Two-Dimensional Quaternion Sparse Principle Component Analysis

ICASSP, pp. 1528-1532, 2018.

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Abstract:

Motivated by the facts that, (1), the spatial structure of images and the correlation among color channels are important for color face recognition, and (2), natural face images may be occluded, in this work, we propose two-dimensional quaternion sparse principle component analysis (2DQSPCA) to extract features for color face recognition....More

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