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Learning a Gaussian basis for spectra representation aimed at reflectance classification

Robles-Kelly, Antonio


In this paper, we present a method which aims at learning a Gaussian basis which can be used to represent the reflectance spectra in the image while yielding a high recognition rate when used as input to an SVM classifier. To do this, we view the reflectance spectra as a Gaussian mixture and depart from a maximum-likelihood formulation which allows the introduction of posterior probabilities as a means to computing the mixture weights. This formulation permits the update of the Gaussian basis...[Show more]

CollectionsANU Research Publications
Date published: 2011
Type: Conference paper
Source: Graph connectivity in sparse subspace clustering
DOI: 10.1109/CVPRW.2011.5981791


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