We propose a method to fit arbitrarily accurate blendshape rig models by solving the inverse rig problem in realistic human face animation. The method considers blendshape models with different levels of added corrections and solves the regularized least-squares problem using coordinate descent, i.e., iteratively estimating blendshape weights. Besides making the optimization easier to solve, this approach ensures that mutually exclusive controllers will not be activated simultaneously and improves the goodness of fit after each iteration. We show experimentally that the proposed method yields solutions with mesh error comparable to or lower than the state-of-the-art approaches while significantly reducing the cardinality of the weight vector (over 20 percent), hence giving a high-fidelity reconstruction of the reference expression that is easier to manipulate in the post-production manually. Python scripts for the algorithm will be publicly available upon acceptance of the paper.

翻译：我们提出了一种通过求解真实人脸动画中的逆向蒙皮问题来拟合任意精确混合变形模型的方法。该方法考虑了不同修正级别的混合变形模型，并使用坐标下降法（即迭代估计混合变形权重）求解正则化最小二乘问题。这种方法不仅简化了优化求解过程，还能确保互斥控制器不会同时激活，并在每次迭代后提高拟合优度。实验表明，所提出的方法在网格误差上达到与当前最先进方法相当或更低的水平，同时显著降低了权重向量的基数（超过20%），从而实现对参考表达式的高保真重建，便于后期制作中的人工操控。论文被接收后，该算法的Python脚本将公开发布。