Multi-View Discriminant Analysis

@article{Kan2016MultiViewDA,
  title={Multi-View Discriminant Analysis},
  author={Meina Kan and S. Shan and Haihong Zhang and S. Lao and Xilin Chen},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2016},
  volume={38},
  pages={188-194}
}
  • Meina Kan, S. Shan, +2 authors Xilin Chen
  • Published 2016
  • Computer Science, Medicine
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
In many computer vision systems, the same object can be observed at varying viewpoints or even by different sensors, which brings in the challenging demand for recognizing objects from distinct even heterogeneous views. In this work we propose a Multi-view Discriminant Analysis (MvDA) approach, which seeks for a single discriminant common space for multiple views in a non-pairwise manner by jointly learning multiple view-specific linear transforms. Specifically, our MvDA is formulated to… Expand
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