Title
CULLIDE: Interactive Collision Detection between Complex Models in Large Environments using Graphics Hardware
Abstract
We present a novel approach for fast collision detection between multiple deformable and breakable objects in a large environment using graphics hardware. Our algorithm takes into account low bandwidth to and from the graphics cards and computes a potentially colliding set (PCS) using visibility queries. It involves no precomputation and proceeds in multiple stages: PCS computation at an object level and PCS computation at sub-object level, followed by exact collision detection. We use a linear time two-pass rendering algorithm to compute each PCS efficiently. The overall approach makes no assumption about the input primitives or the object's motion and is directly applicable to all triangulated models. It has been implemented on a PC with NVIDIA GeForce FX 5800 Ultra graphics card and applied to different environments composed of a high number of moving objects with tens of thousands of triangles. It is able to compute all the overlapping primitives between different objects up to image-space resolution in a few milliseconds.
Year
DOI
Venue
2005
10.1145/844174.844178
Graphics Hardware
Keywords
Field
DocType
fast collision detection,ultra graphics card,complex model,interactive collision detection,exact collision detection,large environment,multiple deformable,breakable object,different environment,graphics hardware,pcs computation,different object,graphics card,simplification,languages,collision detection,linear time,level of detail,gpu computing,numerical simulation,multigrid,conjugate gradient,fluid simulation
Graphics,Collision detection,Graphics hardware,Computer graphics (images),Level of detail,Computer science,Real-time rendering,Texture memory,Software rendering,Rendering (computer graphics)
Conference
ISBN
Citations 
PageRank 
978-1-58113-739-2
109
5.68
References 
Authors
16
4
Search Limit
100109
Name
Order
Citations
PageRank
Naga K. Govindaraju13331234.15
Stephane Redon273044.93
Ming Lin37046525.99
Dinesh Manocha49551787.40