3D Collision Detection Algorithm based on Composite Balanced Binary Bounding Box Tree

DOI

10.2991/emcm-16.2017.125How to use a DOI?

Keywords

Collision detection; Composite bounding box; Sphere bounding box; OBB bounding box; Shape classification

Abstract

The existing bounding box has the contradiction between compactness and complexity. On the one hand, the poor compactness of the bounding box often leads to the poor effect of removing the disjoint objects, which leads to the low efficiency of collision detection. On the another hand, the good compactness of the bounding box often leads to the high complexity of the collision detection algorithm, which leads to the high time complexity of collision detection. To solve this problem, this paper proposes a parallel collision detection algorithm based on the composite balanced binary bounding box tree. In the process of constructing the multilayered bounding box of the object in the algorithm, the selection of the bounding box is classified according to the near-sphere value of the different levels of the element set. The shape of an object is similar to that of a sphere, it will use the sphere bounding box, and the shape of an object is not similar to that of a sphere, it will use the OBB bounding box. This method solves the contradiction of the bounding box better. At the same time, in order to speed up the efficiency of collision detection, this paper uses the parallel algorithm. The experimental results show that the proposed algorithm is better than other classical algorithms, and is suitable for large scale application environment.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jinping Liu
AU  - Jianxun Chen
PY  - 2017/02
DA  - 2017/02
TI  - 3D Collision Detection Algorithm based on Composite Balanced Binary Bounding Box Tree
BT  - Proceedings of the 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcm-16.2017.125
DO  - 10.2991/emcm-16.2017.125
ID  - Liu2017/02
ER  -