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Learning structurally discriminant features in 3D faces

9 years 11 months ago
Learning structurally discriminant features in 3D faces
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 models. The feature-subsets that we infer as the output establishes domain knowledge for the challenging problem of 3D face recognition with dense 3D gallery models and sparse or low resolution probes.
Sreenivas R. Sukumar, Hamparsum Bozdogan, David L.
Added 20 Oct 2009
Updated 27 Oct 2009
Type Conference
Year 2008
Where ICIP
Authors Sreenivas R. Sukumar, Hamparsum Bozdogan, David L. Page, Andreas Koschan, Mongi A. Abidi
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