Radial View Based Culling for Continuous Self-Collision
Detection of Skeletal Models
Sai-Keung
Wong, Wen-Chieh
Lin, Chun-Hung Hung, Yi-Jheng
Huang, Shing-Yeu
Lii
National
Chiao Tung University, Taiwan, ROC
Figure 1: The major procedures of our method:
(a) Input of a deforming mesh with a skeleton; (b) Clustering triangles based
on the skeleton; (c) A radial view test from an observer primitive (an enlarged
view of the dashed region in (b)); (d) Culling results. Potentially colliding
triangles are colored as red; (e) Our method works
better for observer points lying inside the mesh, but it can tolerate some
observer points lying outside the mesh. Negatively oriented triangles are
colored as blue. [Please click to
enlarge the images]
Abstract
We present a novel radial-view-based
culling method for continuous self-collision detection (CSCD) of skeletal
models. Our method targets closed triangular meshes used to represent the
surface of a model. It can be easily integrated with bounding volume hierarchies
(BVHs) and used as the first stage for culling non-colliding triangle pairs. A
mesh is decomposed into clusters with respect to a set of observer primitives
(i.e., observer points and line segments) on the skeleton of the mesh so that
each cluster is associated with an observer primitive. One BVH is then built
for each cluster. At the runtime stage, a radial view test is performed from
the observer primitive of each cluster to check its collision state. Every pair
of clusters is also checked for collisions. We evaluated our method on various
models and compared its performance with prior methods. Experimental results
show that our method reduces the number of the bounding volume overlapping
tests and the number of potentially colliding triangle pairs, thereby improving
the overall process of CSCD.
Publication(s)
Cite:
@article{ref:WongLin:SIGGRAPH2013,
author = {Sai-Keung
Wong and Wen-Chieh
Lin and Chun-Hung Hung and Yi-Jheng Huang
and Shing-Yeu Lii},
title
= {Radial view based culling for continuous self-collision detection of
skeletal models},
journal = {ACM Transactions on Graphics
(ACM SIGGRAPH)},
volume = {32},
number = {4},
page
= {114},
year = {2013}
}
Movies: RVBC Method [ 51
MB] , Robustness Tests [ 43 MB]
Data (Rope, Urchin and Box) and Binary (Windows Only).
Source Code:
Methods based on Heaviside and
Bernstein (source code) for computing the sign of cubic polynomials.
Last update: 21st August, 2013