A Multi-layer Model for Face Aging Simulation
A Multi-layer Model for Face Aging Simulation
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DOI：
10.1007/978-3-642-22639-7_18
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
Yixiong Liang;Ying Xu;Lingbo Liu;Shenghui Liao;Beiji Zou
中科院分区：
文献类型：
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作者：
Yixiong Liang;Ying Xu;Lingbo Liu;Shenghui Liao;Beiji Zou
人脸衰老模拟是一项非常复杂和具有挑战性的研究课题，由于其广泛的应用，引起了心理学、计算机图形学和计算机视觉等领域研究者的广泛关注。本文提出了一种从粗到细的多层人脸表示和老化仿真动画算法。在粗糙层中，我们建立了一个全局统计的外观模型来表示人脸，并根据在外观空间中学习到的年龄轨迹来对人脸进行老化。在中间层，我们学习了一组年龄相关的耦合字典，并通过对学习到的字典的稀疏表示来表示和老化人脸。在精细层，我们从每个年龄组的图像中抽取大量的面部部件和皮肤区域作为字典，以模拟面部部件和皱纹的老化效果。我们收集了10，050张不同年龄段的中国护照类型图像数据库，用于学习和老化模拟。通过仿真和实测数据处理验证了所提方法的有效性。
Face aging simulation is a very complex and challenging task and interests many researchers in the fields of psychology, computer graphics and computer vision due to its widely applications. In this paper, we propose a multi-layer coarse-to-fine face representation and aging simulation and animation algorithm. In the coarse layer, we build a global statistical appearance model for representation and faces are aged based on the learned age trajectory in the appearance space. In the mid layer, we learned a set of age specific coupled dictionaries and the faces are represented and aged via the sparse representation on the learned dictionary. At the fine layer, we sample a lot of patches of facial components and skin zones from images of each age group and use them as the dictionaries to simulate the aging effects of the facial components and wrinkles. We collect a database of 10,050 Chinese passport-type images with different ages for the learning and aging simulation. Experimental results demonstrate the effectiveness of the proposed method.