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Adjacent Triangle

The Experts below are selected from a list of 30 Experts worldwide ranked by ideXlab platform

Dinesh Manocha – 1st expert on this subject based on the ideXlab platform

  • ICCD: Interactive continuous collision detection between deformable models using connectivity-based culling
    IEEE Transactions on Visualization and Computer Graphics, 2009
    Co-Authors: Min Tang, Sean Curtis, Sung-eui Yoon, Dinesh Manocha

    Abstract:

    We present an interactive algorithm for continuous collision detection between deformable models. We introduce multiple techniques to improve the culling efficiency and the overall performance of continuous collision detection. First, we present a novel formulation for continuous normal cones and use these normal cones to efficiently cull large regions of the mesh as part of self-collision tests. Second, we introduce the concept of procedural representative Triangles to remove all redundant elementary tests between nonAdjacent Triangles. Finally, we exploit the mesh connectivity and introduce the concept of orphan sets to eliminate redundant elementary tests between Adjacent Triangle primitives. In practice, we can reduce the number of elementary tests by two orders of magnitude. These culling techniques have been combined with bounding volume hierarchies and can result in one order of magnitude performance improvement as compared to prior collision detection algorithms for deformable models. We highlight the performance of our algorithm on several benchmarks, including cloth simulations, N-body simulations, and breaking objects. © 2006 IEEE.

T. Matsuoka – 2nd expert on this subject based on the ideXlab platform

  • Memory efficient Adjacent Triangle connectivity of a vertex using Triangle strips
    Proceedings Computer Graphics International 2004., 2004
    Co-Authors: H. Annaka, T. Matsuoka

    Abstract:

    We often need to refer to Adjacent elements (e.g., vertices, edges and Triangles) in Triangle meshes for rendering, mesh simplification and other processes. It is, however, sometimes impossible to prepare the enormous memory needed to represent element connectivity in gigantic Triangle meshes. This paper proposes a new scheme for referring to Adjacent Triangles around a vertex in nonmanifold Triangle meshes. First, we introduce the constraints to allow random access to a Triangle in a sequence of Triangle strips. Then, for each vertex, we construct a list of references to its Adjacent strips as a representation of Triangle connectivity. Experimental results show that, compared to conventional methods, our scheme can reduce the total size of a Triangle mesh and Adjacent Triangle connectivity to about 50%

  • Computer Graphics International – Memory efficient Adjacent Triangle connectivity of a vertex using Triangle strips
    , 2004
    Co-Authors: H. Annaka, T. Matsuoka

    Abstract:

    We often need to refer to Adjacent elements (e.g., vertices, edges and Triangles) in Triangle meshes for rendering, mesh simplification and other processes. It is, however, sometimes impossible to prepare the enormous memory needed to represent element connectivity in gigantic Triangle meshes. This paper proposes a new scheme for referring to Adjacent Triangles around a vertex in nonmanifold Triangle meshes. First, we introduce the constraints to allow random access to a Triangle in a sequence of Triangle strips. Then, for each vertex, we construct a list of references to its Adjacent strips as a representation of Triangle connectivity. Experimental results show that, compared to conventional methods, our scheme can reduce the total size of a Triangle mesh and Adjacent Triangle connectivity to about 50%

Min Tang – 3rd expert on this subject based on the ideXlab platform

  • ICCD: Interactive continuous collision detection between deformable models using connectivity-based culling
    IEEE Transactions on Visualization and Computer Graphics, 2009
    Co-Authors: Min Tang, Sean Curtis, Sung-eui Yoon, Dinesh Manocha

    Abstract:

    We present an interactive algorithm for continuous collision detection between deformable models. We introduce multiple techniques to improve the culling efficiency and the overall performance of continuous collision detection. First, we present a novel formulation for continuous normal cones and use these normal cones to efficiently cull large regions of the mesh as part of self-collision tests. Second, we introduce the concept of procedural representative Triangles to remove all redundant elementary tests between nonAdjacent Triangles. Finally, we exploit the mesh connectivity and introduce the concept of orphan sets to eliminate redundant elementary tests between Adjacent Triangle primitives. In practice, we can reduce the number of elementary tests by two orders of magnitude. These culling techniques have been combined with bounding volume hierarchies and can result in one order of magnitude performance improvement as compared to prior collision detection algorithms for deformable models. We highlight the performance of our algorithm on several benchmarks, including cloth simulations, N-body simulations, and breaking objects. © 2006 IEEE.