The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Accurate and Fast Proximity Queries Between Polyhedra Using Convex Surface Decomposition
Abstract
The need to perform fast and accurate proximity queries arises frequently in physically-based modeling, simulation, animation, real-time interaction within a virtual environment, and game dynamics. The set of proximity queries include intersection detection, tolerance verification, exact and approximate minimum distance computation, and (disjoint) contact determination. Specialized data structures and algorithms have often been designed to perform each type of query separately. We present a unified approach to perform any of these queries seamlessly for general, rigid polyhedral objects with boundary representations which are orientable 2-manifolds. The proposed method involves a hierarchical data structure built upon a surface decomposition of the models. Furthermore, the incremental query algorithm takes advantage of coherence between successive frames. It has been applied to complex benchmarks and compares very favorably with earlier algorithms and systems.
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OBBTree: a hierarchical structure for rapid interference detection
Gottschalk, S., Lin, M. C., & Manocha, D. (1996) · Proceedings of the 23rd annual conference on Computer graphics and interactive techniques · doi:10.1145/237170.237244 · Cited by 2,081
Self-citationA fast procedure for computing the distance between complex objects in three-dimensional space
Gilbert, E. G., Johnson, D. W., & Keerthi, S. S. (1988) · IEEE Journal on Robotics and Automation · doi:10.1109/56.2083 · Cited by 1,513
Efficient collision detection using bounding volume hierarchies of k-DOPs
Klosowski, J. T., Held, M., Mitchell, J. S. B., Sowizral, H., & Zikan, K. (1998) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/2945.675649 · Cited by 873
Linear-Time Algorithms for Linear Programming in $R^3 $ and Related Problems
Megiddo, N. (1983) · SIAM Journal on Computing · doi:10.1137/0212052 · Cited by 837
Linear-time algorithms for linear programming in R3 and related problems
Megiddo, N. (1982) · doi:10.1109/sfcs.1982.74 · Cited by 483
V-Clip: fast and robust polyhedral collision detection
Mirtich, B. (1998) · ACM Transactions on Graphics · doi:10.1145/285857.285860 · Cited by 403
Efficient distance computation between non-convex objects
Quinlan, S. (2002) · Proceedings of the 1994 IEEE International Conference on Robotics and Automation · doi:10.1109/robot.1994.351059 · Cited by 391
Convex Partitions of Polyhedra: A Lower Bound and Worst-Case Optimal Algorithm
Chazelle, B. (1984) · SIAM Journal on Computing · doi:10.1137/0213031 · Cited by 238
Efficient collision detection for animation and robotics
Lin, M. C., & Canny, J. (1993) · Cited by 231
Self-citationInteractive collision detection
Hubbard, P. M. (1993) · Proceedings of 1993 IEEE Research Properties in Virtual Reality Symposium · doi:10.1109/vrais.1993.378267 · Cited by 197
Metadata
- Authors
- Ehmann, S. A., & Lin, M. C.
- Venue
- Computer Graphics Forum
- Publisher
- Wiley
- Published
- 2001-09
- Volume
- 20
- Issue
- 3
- Pages
- 500-511
- ISSN
- 0167-7055 (ISSN-L)
- 1467-8659
- OpenAlex
- W2113525359
- Cited by
- 264
- References
- 16
- FWCI
- 32.76
- Type
- journal article
- Language
- en
- Open access
- closed
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