Robust Tensor Analysis With L1-Norm

Authors:
Yanwei Pang;Xuelong Li;Yuan Yuan
Affiliations:
Sch. of Electron. Inf. Eng., Tianjin Univ., Tianjin, China;-;-
Venue:
IEEE Transactions on Circuits and Systems for Video Technology
Year:
2010

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Abstract

Tensor analysis plays an important role in modern image and vision computing problems. Most of the existing tensor analysis approaches are based on the Frobenius norm, which makes them sensitive to outliers. In this paper, we propose L1-norm-based tensor analysis (TPCA-L1), which is robust to outliers. Experimental results upon face and other datasets demonstrate the advantages of the proposed approach.