A collision detection framework for deformable objects

Rynson W.H. Lau; Mo Luk; Oliver Chan; Frederick W.B. Li

doi:10.1145/585740.585760

A collision detection framework for deformable objects

Rynson W.H. Lau, Mo Luk, Oliver Chan, Frederick W.B. Li

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

14 Citations (Scopus)

Abstract

Many collision detection methods have been proposed. Most of them can only be applied to rigid objects. In general, these methods precompute some geometric information of each object, such as bounding boxes, to be used for run-time collision detection. However, if the object deforms, the precomputed information may not be valid anymore and hence needs to be recomputed in every frame while the object is deforming. In this paper, we presents an efficient collision detection framework for deformable objects, which considers both inter-collisions and self-collisions of deformable objects modeled by NURBS surfaces. Towards the end of the paper, we show some experimental results to demonstrate the performance of the new method. © 2002 ACM.

Original language	English
Title of host publication	VRST '02: Proceedings of the ACM symposium on Virtual reality software and technology
Publisher	Association for Computing Machinery
Pages	113-120
ISBN (Print)	978-1-58113-530-5
DOIs	https://doi.org/10.1145/585740.585760
Publication status	Published - Nov 2002
Event	2002 ACM Symposium on Virtual Reality Software and Technology (VRST02) - Hong Kong, China Duration: 11 Nov 2002 → 13 Nov 2002

Conference

Conference	2002 ACM Symposium on Virtual Reality Software and Technology (VRST02)
Place	China
City	Hong Kong
Period	11/11/02 → 13/11/02

Research Keywords

Collision detection
Deformable objects
Interference detection
NURBS surfaces

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10.1145/585740.585760

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@inproceedings{8cf24cb84df64e2281524286363734b6,

title = "A collision detection framework for deformable objects",

abstract = "Many collision detection methods have been proposed. Most of them can only be applied to rigid objects. In general, these methods precompute some geometric information of each object, such as bounding boxes, to be used for run-time collision detection. However, if the object deforms, the precomputed information may not be valid anymore and hence needs to be recomputed in every frame while the object is deforming. In this paper, we presents an efficient collision detection framework for deformable objects, which considers both inter-collisions and self-collisions of deformable objects modeled by NURBS surfaces. Towards the end of the paper, we show some experimental results to demonstrate the performance of the new method. {\textcopyright} 2002 ACM.",

keywords = "Collision detection, Deformable objects, Interference detection, NURBS surfaces",

author = "Lau, {Rynson W.H.} and Mo Luk and Oliver Chan and Li, {Frederick W.B.}",

year = "2002",

month = nov,

doi = "10.1145/585740.585760",

language = "English",

isbn = "978-1-58113-530-5",

pages = "113--120",

booktitle = "VRST '02: Proceedings of the ACM symposium on Virtual reality software and technology",

publisher = "Association for Computing Machinery",

address = "United States",

note = "2002 ACM Symposium on Virtual Reality Software and Technology (VRST02) ; Conference date: 11-11-2002 Through 13-11-2002",

}

Lau, RWH, Luk, M, Chan, O & Li, FWB 2002, A collision detection framework for deformable objects. in VRST '02: Proceedings of the ACM symposium on Virtual reality software and technology. Association for Computing Machinery, pp. 113-120, 2002 ACM Symposium on Virtual Reality Software and Technology (VRST02), Hong Kong, China, 11/11/02. https://doi.org/10.1145/585740.585760

A collision detection framework for deformable objects. / Lau, Rynson W.H.; Luk, Mo; Chan, Oliver et al.
VRST '02: Proceedings of the ACM symposium on Virtual reality software and technology. Association for Computing Machinery, 2002. p. 113-120.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - A collision detection framework for deformable objects

AU - Lau, Rynson W.H.

AU - Luk, Mo

AU - Chan, Oliver

AU - Li, Frederick W.B.

PY - 2002/11

Y1 - 2002/11

N2 - Many collision detection methods have been proposed. Most of them can only be applied to rigid objects. In general, these methods precompute some geometric information of each object, such as bounding boxes, to be used for run-time collision detection. However, if the object deforms, the precomputed information may not be valid anymore and hence needs to be recomputed in every frame while the object is deforming. In this paper, we presents an efficient collision detection framework for deformable objects, which considers both inter-collisions and self-collisions of deformable objects modeled by NURBS surfaces. Towards the end of the paper, we show some experimental results to demonstrate the performance of the new method. © 2002 ACM.

AB - Many collision detection methods have been proposed. Most of them can only be applied to rigid objects. In general, these methods precompute some geometric information of each object, such as bounding boxes, to be used for run-time collision detection. However, if the object deforms, the precomputed information may not be valid anymore and hence needs to be recomputed in every frame while the object is deforming. In this paper, we presents an efficient collision detection framework for deformable objects, which considers both inter-collisions and self-collisions of deformable objects modeled by NURBS surfaces. Towards the end of the paper, we show some experimental results to demonstrate the performance of the new method. © 2002 ACM.

KW - Collision detection

KW - Deformable objects

KW - Interference detection

KW - NURBS surfaces

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U2 - 10.1145/585740.585760

DO - 10.1145/585740.585760

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 978-1-58113-530-5

SP - 113

EP - 120

BT - VRST '02: Proceedings of the ACM symposium on Virtual reality software and technology

PB - Association for Computing Machinery

T2 - 2002 ACM Symposium on Virtual Reality Software and Technology (VRST02)

Y2 - 11 November 2002 through 13 November 2002

ER -

A collision detection framework for deformable objects

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