Correlation-Preserving Photo Collage

Correlation-Preserving Photo Collage
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保持相关的照片拼贴

DOI:
10.1109/tvcg.2017.2703853
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发表时间:
2018
影响因子:
5.2
通讯作者:
Wenping Wang
Wenping Wang
中科院分区:
计算机科学1区
文献类型:
--
作者:
Lingjie Liu;Guangmei Jing;Zhang Hongjie;Yanwen Guo;Zhonggui Chen;Wenping Wang

文献摘要

被引文献

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提出了一种新的方法来生产照片拼贴,保持内容的相关性的照片。我们使用深度学习技术来找到给定照片之间的相关性,以便于将它们嵌入画布上,并开发一种有效的组合优化技术,使相关的照片彼此保持接近。为了有效地利用画布空间,我们的方法首先提取照片的显著区域,并仅包装这些显著区域。我们允许显着的区域具有任意的形状,因此产生信息丰富,但更紧凑的拼贴比其他类似的拼贴方法的基础上显着的区域。我们提出了广泛的实验结果,用户研究结果,并对国家的最先进的方法进行比较,以显示我们的方法的优越性。
A new method is presented for producing photo collages that preserve content correlation of photos. We use deep learning techniques to find correlation among given photos to facilitate their embedding on the canvas, and develop an efficient combinatorial optimization technique to make correlated photos stay close to each other. To make efficient use of canvas space, our method first extracts salient regions of photos and packs only these salient regions. We allow the salient regions to have arbitrary shapes, therefore yielding informative, yet more compact collages than by other similar collage methods based on salient regions. We present extensive experimental results, user study results, and comparisons against the state-of-the-art methods to show the superiority of our method.