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Pose-based composition improvement for portrait photographs

机译:基于姿势照片的姿势构成改进

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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:本文研究了肖像绘画的组成,并开发了一种改进肖像照片的构成的算法。肖像绘画的研究表明,肖像绘画中的面部和图形的放置是姿势相关的。基于该观察,本文开发了一种算法来通过学习面部的放置以及从示例肖像画来改善肖像照片的组成。根据其图形姿势与输入照片的相似性来选择示例肖像绘画。该相似度测量被建模为匹配问题。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,基于姿势的改进是优选的,比基于规则的方法更优选。

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