关键词: 手语, 非手部手势, 头部动作, 核典型相关分析, 虚拟人

Abstract: Non-manual component plays an important role in sign language communication. Head movement synthesis and synchronization with gesture is one of those main topics. Based on realistic training data, this paper introduces detailed explorations to reveal the relationship between gesture and head motion, and uses kernel canonical correlation analysis (KCCA) to build the head movement prediction model. Animation synthesis results and evaluation experiments imply that the proposed method can better measure the cooperation between sign gesture and head motion and enhance the naturalness of synthesized behaviors of sign language virtual human.

Key words: sign language, non-manual component, head movement, kernel canonical correlation analysis (KCCA), virtual human