Abstract A new technique to accelerate the positioning of human body models (HBMs) by means of a dimensionality reduction of a database of precomputed simulations is presented. First, a set of important subspace deformation modes which are used to approximate the model’s movements observed in the training simulations are computed. In the second step, a convex optimization problem is solved in order to obtain an optimal position of the human body model as described by the user. We apply the proposed method to a new reclined seating position of the Total Human Model for Safety (THUMS, v5).

中文翻译：

---

使用模型阶数减少定位人体模型以实现耐撞性

摘要 提出了一种通过预计算模拟数据库的降维来加速人体模型（HBM）定位的新技术。首先，计算一组重要的子空间变形模式，用于近似训练模拟中观察到的模型运动。第二步，求解凸优化问题，得到用户描述的人体模型的最优位置。我们将所提出的方法应用于安全总人体模型（THUMS，v5）的新斜倚座椅位置。