Statistical shape modeling using point distribution models (PDMs) has been studied extensively for segmentation and other image analysis tasks. Methods investigated in the literat...
Geremy Heitz, Torsten Rohlfing, Calvin R. Maurer J...
A general-purpose object indexingtechnique is described that combines the virtues of principal component analysis with the favorable matching properties of high-dimensional spaces...
XML is becoming the dominant standard for representing and exchanging data on the World Wide Web. The ability to transform and present data in XML is crucial and XSLT (Extensible ...
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
In this paper we address the problem of registering 3D scattered data by the mean of a statistical shape model. This model is built from a training set on which a principal compon...