Collision detection for articulated deformable characters

Abstract

In this paper, we present an efficient method for detecting collisions and self-collisions on articulated models deformed by Position Based Skinning. Position Based Skinning is a real-time skinning method, which produces believable skin deformations, and avoids artifacts such as the well-known "candy-wrapper" effect and joint-bulging. The proposed method employs spatial hashing with a uniform grid to detect collisions and self collisions. All the mesh primitives are mapped to a hash table, where only primitives mapped to the same hash index indicate a possible collision and need to be tested for intersections. Being based on spatial hashing, our method requires neither expensive set-up nor complex data structures and is hence suitable for articulated characters with deformable soft tissues. We exploit the skeletal nature of the deformation to only update the hash table when required. The resulting algorithm is simple to implement and fast enough for real-time applications. We demonstrate the efficiency of our method on various animation examples. A quantitative experiment is also presented to evaluate our method.