A Hierarchical Hashing Scheme for Nearest Neighbor Search and Broad-Phase Collision Detection

摘要

Increasing computational power allows computer graphics researchers to model spectacular phenomena such as fluids and their interactions with de-formable objects and structures. Particle-based (or Lagrangian) fluid and solid simulations are commonly managed separately and mixed together for the collision-detection phase. We present a unified dynamic acceleration model to be used for particle neighborhood queries and broad-phase collision detection, based on a hierarchical hash table data structure. Our method is able to significantly reduce computations in large, empty areas, and thus gives better results than existing acceleration techniques, such as multilevel hashing schemes or KD-trees, in most situations.