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Pose-based composition improvement for portrait photographs

机译:基于姿势的肖像照片构图改进

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This paper studies the composition of portrait paintings and develops an algorithm to improve the composition of portrait photographs. The study of portrait paintings shows that placement of the face and the figure in portrait paintings is pose-related. Based on this observation, this paper develops an algorithm to improve the composition of a portrait photograph by learning the placement of the face and the figure from an example portrait painting. The example portrait painting is selected based on the similarity of its figure pose to that of the input photograph. This similarity measure is modeled as a graph matching problem. Finally, space cropping is performed using an optimization function. Experimental results and a user study demonstrate that the proposed pose-based improvement is preferred more than rule-based methods.
机译:本文研究了人像绘画的构成,并提出了一种改善人像照片构成的算法。对肖像画的研究表明,肖像画中面部和人物的位置与姿势有关。基于这种观察,本文开发了一种算法,可以通过从人像绘画实例中学习人脸和人物的位置来改善人像照片的构图。基于肖像画与输入照片的相似度来选择示例肖像画。这种相似性度量被建模为图匹配问题。最后,使用优化功能执行空间裁剪。实验结果和用户研究表明,所提出的基于姿势的改进比基于规则的方法更为可取。

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