Robust image retargeting via axis-aligned deformation

Daniele Panozzo, Ofir Weber, Olga Sorkine

Research output: Contribution to journalConference articlepeer-review

94 Scopus citations

Abstract

We propose the space of axis-aligned deformations as the meaningful space for content-aware image retargeting. Such deformations exclude local rotations, avoiding harmful visual distortions, and they are parameterized in 1D. We show that standard warping energies for image retargeting can be minimized in the space of axis-aligned deformations while guaranteeing that bijectivity constraints are satisfied, leading to high-quality, smooth and robust retargeting results. Thanks to the 1D parameterization, our method only requires solving a small quadratic program, which can be done within a few milliseconds on the CPU with no precomputation overhead. We demonstrate how the image size and the saliency map can be changed in real time with our approach, and present results on various input images, including the RETARGETME benchmark. We compare our results with six other algorithms in a user study to demonstrate that the space of axis-aligned deformations is suitable for the problem at hand.

Original languageEnglish
Pages (from-to)229-236
Number of pages8
JournalComputer Graphics Forum
Volume31
Issue number2
DOIs
StatePublished - 2012
Externally publishedYes
Event33rd Annual Conference on European Association for Computer Graphics, EUROGRAPHICS 2012 - Cagliari, Sardinia, Italy
Duration: 13 May 201218 May 2012

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