Nearest Neighbor Convex Hull Classification Method for Face Recognition

Authors:
Xiaofei Zhou;Yong Shi
Affiliations:
Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, China 100190;Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, China 100190 and College of Information Science and Technology, University of Nebraska at Omaha, Omaha ...
Venue:
ICCS 2009 Proceedings of the 9th International Conference on Computational Science
Year:
2009

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Abstract

In this paper, nearest neighbor convex hull (NNCH) classification approach is used for face recognition. In NNCH classifier, a convex hull of training samples of a class is taken as the distribution estimation of the class, and Euclidean distance from a test sample to the convex hull (the distance is called convex hull distance) is taken as the similarity measure for classification. Experiments on face data show that the nearest neighbor convex hull approach can lead to better results than those of 1-nearest neighbor (1-NN) classifier and SVM classifiers.