Rank Embedding for Robust Image Feature Extraction

@article{Wong2017LowRankEF,
  title={Low-Rank Embedding for Robust Image Feature Extraction},
  author={Wai Keung Wong and Jiajun Wen and Xiaozhao Fang and Yuwu Lu},
  journal={IEEE Transactions on Image Processing},
  year={2017},
  volume={26},
  pages={2905-2917}
}
Robustness to noises, outliers, and corruptions is an important issue in linear dimensionality reduction. Since the sample-specific corruptions and outliers exist, the class-special structure or the local geometric structure is destroyed, and thus, many existing methods, including the popular manifold learning- based linear dimensionality methods, fail to achieve good performance in recognition tasks. In this paper, we focus on the unsupervised robust linear dimensionality reduction on… CONTINUE READING
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