Paper Info
Title
Consistent parameterization and statistical analysis of human head scans
Abstract
Statistical shape analysis of 3-D scanned human heads provides important information for many applications. Nevertheless, special geometry processing techniques have to be developed for consistently parameterizing scans due to the fact that different scanning projects vary in landmark definition, noise control and other factors. For consistent parameterization, fitting a generic model to each scan has proved to be an effective method. In this paper, improved techniques are presented to solve problems in parameterizing different data sets. Principal Component Analysis (PCA) is thus conducted on the consistently parameterized data sets, and shape variances along principal components are demonstrated. In addition, shape variations analyzed by Independent Component Analysis (ICA) are also presented.
Year
DOI
Venue
2009
10.1007/s00371-009-0316-6
The Visual Computer
Keywords
Field
DocType
shape variance,consistent parameterization,different data set,independent component analysis,shape variation,parameterizing scan,principal component analysis,statistical analysis,3-d scanned human head,statistical shape analysis,consistent parameterization · 3d mesh deformation · principal component analysis · independent component analysis,parameterized data set,principal component,noise control
Data set,Computer science,Artificial intelligence,Human head,Computer vision,Parameterized complexity,Pattern recognition,Geometry processing,Statistical shape analysis,Principal geodesic analysis,Independent component analysis,Statistics,Principal component analysis
Journal
Volume
Issue
ISSN
25
9
1432-2315
Citations 
PageRank 
References 
7
0.59
13
Authors
2
Name
Order
Citations
PageRank
Pengcheng Xi1878.65
Chang Shu2393.48