Kinship-Guided Age Progression
Kinship-Guided Age Progression
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DOI：
10.1016/j.patcog.2015.12.015
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发表时间：
2016-11
期刊：
影响因子：
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通讯作者：
Xiangbo Shu;Jinhui Tang;Hanjiang Lai;Zhiheng Niu;Shuicheng Yan
中科院分区：
文献类型：
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作者：
Xiangbo Shu;Jinhui Tang;Hanjiang Lai;Zhiheng Niu;Shuicheng Yan
年龄进展被定义为在美学上重新呈现老化的面部，并且在输入面部的任何未来年龄具有身份保留和高可信度。年龄增长面临两个主要挑战：（1）特定个体的年龄增长是随机的和不确定的，尽管对于相对较大的人群来说，这个过程中存在一些普遍的变化和不确定性;（2）年轻人可能没有明显的身份信息。在这项工作中，我们提出了一个高效和有效的亲属指导的年龄增长（KinGAP）的个人，它可以自动生成个性化的老化图像，利用亲属关系，或更具体地说，与指导的高级亲属脸。该方法主要由三个老化模块组成，分别用于保存个体老化特征、捕捉人类老化趋势和指导老化方向。大量的实验结果和用户研究分析我们构建的年龄亲属人脸数据集验证了我们的方法的优越性。
Age progression is defined as aesthetically re-rendering an aging face with identity preservation and high credibility at any future age for an input face. There are two main challenges in age progression: (1) age progression of a specific individual is stochastic and non-deterministic, though there exist some general changes and resemblances in this process for a relatively large population; (2) there may not be apparent identity information for people at the tender age. In this work, we present an efficient and effective Kinship-Guided Age Progression (KinGAP) approach for an individual, which can automatically generate personalized aging images by leveraging kinship, or more specifically, with guidance of the senior kinship face. The proposed approach mainly consists of three aging modules, which are designed to preserve individual aging characteristics, capture human aging tendency, and guide aging direction, respectively. Extensive experimental results and user study analysis on our constructed age-kinship face dataset validate the superiority of our approach.