中文摘要：

为了使自动合成的手语虚拟人头部运动更具真实感, 提出一种邻域保持典型相关分析方法实现头部运动特征的预测. 首先从真实手语表演数据中提取同步手势和头部运动特征; 然后在利用非线性典型相关分析最大化两者运动特征相关性的同时引入邻域保持约束, 以获取更加平滑的头部运动特征. 实验结果表明, 该方法预测获得的头部运动特征能够合成出更逼真、自然的手语虚拟人头部动画.

英文摘要：

To improve the naturalness of head animation of virtual signers, this paper proposes neighborhood preserving canonical correlation analysis to realize head motion prediction. Firstly, synchronous hand and head motion features are extracted from a real signer performance. Secondly, the nonlinear canonical corre-lation analysis is applied to build a mapping from hand to head motion features. Meanwhile, neighborhood preserving constraint is employed to capture action transitions of successive motion frames, and better model the smoothness between them. Experimental results show that the proposed method can achieve more realis-tic and natural head animation of the signing avatar.