Image composition with blurring effect from depth of field

Liu Hai, Ma Lizhuang

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

Abstract

This paper describes a new framework for image composition according to the blurring effect bred by changing depth of field from the target images. The framework involves two stages: a learning phase, in which the target image, with one part of the image purported to be "further" and another part "near", is presented as "learning data" and the learned filter is applied to some objects in source image; and a composition phase, in which those blurred objects of source image are composed into the "further" part of the target image. The framework is based on a simple multiscale Gaussian filter, inspired primarily by recent results in texture synthesis and image editing.

Original languageEnglish
Title of host publicationEntertainment Computing - ICEC 2007 - 6th International Conference, Proceedings
Pages98-103
Number of pages6
StatePublished - 2007
Externally publishedYes
Event6th International Conference of Entertainment Computing, ICEC 2007 - Shanghai, China
Duration: 15 Sep 200717 Sep 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4740 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Conference of Entertainment Computing, ICEC 2007
Country/TerritoryChina
CityShanghai
Period15/09/0717/09/07

Keywords

  • Gaussian filter
  • Image editing
  • Markov random fields
  • Texture synthesis
  • Texture transfer

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