Recovery of relative depth from a single observation using an uncalibrated (real-aperture) camera

Vinay P. Namboodiri, Subhasis Chaudhuri

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

37 Citations (Scopus)

Abstract

In this paper we investigate the challenging problem of recovering the depth layers in a scene from a single defocused observation. The problem is definitely solvable if there are multiple observations. In this paper we show that one can perceive the depth in the scene even from a single observation. We use the inhomogeneous reverse heat equation to obtain an estimate of the blur, thereby preserving the depth information characterized by the defocus. However, the reverse heat equation, due to its parabolic nature, is divergent. We stabilize the reverse heat equation by considering the gradient degeneration as an effective stopping criterion. The amount of (inverse) diffusion is actually a measure of relative depth. Because of ill-posedness we propose a graph-cuts based method for inferring the depth in the scene using the amount of diffusion as a data likelihood and a smoothness condition on the depth in the scene. The method is verified experimentally on a varied set of test cases.

Original languageEnglish
Title of host publication26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
PublisherIEEE
ISBN (Print)9781424422432
DOIs
Publication statusPublished - 5 Aug 2008
Event26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR - Anchorage, AK, USA United States
Duration: 23 Jun 200828 Jun 2008

Publication series

Name26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

Conference

Conference26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
CountryUSA United States
CityAnchorage, AK
Period23/06/0828/06/08

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering

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