Abstract
Collision detection between deforming models is a difficult problem for collision detection systems to handle. This problem is even more difficult when deformations are unconstrained, objects are in close proximity to one another, and when the entity count is high. We propose a method to perform collision detection between multiple deforming objects with unconstrained deformations that will give good results in close proximities. Currently no systems exist that achieve good performance on both unconstrained triangle level deformations and deformations that preserve edge connectivity. We propose a new system built as a combination of Graphics Processing Unit (GPU) based culling and Axis Aligned Bounding Box (AABB) based culling. Techniques for performing hierarchy-less GPU-based culling are given. We then discuss how and when to switch between GPU-based culling and AABB based techniques.
Degree
MS
College and Department
Physical and Mathematical Sciences; Computer Science
Rights
http://lib.byu.edu/about/copyright/
BYU ScholarsArchive Citation
Tuft, David Owen, "System for Collision Detection Between Deformable Models Built on Axis Aligned Bounding Boxes and GPU Based Culling" (2007). Theses and Dissertations. 1120.
https://scholarsarchive.byu.edu/etd/1120
Date Submitted
2007-01-12
Document Type
Thesis
Handle
http://hdl.lib.byu.edu/1877/etd1689
Keywords
computer science, collision detection, gpu, graphics processing unit, axis aligned bounding box, deformable models, culling
Language
English