Minimal Hierarchical Collision Detection
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We present a novel bounding volume hierarchy that allows for extremely
small data structure sizes while still performing collision detection as
fast as other classical hierarchical algorithms in most cases.
The hierarchical data structure is a variation of axis-aligned bounding box
trees. In addition to being very memory efficient, it can be constructed
efficiently and very fast.
We also propose a criterion to be used during the construction of the BV
hierarchies is more formally established than previous heuristics.
The idea of the argument is general and can be applied to other bounding
volume hierarchies as well.
Furthermore, we describe a general optimization technique that can be applied to
most hierarchical collision detection algorithms.
Finally, we describe several box overlap tests that exploit the special
features of our new BV hierarchy.
These are compared experimentally among
each other and with the DOP tree using a benchmark suite
of CAD data.
Interference detection, virtual prototyping,
hierarchical partitioning, hierarchical data structures,
physically-based modeling, R-trees.
, author = "Gabriel Zachmann"
, title = "Minimal Hierarchical Collision Detection"
, booktitle = "Proc. ACM Symposium on Virtual Reality Software and Technology
, year = 2002
, address = "Hong Kong, China"
, month = nov # "11--13"
, pages = "121--128"
, url = "http://www.gabrielzachmann.org/"
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