GPU-based radial view-based culling for continuous self-collision detection of deformable surfaces

Wong, Sai‐Keung; Cheng, Yu-Chun

doi:10.1007/s00371-014-1056-9

Cited by 4 publications

(7 citation statements)

References 32 publications

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“…As we discussed in the last section, the calculating cost is a problem that needs to be solved both for a meshless method and mesh‐based method. Using the powerful parallel computing ability of GPU is an effective way to solve this problem . In addition, it is also an effective method to reduce the cost of calculation by using the model reduction method to reduce the dimension of the model rationally on the basis of ensuring effective precision .…”

Section: Discussion and Future Potentialmentioning

confidence: 99%

“…Using the powerful parallel computing ability of GPU is an effective way to solve this problem. 36,47,[92][93][94][95] In addition, it is also an effective method to reduce the cost of calculation by using the model reduction method to reduce the dimension of the model rationally on the basis of ensuring effective precision. [96][97][98][99] In addition, some meshing methods, mesh optimization methods, 12,13,25,[100][101][102] and some meshless methods 103-107 that are not used or applied in fields other than surgical simulation are also of concern.…”

Section: Laplacian Coordinates Constraints and Local Volume Preservationmentioning

confidence: 99%

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A review of virtual cutting methods and technology in deformable objects

Wang

2018

Robotics Computer Surgery

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Section: Discussion and Future Potentialmentioning

confidence: 99%

Section: Laplacian Coordinates Constraints and Local Volume Preservationmentioning

confidence: 99%

A review of virtual cutting methods and technology in deformable objects

Wang

2018

Robotics Computer Surgery

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“…Therefore various acceleration schemes have been proposed to efficiently cull unnecessary tests. Examples are spatial hashing [Teschner et al 2003], chromatic decomposition of orthogonal triangle sets [Govindaraju et al 2005], connectivity based culling [Tang et al 2008], separating axis tests [Tang et al 2011], radial view based culling [Wong et al 2013], [Wong and Cheng 2014], , simulation space based culling [Barbič and James 2010], [Zheng and James 2012], the use of representative primitives [Curtis et al 2008], rasterization of objects using GPUs [Govindaraju et al 2003], [Heidelberger et al 2004], [Faure et al 2008], [Wang et al 2012] and various hierarchical methods [Mezger et al 2003], [Schvartzman et al 2010], [Schvartzman et al 2009]. …”

Section: Collision Detection For Deformable Objectsmentioning

confidence: 99%

Air meshes for robust collision handling

Müller¹,

Chentanez²,

Kim³

et al. 2015

ACM Trans. Graph.

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Figure 1: A dancer with a multi-layered skirt. Our method robustly simulates the complex interaction of the layers and is able to smoothly recover from any entangled state. AbstractWe propose a new method for both collision detection and collision response geared towards handling complex deformable objects in close contact. Our method does not miss collision events between time steps and solves the challenging problem of untangling automatically and robustly. It is conceptually simple and straight forward to parallelize due to the regularity of the algorithm.The main idea is to tessellate the air between objects once before the simulation and by considering one unilateral constraint per element that prevents its inversion during the simulation. If large relative rotations and translations are present in the simulation, an additional dynamic mesh optimization step is needed to prevent mesh locking. This step is fast in 2D and allows the simulation of arbitrary scenes. Because mesh optimization is expensive in 3D, however, the method is best suited for the subclass of 3D scenarios in which relative motions are limited. This subclass contains two important problems, namely the simulation of multi-layered clothing and tissue on animated characters.

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“…However, the computation cost is more expensive. There exist several parallel methods to speed up the calculation process . After analyzing and comparing these methods, we found that these methods are designed for general application and are not efficient enough to meet our task requirement.…”

Section: Introductionmentioning

confidence: 99%

“…There exist several parallel methods to speed up the calculation process. [12][13][14][15][16][17] After analyzing and comparing these methods, we found that these methods are designed for general application and are not efficient enough to meet our task requirement. The performances of these parallel methods are affected by unbalanced computation load and excess computing.…”

Section: Introductionmentioning

confidence: 99%

A multi‐GPU finite element computation and hybrid collision handling process framework for brain deformation simulation

Tian

Shen

2018

Computer Animation & Virtual

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This paper offers a fast multi‐graphics processing unit (GPU) parallel simulation framework to the problem of real‐time and nonlinear finite element computation of brain deformation. A load balancing strategy is proposed to ensure the efficient distribution of nonlinear finite element computation on multi‐GPU. A data storage structure is designed to minimize the amount of data transfer and make full use of the overlay technique of GPU to reduce the transferring latency between multi‐GPUs. We further present a fast central processing unit (CPU)–GPU parallel continuous collision detection and response method, which not only can deal with the collision between the brain and skull but also can handle the self‐collision of the brain. Our method can make full use of CPU and GPU to implement a parallel computation about deformation and collision detection. Our experimental results show that our method is able to handle a brain geometric model with high detail gyrus composed of more than 40,000 tetrahedron elements. This can facilitate the fidelity of the current virtual brain surgery simulator. We evaluate our approach qualitatively and quantitatively and compare it with related works.

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GPU-based radial view-based culling for continuous self-collision detection of deformable surfaces

Cited by 4 publications

References 32 publications

A review of virtual cutting methods and technology in deformable objects

A review of virtual cutting methods and technology in deformable objects

Air meshes for robust collision handling

A multi‐GPU finite element computation and hybrid collision handling process framework for brain deformation simulation

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