Computer Science and Information Engineering, World Congress on (2009)
Los Angeles, California USA
Mar. 31, 2009 to Apr. 2, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.191
A new classification method called Affine Subspace Nearest Points (ASNP) algorithm is presented in this paper. Similar to the idea of the geometrical explanation of Support Vector Machines (SVMs), the ASNP algorithm designed by us as a binary classifier extends the areas searched for the nearest points from the convex hulls in SVM to affine subspaces, and constructs the decision hyperplane separating the affine subspaces with equivalent margin. We combine the algorithm with the 2D wavelet transform (WT) for face recognition. The low frequency features of face images extracted by 2D wavelet transform are employed as the inputs of the ASNP classifiers. Experiments on the ORL face database show that the proposed method obtains good recognition accuracy.
classification, recognition, SVM, affine subspace, data mining, face recognition.
Z. Xiaofei and S. Yong, "Affine Subspace Nearest Points Classification Algorithm for Wavelet Face Recognition," 2009 WRI World Congress on Computer Science and Information Engineering, CSIE(CSIE), Los Angeles, CA, 2009, pp. 684-688.