Abstract
Continuous collision detection improves the computation of the contact information for interacting objects in dynamic virtual environments. The computation cost is relatively high in the phase of the elementary test processing. In virtual environments, such as crowds in large urban models, there is a large portion of feature pairs that do not collide but the computation is relatively of high cost. In this paper, we propose a robust approach for solving the scalability of the collision detection problem by applying four distinct phases. First, k-DOPs are used for culling non-proximal triangles. Second, the feature assignment scheme is used for minimizing the number of potentially colliding feature pairs. Third, an intrinsic filter is employed for filtering non-coplanar feature pairs. Forth, we use a direct method for computing the contact time that is more efficient than the numerical Interval Newton method. We have implemented our system and have compared its performance with the most recently developed approaches. Six benchmarks were evaluated and the complexity of the models was up to 1.5M triangles. The experimental results show that our method improves the performance for the elementary tests.
Original language | English |
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Title of host publication | Proceedings - VRST 2010 |
Subtitle of host publication | ACM Symposium on Virtual Reality Software and Technology |
Pages | 55-62 |
Number of pages | 8 |
DOIs | |
Publication status | Published - 1 Dec 2010 |
Event | 17th ACM Symposium on Virtual Reality Software and Technology, VRST 2010 - Hong Kong, Hong Kong Duration: 22 Nov 2010 → 24 Nov 2010 |
Conference
Conference | 17th ACM Symposium on Virtual Reality Software and Technology, VRST 2010 |
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Country/Territory | Hong Kong |
City | Hong Kong |
Period | 22/11/10 → 24/11/10 |
Keywords
- Continuous collision detection
- Deformable objects
- Virtual reality
ASJC Scopus subject areas
- Software