High-quality depth from uncalibrated small motion clip

  • Hyowon Ha
  • , Sunghoon Im
  • , Jaesik Park
  • , Hae Gon Jeon
  • , In So Kweon

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

95 Scopus citations

Abstract

We propose a novel approach that generates a highquality depth map from a set of images captured with a small viewpoint variation, namely small motion clip. As opposed to prior methods that recover scene geometry and camera motions using pre-calibrated cameras, we introduce a self-calibrating bundle adjustment tailored for small motion. This allows our dense stereo algorithm to produce a high-quality depth map for the user without the need for camera calibration. In the dense matching, the distributions of intensity profiles are analyzed to leverage the benefit of having negligible intensity changes within the scene due to the minuscule variation in viewpoint. The depth maps obtained by the proposed framework show accurate and extremely fine structures that are unmatched by previous literature under the same small motion configuration.

Original languageEnglish
Title of host publicationProceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016
PublisherIEEE Computer Society
Pages5413-5421
Number of pages9
ISBN (Electronic)9781467388504
DOIs
StatePublished - 9 Dec 2016
Event29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 - Las Vegas, United States
Duration: 26 Jun 20161 Jul 2016

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume2016-December
ISSN (Print)1063-6919

Conference

Conference29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016
Country/TerritoryUnited States
CityLas Vegas
Period26/06/161/07/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

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