MPCA: Multilinear Principal Component Analysis of Tensor Objects

@article{Lu2008MPCAMP,
  title={MPCA: Multilinear Principal Component Analysis of Tensor Objects},
  author={Haiping Lu and K. Plataniotis and A. Venetsanopoulos},
  journal={IEEE Transactions on Neural Networks},
  year={2008},
  volume={19},
  pages={18-39}
}
This paper introduces a multilinear principal component analysis (MPCA) framework for tensor object feature extraction. Objects of interest in many computer vision and pattern recognition applications, such as 2D/3D images and video sequences are naturally described as tensors or multilinear arrays. The proposed framework performs feature extraction by determining a multilinear projection that captures most of the original tensorial input variation. The solution is iterative in nature and it… Expand
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