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Image Retargeting Using Mesh Parametrization

delete2009-08-01
delete182
PRE
AI
Y
Yanwen Guo *
F
Feng Liu
周
周志华 (Zhihua Zhou)
M
Michael Gleicher
DOI:10.1109/TMM.2009.2021781delete
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摘要

摘要

En 中文
Image retargeting aims to adapt images to displays of small sizes and different aspect ratios. Effective retargeting requires emphasizing the important content while retaining surrounding context with minimal visual distortion. In this paper, we present such an effective image retargeting method using saliency-based mesh parametrization. Our method first constructs a mesh image representation that is consistent with the underlying image structures. Such a mesh representation enables easy preservation of image structures during retargeting since it captures underlying image structures. Based on this mesh representation, we formulate the problem of retargeting an image to a desired size as a constrained image mesh parametrization problem that aims at finding a homomorphous target mesh with desired size. Specifically, to emphasize salient objects and minimize visual distortion, we associate image saliency into the image mesh and regard image structure as constraints for mesh parametrization. Through a stretch-based mesh parametrization process we obtain the homomorphous target mesh, which is then used to render the target image by texture mapping. The effectiveness of our algorithm is demonstrated by experiments.
Keyword:
Attention model
image retargeting
mesh parametrization
AI总结

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期刊

IEEE Transactions on Multimedia 封面图
IEEE Transactions on Multimedia
IF:
9.7
论文数:
4.7K
被引数:
2.4W

机构

University of Wisconsin System 封面图
University of Wisconsin System
学者数:
6.7W
论文数: 5.8W
被引数: 382
N
nanjing university
学者数:
7.8W
论文数: 5.6W
被引数: 87
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