Image de-fencing revisited

Minwoo Park, Kyle Brocklehurst, Robert T. Collins, Yanxi Liu

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

27 Scopus citations

Abstract

We introduce a novel image defencing method suitable for consumer photography, where plausible results must be achieved under common camera settings. First, detection of lattices with see-through texels is performed in an iterative process using online learning and classification from intermediate results to aid subsequent detection. Then, segmentation of the foreground is performed using accumulated statistics from all lattice points. Next, multi-view inpainting is performed to fill in occluded areas with information from shifted views where parts of the occluded regions may be visible. For regions occluded in all views, we use novel symmetry-augmented inpainting, which combines traditional texture synthesis with an increased pool of candidate patches found by simulating bilateral symmetry patterns from the source image. The results show the effectiveness of our proposed method.

Original languageEnglish (US)
Title of host publicationComputer Vision, ACCV 2010 - 10th Asian Conference on Computer Vision, Revised Selected Papers
Pages422-434
Number of pages13
EditionPART 4
DOIs
StatePublished - Mar 16 2011
Event10th Asian Conference on Computer Vision, ACCV 2010 - Queenstown, New Zealand
Duration: Nov 8 2010Nov 12 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 4
Volume6495 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other10th Asian Conference on Computer Vision, ACCV 2010
CountryNew Zealand
CityQueenstown
Period11/8/1011/12/10

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Image de-fencing revisited'. Together they form a unique fingerprint.

Cite this