STMPL: Human Soft-Tissue Simulation
Anton Agafonov Lihi Zelnik-Manor
In various applications, such as virtual reality and gaming, simulating the
deformation of soft tissues in the human body during interactions with external
objects is essential. Traditionally, Finite Element Methods (FEM) have been
employed for this purpose, but they tend to be slow and resource-intensive. In
this paper, we propose a unified representation of human body shape and soft
tissue with a data-driven simulator of non-rigid deformations. This approach
enables rapid simulation of realistic interactions.
  Our method builds upon the SMPL model, which generates human body shapes
considering rigid transformations. We extend SMPL by incorporating a soft
tissue layer and an intuitive representation of external forces applied to the
body during object interactions. Specifically, we mapped the 3D body shape and
soft tissue and applied external forces to 2D UV maps. Leveraging a UNET
architecture designed for 2D data, our approach achieves high-accuracy
inference in real time. Our experiment shows that our method achieves plausible
deformation of the soft tissue layer, even for unseen scenarios.