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Submitted by Stephane Redon, posted on August 08, 2003




Image Description, by Stephane Redon



This image is from an interactive demo of our new discrete collision detection approach for large-scale environments, in which the Stanford dragon (250,000 triangles) breaks when the Stanford bunny (35,000 triangles) falls on it. The demo runs on a pentium 2.4 GHz with a NVIDIA Geforce FX 5800).

This discrete collision detection method is a graphics-hardware based approach, which takes advantage of the new occlusion queries of the recent graphics cards to efficiently cull away most of the non-colliding objects or sub-objects. As opposed to most GPU-based methods for collision detection, this method doesn't require frame-buffer readbacks. This allows to achieve a high frame-rate for complex bodies. Moreover, since no data structure is required, the method handles naturally deformable bodies, breaking bodies, and changing topologies.

As this demo is essentially designed to test the CD method, the physics part of the demo is a very simple implementation of impulse-based physics . The dragon is organized in triangle strips and a heuristic is used to remove some strips and propagate the fracture when the bunny collides the dragon. Since no penetration depth is computed, the velocity of the contact point on the bunny is used as the contact normal. This gives satisfying results in this case. Note that the demo shows that the method handles N-body collision detection as well, as the parts falling on the floor may push parts which are already resting (cf video here )

The lighting in this image is a very simplified (hacked / not exact) version of CPU-based image-based lighting, tested for fun. However, the immediate-mode implementation was rather slow (15 fps, including collision detection and physics) and has been replaced by simple lighting in the video. We plan to implement the lighting in hardware later (thanks to Paul Debevec for the permission to use his Light Probe images).

More information can be found at my page at UNC (dragon video.) or at the paper's page by Naga Govindaraju (the paper's first author).

Cheers,

Stephane Redon
redon [at] cs [dot] unc [dot] edu


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