Shape Priors by Kernel Density Modeling of PCA Residual Structure

Abstract

Modern image processing techniques increasingly use prior models of the expected distribution of objects. Principal component eigen-models are often selected for shape prior modeling, but are limited in capturing only the second order moment statistics. On the other hand, kernel densities can in concept reproduce arbitrary statistics, but are problematic… (More)
DOI: 10.1109/ICIP.2007.4380022

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