BiggerPicture

Author:

Wang Miao1,Lai Yu-Kun2,Liang Yuan1,Martin Ralph R.2,Hu Shi-Min1

Affiliation:

1. Tsinghua University, Beijing

2. Cardiff University

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.

Funder

Research Grants Council, University Grants Committee, Hong Kong

National Natural Science Foundation of China

Tsinghua University

Ministry of Science and Technology of the People's Republic of China

Engineering and Physical Sciences Research Council

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design

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2. Context-Aware Seam Restoration for Image Extension;2023 IEEE International Conference on Visual Communications and Image Processing (VCIP);2023-12-04

3. Survey on learning-based scene extrapolation in robotics;International Journal of Intelligent Robotics and Applications;2023-11-22

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