Comparison of sparse point distribution models



AbstractThis paper compares several methods for obtaining sparse and compact point distribution models suited for data sets containing many variables. These are evaluated on a database consisting of 3D surfaces of a section of the pelvic bone obtained from CT scans of 33 porcine carcasses. The superior model with respect to sparsity, reconstruction error and interpretability is found to be a varimax rotated model with a threshold applied to small loadings. The models describe the biological variation in the database and are used for developing robotic tools when automating labor-intensive procedures in abattoirs.
KeywordsImage analysis, Point distribution models, Varimax, Sparse PCA, Robotic Tools
TypeJournal paper [With referee]
JournalMachine Vision and Applications
Year2009
PublisherSpringer
NoteDOI: 10.1007/s00138-009-0203-1
BibTeX data [bibtex]
IMM Group(s)Image Analysis & Computer Graphics