Scene shape estimation from multiple partly cloudy days

Scott Workman, Richard Souvenir, Nathan Jacobs

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Clouds are a cue for estimating weak correspondences in outdoor cameras. These correspondences encode the uncertain spatio-temporal relationships between pixels both within individual cameras and across networks of cameras. Using this generalized notion of correspondence, we present methods for estimating the geometry of an outdoor scene from: (1) a single calibrated camera, (2) a network of calibrated cameras, and (3) a collection of arbitrary, uncalibrated cameras. Our methods do not require camera motion nor overlapping fields of view, and use simple geometric constraints based on appearance changes caused by cloud shadows. We define these geometric constraints, describe new algorithms for estimating shape given videos from multiple partly cloud days, and evaluate these algorithms on real and synthetic scenes.

Original languageEnglish
Pages (from-to)116-129
Number of pages14
JournalComputer Vision and Image Understanding
Volume134
DOIs
StatePublished - May 1 2015

Bibliographical note

Funding Information:
We gratefully acknowledge the support of DARPA CSSG D11AP00255 .

Publisher Copyright:
© 2014 Elsevier Inc.

Keywords

  • Correspondence estimation
  • Distributed smart cameras
  • Outdoor cameras
  • Shape estimation

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition

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