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LEARNING STRUCTURALLY DISCRIMINANT FEATURES IN 3D FACES Sreenivas R. Sukumar1
 

Summary: LEARNING STRUCTURALLY DISCRIMINANT FEATURES IN 3D FACES
Sreenivas R. Sukumar1
, Hamparsum Bozdogan2
, David L. Page1
, Andreas F. Koschan1
, Mongi A. Abidi1
Email: {ssrangan, bozdogan, dpage, akoschan, abidi@ utk.edu}
1
Imaging Robotics and Intelligent Systems Lab, Department of Electrical and Computer Engineering,
2
Department of Statistics
The University of Tennessee, Knoxville, USA.
ABSTRACT
In this paper, we derive a data mining framework to analyze
3D features on human faces. The framework leverages
kernel density estimators, genetic algorithm and an
information complexity criterion to identify discriminant
feature-clusters of lower dimensionality. We apply this
framework on human face anthropometry data of 32
features collected from each of the 300 3D face mesh

  

Source: Abidi, Mongi A. - Department of Electrical and Computer Engineering, University of Tennessee
Koschan, Andreas - Imaging, Robotics, and Intelligent Systems, University of Tennessee

 

Collections: Computer Technologies and Information Sciences; Engineering