filename     : p_colDetHashing.pdf
entry        : 
pages        : 47-54
year         : 2003
title        : Optimized Spatial Hashing for Collision Detection of Deformable Objects
author       : Matthias Teschner, Bruno Heidelberger, Matthias Mueller, Danat Pomeranets, Markus Gross
booktitle    : Proceedings of Vision, Modeling, and Visualization 2003
editor       : T. Ertl, B. Girod, G. Greiner, H. Niemann, H.-P. Seidel, E. Steinbach, R. Westermann
publisher    : Akademische Verlagsgesellschaft Aka GmbH, Berlin, ISBN 3-89838-048-3
language     : English
month        : Nov
keywords     : collision detection, spatial hashing, dynamic environments, deformable modeling
abstract     : 
We propose a new approach to collision and self--collision detection
of dynamically deforming objects that consist of tetrahedrons.
Tetrahedral meshes are commonly used to represent volumetric
deformable models and the presented algorithm is integrated in a
physically--based environment, which can be used in game engines and
surgical simulators. The proposed algorithm employs a hash function
for compressing a potentially infinite regular spatial grid.  Although
the hash function does not always provide a unique mapping of grid
cells, it can be generated very efficiently and does not require
complex data structures, such as octrees or BSPs. We have investigated
and optimized the parameters of the collision detection algorithm,
such as hash function, hash table size and spatial cell size. The
algorithm can detect collisions and self--collisions in environments
of up to 20k tetrahedrons in real--time.  Although the algorithm works
with tetrahedral meshes, it can be easily adapted to other object
primitives, such as triangles.