A Practical Collision Filtering for Complex Environments using Imagebased Techniques

1
A Practical Collision Filtering for Complex
Environments using Image-based Techniques
Student Yong-Cheng Chen?????
Advisor Jung-Hong Chuang???????
Motivation
We present an algorithm for efficient and exact
collision detection between complex models in
large environments using graphics hardware. The
purpose of our algorithm is to improve
image-based collision culling and partition the
potentially colliding set (PCS) into subsets. Our
algorithm eliminates objects which are fully
visible in PCS using occlusion query. It is based
on CULLIDE and decides an order of rendering to
supply a more efficient culling performance.

• Partition of potentially colliding set
• Low bandwidth requirement
• Handle rigid or deformable objects
• Exact collision detection

Collision Culling
We can conspicuously reduce the extent of culling
to rely on the depth complexity of the scene
along the view direction using a far-to-near
rendering order.
PCS Partition
Implements in C and OpenGL on VC 7.0 with 3.0
GHz Intel Pentium 4 CPU, 512MB memory, and
Geforce 6800 GPU.
Result
Our approach determines whether sepa-rating
surfaces exist between the subsets of the PCS in
linear time.
(A) Simulating 50 torii at different frame
buffer resolutions
(A) Motion with gravity in simple environment
(B) Simulating 50200 torii with a frame buffer
resolution of 800x 800
(B) Motion without gravity in complex environment