We present a variational integration of nonlinear shape statistics into a Mumford—Shah based segmentation process. The nonlinear statistics are derived from a set of training silhouettes by a novel method of density estimation which can be considered as an extension of kernel PCA to a stochastic framework.
Description
Nonlinear Shape Statistics in Mumford—Shah Based Segmentation - Springer
%0 Book Section
%1 noKey
%A Cremers, Daniel
%A Kohlberger, Timo
%A Schnörr, Christoph
%B Computer Vision — ECCV 2002
%D 2002
%E Heyden, Anders
%E Sparr, Gunnar
%E Nielsen, Mads
%E Johansen, Peter
%I Springer Berlin Heidelberg
%K segmentation variational
%P 93-108
%R 10.1007/3-540-47967-8_7
%T Nonlinear Shape Statistics in Mumford—Shah Based Segmentation
%U http://dx.doi.org/10.1007/3-540-47967-8_7
%V 2351
%X We present a variational integration of nonlinear shape statistics into a Mumford—Shah based segmentation process. The nonlinear statistics are derived from a set of training silhouettes by a novel method of density estimation which can be considered as an extension of kernel PCA to a stochastic framework.
%@ 978-3-540-43744-4
@incollection{noKey,
abstract = {We present a variational integration of nonlinear shape statistics into a Mumford—Shah based segmentation process. The nonlinear statistics are derived from a set of training silhouettes by a novel method of density estimation which can be considered as an extension of kernel PCA to a stochastic framework.},
added-at = {2014-08-25T15:50:25.000+0200},
author = {Cremers, Daniel and Kohlberger, Timo and Schnörr, Christoph},
biburl = {https://www.bibsonomy.org/bibtex/2ced2008c3f1cff7baeeaeea889103204/alex_ruff},
booktitle = {Computer Vision — ECCV 2002},
description = {Nonlinear Shape Statistics in Mumford—Shah Based Segmentation - Springer},
doi = {10.1007/3-540-47967-8_7},
editor = {Heyden, Anders and Sparr, Gunnar and Nielsen, Mads and Johansen, Peter},
interhash = {ba06f55fb09077b04b35a60db103e1b7},
intrahash = {ced2008c3f1cff7baeeaeea889103204},
isbn = {978-3-540-43744-4},
keywords = {segmentation variational},
language = {English},
pages = {93-108},
publisher = {Springer Berlin Heidelberg},
series = {Lecture Notes in Computer Science},
timestamp = {2014-08-25T15:54:23.000+0200},
title = {Nonlinear Shape Statistics in Mumford—Shah Based Segmentation},
url = {http://dx.doi.org/10.1007/3-540-47967-8_7},
volume = 2351,
year = 2002
}