利用主动外观模型合成动态人脸表情
Dynamic Facial Expression Synthesis by Active Appearance Model
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摘要: 人脸表情发生变化时,面部纹理也相应地改变;为了方便有效地模拟这一动态的表情变化过程,提出一种基于主动外观模型的人脸表情合成方法.首先离线学习人脸表情与人脸形状和外观参数之间的关系,利用该学习结果实现对输入人脸图像的表情合成;针对合成图像中眼睛和牙齿模糊的缺点,利用合成的眼睛图像和牙齿模板来替代模糊纹理.实验结果表明,该方法能合成不同表情强度和类型的表情图像;合成的眼睛图像不仅增强了表情的真实感,同时也便于实现眼睛的动画.Abstract: As the facial expression changes,the facial texture changes accordingly. To simulate this dynamic process of expression changes,this paper proposes a method of facial expression synthesis based on active appearance model. First,the relationship between facial expression and model parameters is obtained with an offline learning strategy. Then,the given person's facial expressions can be synthesized based on the learning results. In order to solve the problem of blurry eyes and teeth,a synthetic eye image and a teeth template are used to replace these blurry parts of textures. Experimental results show that facial expressions with different intensity and categories can be synthesized;the synthetic eye image enhances the realism of the expressions and makes it easy to implement eye animation.
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