Integration of multiview stereo and silhouettes via convex functionals on convex domains

Kalin Kolev, Daniel Cremers

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

24 Scopus citations


We propose a convex framework for silhouette and stereo fusion in 3D reconstruction from multiple images. The key idea is to show that the reconstruction problem can be cast as one of minimizing a convex functional where the exact silhouette consistency is imposed as a convex constraint that restricts the domain of admissible functions. As a consequence, we can retain the original stereo-weighted surface area as a cost functional without heuristic modifications by balloon terms or other strategies, yet still obtain meaningful (nonempty) global minimizers. Compared to previous methods, the introduced approach does not depend on initialization and leads to a more robust numerical scheme by removing the bias near the visual hull boundary. We propose an efficient parallel implementation of this convex optimization problem on a graphics card. Based on a photoconsistency map and a set of image silhouettes we are therefore able to compute highly-accurate and silhouette-consistent reconstructions for challenging real-world data sets in less than one minute.

Original languageEnglish
Title of host publicationComputer Vision - ECCV 2008 - 10th European Conference on Computer Vision, Proceedings
PublisherSpringer Verlag
Number of pages14
EditionPART 1
ISBN (Print)3540886818, 9783540886815
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


Conference10th European Conference on Computer Vision, ECCV 2008


Dive into the research topics of 'Integration of multiview stereo and silhouettes via convex functionals on convex domains'. Together they form a unique fingerprint.

Cite this