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Nearest intra-class space classifier for face recognition

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4 Author(s)
Wei Liu ; Inst. of Autom., Chinese Acad. of Sci., Beijing, China ; Yunhong Wang ; S. Z. Li ; Tieniu Tan

We propose a novel classification method, called nearest intra-class space (NICS), for face recognition. In our method, the distribution of face patterns of each person is represented by the intra-class space to capture all intra-class variations. Then, a regular principal subspace is derived from each intra-class space using principal component analysis. The classification is based on the nearest weighted distance, combining distance-from-subspace and distance-in-subspace, between the query face and each intra-class subspace. Experimental results show that the NICS classifier outperforms other classifiers in terms of recognition performance.

Published in:

Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on  (Volume:4 )

Date of Conference:

23-26 Aug. 2004