Continuous global optimization in multiview 3D reconstruction

Kalin Kolev, Maria Klodt, Thomas Brox, Selim Esedoglu, Daniel Cremers

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

11 Scopus citations

Abstract

In this work, we introduce a robust energy model for multiview 3D reconstruction that fuses silhouette- and stereo-based image information. It allows to cope with significant amounts of noise without manual pre-segmentation of the input images. Moreover, we suggest a method that can globally optimize this energy up to the visibility constraint. While similar global optimization has been presented in the discrete context in form of the maxflow-mincut framework, we suggest the use of a continuous counterpart. In contrast to graph cut methods, discretizations of the continuous optimization technique are consistent and independent of the choice of the grid connectivity. Our experiments demonstrate that this leads to visible improvements. Moreover, memory requirements are reduced, allowing for global reconstructions at higher resolutions.

Original languageEnglish
Title of host publicationEnergy Minimization Methods in Computer Vision and Pattern Recognition - 6th International Conference, EMMCVPR, 2007 Proceedings
PublisherSpringer Verlag
Pages441-452
Number of pages12
ISBN (Print)9783540741954
DOIs
StatePublished - 2007
Externally publishedYes
Event6th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2007 - Ezhou, China
Duration: 27 Aug 200729 Aug 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4679 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2007
Country/TerritoryChina
CityEzhou
Period27/08/0729/08/07

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