Two-Dimensional Color Uncorrelated Principal Component Analysis for Feature Extraction with Application to Face Recognition

Cairong Zhao; Duoqian Miao

doi:10.1007/978-3-319-02961-0_17

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Two-Dimensional Color Uncorrelated Principal Component Analysis for Feature Extraction with Application to Face Recognition

Cairong Zhao Duoqian Miao

Year: 2013 Lecture notes in computer science Pages: 138-145 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-319-02961-0_17

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Keywords:

Artificial intelligence Uncorrelated Pattern recognition (psychology) Principal component analysis Computer science Facial recognition system Face (sociological concept) Independent component analysis Feature extraction Redundancy (engineering) Subspace topology Computer vision Mathematics Statistics

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Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Remote Sensing and Land Use

Physical Sciences → Earth and Planetary Sciences → Atmospheric Science

Image Retrieval and Classification Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Two-Dimensional Color Uncorrelated Principal Component Analysis for Feature Extraction with Application to Face Recognition

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