Title :
Comments on "Globally Maximizing, Locally Minimizing: Unsupervised Discriminant Projection with Application to Face and Palm Biometrics"
Author :
Deng, Weihong ; Hu, Jiani ; Guo, Jun ; Zhang, Honggang ; Zhang, Chuang
Author_Institution :
Sch. of Inf. Eng., Beijing Univ. of Posts & Telecommun., Beijing
Abstract :
In (Yang et al., 2007), UDP is proposed to address the limitation of LPP for the clustering and classification tasks. In this communication, we show that the basic ideas of UDP and LPP are identical. In particular, UDP is just a simplified version of LPP on the assumption that the local density is uniform.
Keywords :
authorisation; face recognition; learning (artificial intelligence); matrix algebra; UDP; classification tasks; clustering tasks; face biometrics; locality preserving projection; palm biometrics; unsupervised discriminant projection; Biometrics; Laplace equations; Learning systems; Linear approximation; Scattering; Solid modeling; Face and gesture recognition; Feature evaluation and selection; Statistical; Algorithms; Artificial Intelligence; Biometry; Computer Simulation; Discriminant Analysis; Face; Hand; Humans; Image Interpretation, Computer-Assisted; Models, Biological; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2007.70783
