基于主色和特征点的动画人物面部表情识别

Seok-Woo Jang, Gye-Young Kim, Hyun-Suk Na
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引用次数: 1

摘要

提出了一种利用主色和特征点识别动画人物面部表情的方法。该方法定义了适合动画角色的简化网格模型,并使用主色检测其面部和面部成分。它还提取每个面部成分的基于边缘的特征点。然后通过神经网络将特征点划分为相应的AU(动作单元),最后根据建议的AU规范识别人物面部表情。实验结果表明,该方法能够可靠地识别动画人物的面部表情。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recognition of Facial Expressions of Animation Characters Using Dominant Colors and Feature Points
This paper suggests a method to recognize facial expressions of animation characters by means of dominant colors and feature points. The proposed method defines a simplified mesh model adequate for the animation character and detects its face and facial components by using dominant colors. It also extracts edge-based feature points for each facial component. It then classifies the feature points into corresponding AUs(action units) through neural network, and finally recognizes character facial expressions with the suggested AU specification. Experimental results show that the suggested method can recognize facial expressions of animation characters reliably.
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