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Local manifold matching for face recognition

10 years 1 months ago
Local manifold matching for face recognition
In this paper, we propose a novel classification method, called local manifold matching (LMM), for face recognition. LMM has great representational capacity of available prototypes and is based on the local linearity assumption that each data point and its k nearest neighbors from the same class lie on a linear manifold locally embedded in the image space. We present a supervised local manifold learning algorithm for learning all locally linear manifold structures. Then we propose the nearest manifold criterion for the classification in which the query feature point is assigned to the most matching face manifold. Experimental results show that kernel PCA incorporated with the LMM classifier achieves the best face recognition performance.
Wei Liu, Wei Fan, Yunhong Wang, Tieniu Tan
Added 23 Oct 2009
Updated 14 Nov 2009
Type Conference
Year 2005
Where ICIP
Authors Wei Liu, Wei Fan, Yunhong Wang, Tieniu Tan
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