DocumentCode
3016279
Title
Partially observed objects localization with PCA and KPCA models
Author
Romaniuk, B. ; Guilloux, V. ; Desvignes, M. ; Deshayes, M.-J.
Author_Institution
GREYC Image, Caen, France
fYear
2004
fDate
28-30 March 2004
Firstpage
80
Lastpage
84
Abstract
We deal with the problem of partially observed objects. These objects are defined by sets of points and their shape variations are represented by a statistical model. We present two models: a linear model based on PCA and a non-linear model based on KPCA (kernel PCA). The present work attempts to localize non visible parts of an object from visible parts and from the model, explicitly. using the variability represented by the model. Both are applied to the cephalometric problem with good results.
Keywords
medical image processing; object detection; principal component analysis; radiography; KPCA; cephalometric problem; kernel PCA; linear model; nonlinear model; orthodontists; partially observed object localization; radiographs; shape analysis; statistical model; Active appearance model; Active shape model; Cranial; Eigenvalues and eigenfunctions; Image analysis; Kernel; Modal analysis; Principal component analysis; Radiography; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Analysis and Interpretation, 2004. 6th IEEE Southwest Symposium on
Print_ISBN
0-7803-8387-7
Type
conf
DOI
10.1109/IAI.2004.1300949
Filename
1300949
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