Biggerpicture: data-driven image extrapolation using graph matching

Wang, Miao, Lai, Yu-Kun ORCID: https://orcid.org/0000-0002-2094-5680, Liang, Yuan, Martin, Ralph R. and Hu, Shi-Min ORCID: https://orcid.org/0000-0001-7507-6542 2014. Biggerpicture: data-driven image extrapolation using graph matching. ACM Transactions on Graphics 33 (6) , 173. 10.1145/2661229.2661278

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Abstract

Filling a small hole in an image with plausible content is well studied. Extrapolating an image to give a distinctly larger one is much more challenging---a significant amount of additional content is needed which matches the original image, especially near its boundaries. We propose a data-driven approach to this problem. Given a source image, and the amount and direction(s) in which it is to be extrapolated, our system determines visually consistent content for the extrapolated regions using library images. As well as considering low-level matching, we achieve consistency at a higher level by using graph proxies for regions of source and library images. Treating images as graphs allows us to find candidates for image extrapolation in a feasible time. Consistency of subgraphs in source and library images is used to find good candidates for the additional content; these are then further filtered. Region boundary curves are aligned to ensure consistency where image parts are joined using a photomontage method. We demonstrate the power of our method in image editing applications.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Additional Information:	Pdf uploaded in accordance with the publisher’s policy at http://www.sherpa.ac.uk/romeo/issn/0730-0301/ (accessed 02/12/2014)
Publisher:	Association for Computing Machinery (ACM)
ISSN:	0730-0301
Date of First Compliant Deposit:	30 March 2016
Last Modified:	26 Nov 2024 11:00
URI:	https://orca.cardiff.ac.uk/id/eprint/67868

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