In this paper, we first present a simple but effective L1-norm-based two-dimensional principal component analysis (2DPCA). Traditional L2-norm-based least squares criterion is sensitive to outliers, while the newly proposed L1-norm 2DPCA is robust. Experimental results demonstrate its advantages.
|Number of pages||6|
|Journal||IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics|
|Early online date||15 Jan 2010|
|Publication status||Published - Aug 2010|
- L1 norm
- two-dimensional principal component analysis (2DPCA)