Comments on "Globally Maximizing, Locally Minimizing: Unsupervised Discriminant Projection with Application to Face and Palm Biometrics"

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 u...

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Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence 2008-08, Vol.30 (8), p.1503-1504
Main Authors: Weihong Deng, Jiani Hu, Guo, J., Honggang Zhang, Chuang Zhang
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Biometrics
Biometry - methods
Computer Simulation
Discriminant Analysis
Face - anatomy & histology
Face and gesture recognition
Feature evaluation and selection
Hand - anatomy & histology
Humans
Image Interpretation, Computer-Assisted - methods
Laplace equations
Learning systems
Linear approximation
Models, Biological
Pattern Recognition, Automated - methods
Reproducibility of Results
Scattering
Sensitivity and Specificity
Solid modeling
Statistical
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Summary: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.
ISSN:0162-8828
1939-3539
2160-9292
DOI:10.1109/TPAMI.2007.70783