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Discriminative Hessian Eigenmaps for face recognition
2010
2010 IEEE International Conference on Acoustics, Speech and Signal Processing
Dimension reduction algorithms have attracted a lot of attentions in face recognition because they can select a subset of effective and efficient discriminative features in the face images. Most of dimension reduction algorithms can not well model both the intra-class geometry and interclass discrimination simultaneously. In this paper, we introduce the Discriminative Hessian Eigenmaps (DHE), a novel dimension reduction algorithm to address this problem. DHE will consider encoding the geometric
doi:10.1109/icassp.2010.5495241
dblp:conf/icassp/SiTC10
fatcat:uxcnew6imjbq3hibtldusmeafm