Fast robust reconstruction of large-scale environments

Jan Michael Frahm, Marc Pollefeys, Svetlana Lazebnik, Brian Clipp, David Gallup, Rahul Raguram, Changchang Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper tackles the active research problem of fast automatic modeling of large-scale environments from videos and unorganized still image collections. We describe a scalable 3D reconstruction framework that leverages recent research in robust estimation, image-based recognition, and stereo depth estimation. High computational speed is achieved through parallelization and execution on commodity graphics hardware. For video, we have implemented a reconstruction system that works in real time; for still photo collections, we have a system that is capable of processing thousands of images in less than a day on a single commodity computer. Modeling results from both systems are shown on a variety of large-scale real-world datasets.

Original languageEnglish (US)
Title of host publication2010 44th Annual Conference on Information Sciences and Systems, CISS 2010
DOIs
StatePublished - 2010
Externally publishedYes
Event44th Annual Conference on Information Sciences and Systems, CISS 2010 - Princeton, NJ, United States
Duration: Mar 17 2010Mar 19 2010

Publication series

Name2010 44th Annual Conference on Information Sciences and Systems, CISS 2010

Other

Other44th Annual Conference on Information Sciences and Systems, CISS 2010
Country/TerritoryUnited States
CityPrinceton, NJ
Period3/17/103/19/10

ASJC Scopus subject areas

  • Information Systems
  • Information Systems and Management

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