Fast and reliable collision culling using graphics hardware.
We present a reliable culling algorithm that enables fast and accurate collision detection between triangulated models in a complex environment. Our algorithm performs fast visibility queries on the GPUs for eliminating a subset of primitives that are not in close proximity. In order to overcome the accuracy problems caused by the limited viewport resolution, we compute the Minkowski sum of each primitive with a sphere and perform reliable 2.5D overlap tests between the primitives. We are able to achieve more effective collision culling as compared to prior object-space culling algorithms. We integrate our culling algorithm with CULLIDE [1] and use it to perform reliable GPU-based collision queries at interactive rates on all types of models, including nonmanifold geometry, deformable models, and breaking objects.
Govindaraju
Naga K
NK
University of North Carolina at Chapel Hill, NC 27599, USA. naga@cs.unc.edu
Lin
Ming C
MC
Manocha
Dinesh
D
D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D003196:Computer Graphics / Q000295:instrumentation*; D003198:Computer Simulation; D003199:Computer Systems; D003626:Data Display; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000295:instrumentation* / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D008954:Models, Biological; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D014584:User-Computer Interface