Facial expression cloning optimization method based Laplace operator.

Abstract

In view of the reality of facial expression cloning and efficiency of expression reconstruction, a novel method based on motion capture data is proposed. After capturing the data of six fundamental expressions, it normalizes these data to make them in the same range. Then 41 points are chosen in critical areas of facial expression and it gets cloning expression using Laplace deformation algorithm with convex weight which can preserve the details of facial expression to avoid the low fidelity of uniform weights and unstable calculation of cotangent weights. Experimental results show that this method can generate realistic and natural expression animations and the efficiency of facial expression cloning is improved significantly.