motion retargeting for hand gesture

Chunbao Ge, Yiqiang Chen, Wen Gao, Baocai Yin

This paper presents a new technique for retargeting the sign language data captured from motion capture device to different characters with different sizes and proportions. Realistic and natural animations can be produced to express similar meanings to the original. The proposed method first defines many sensitive points on the human body and selects the key sensitive points through analyzing the importance of the sensitive points. Next a novel mapping method based on relative position is presented to adapt the original sensitive points to the target sensitive points. Finally we utilize an IK solver to realize the retargeting problem. Experimental results show that the proposed method dramatically improves the recognition rate about 30%.