An experimental comparison of discrete and continuous shape optimization methods

Maria Klodt, Thomas Schoenemann, Kalin Kolev, Marek Schikora, Daniel Cremers

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

37 Scopus citations

Abstract

Shape optimization is a problem which arises in numerous computer vision problems such as image segmentation and multiview reconstruction. In this paper, we focus on a certain class of binary labeling problems which can be globally optimized both in a spatially discrete setting and in a spatially continuous setting. The main contribution of this paper is to present a quantitative comparison of the reconstruction accuracy and computation times which allows to assess some of the strengths and limitations of both approaches. We also present a novel method to approximate length regularity in a graph cut based framework: Instead of using pairwise terms we introduce higher order terms. These allow to represent a more accurate discretization of the L 2-norm in the length term.

Original languageEnglish
Title of host publicationComputer Vision - ECCV 2008 - 10th European Conference on Computer Vision, Proceedings
PublisherSpringer Verlag
Pages332-345
Number of pages14
EditionPART 1
ISBN (Print)3540886818, 9783540886815
DOIs
StatePublished - 2008
Externally publishedYes
Event10th European Conference on Computer Vision, ECCV 2008 - Marseille, France
Duration: 12 Oct 200818 Oct 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5302 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th European Conference on Computer Vision, ECCV 2008
Country/TerritoryFrance
CityMarseille
Period12/10/0818/10/08

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