A Fast Implementation of PCA-L1 Using Gram-Schmidt Orthogonalization

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概要

• 論文の詳細を見る

• PCA-L1 (principal component analysis based on L1-norm maximization) is an approximate solution of L1-PCA (PCA based on the L1-norm), and has robustness against outliers compared with traditional PCA. However, the more dimensions the feature space has, the more calculation time PCA-L1 consumes. This paper focuses on an initialization procedure of PCA-L1 algorithm, and proposes a fast method of PCA-L1 using Gram-Schmidt orthogonalization. Experimental results on face recognition show that the proposed method works faster than conventional PCA-L1 without decrease of recognition accuracy.

• The Institute of Electronics, Information and Communication Engineersの論文

著者

• KUROKI Yoshimitsu

  Kurume National College of Technology

• HIROKAWA Mariko

  Kurume National College of Technology

関連論文

• An Inter-Prediction Method Using Sparse Representation for High Efficiency Video Coding
• A Fast Implementation of PCA-L1 Using Gram-Schmidt Orthogonalization

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