Inspired by the idea of combining subspace learning and regularization techniques, an algorithm called locally discriminant projection of regularized least squares is proposed. To obtain projection subspace, within-class and between-class graph are constructed firstly. Then, the formula of locally discriminant projection is derived. Finally the projection subspace is worked out by regularized least squares. Compared with common algorithms, the proposed algorithm preserves the local geometrical structure of the manifold and the discriminant structure of the manifold. The experimental results on standard face database show effectiveness of the proposed algorithm.
李勇周,罗大庸,刘少强. 基于正则化最小二乘的局部判别投影的人脸识别*[J]. 模式识别与人工智能, 2008, 21(5): 709-712.
LI Yong-Zhou, LUO Da-Yong, LIU Shao-Qiang. Face Recognition Based on Locally Discriminant Projection of Regularized Least Squares. , 2008, 21(5): 709-712.
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