Fast robust large-scale mapping from video and internet photo collections

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

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents a system approaching fully automatic 3D modeling of large-scale environments. Our system takes as input either a video stream or collection of photographs obtained from Internet photo sharing web-sites such as Flickr. The system achieves high computational performance through algorithmic optimizations for efficient robust estimation, the use of image-based recognition for efficient grouping of similar images, and two-stage stereo estimation for video streams that reduces the computational cost while maintaining competitive modeling results. In addition to algorithmic advances, we achieve a major improvement in computational speed through parallelization and execution on commodity graphics hardware. These improvements lead to real-time video processing and to reconstruction from tens of thousands of images within the span of a day on a single commodity computer. We demonstrate modeling results on a variety of real-world video sequences and photo collections.

Original languageEnglish (US)
Pages (from-to)538-549
Number of pages12
JournalISPRS Journal of Photogrammetry and Remote Sensing
Volume65
Issue number6
DOIs
StatePublished - Nov 2010
Externally publishedYes

Keywords

  • 3D modeling from video
  • 3D registration video
  • Camera registration photo collections

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering (miscellaneous)
  • Computer Science Applications
  • Computers in Earth Sciences

Fingerprint Dive into the research topics of 'Fast robust large-scale mapping from video and internet photo collections'. Together they form a unique fingerprint.

Cite this