Ben Houston

Ben Houston

Canada
3K followers 500+ connections

Activity

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Experience

  • ThreeKit Graphic

    ThreeKit

    Ottawa, Ontario

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    Ottawa, Canada Area

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    Ottawa, Canada Area

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Education

  • Carleton University Graphic

    Carleton University

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    Activities and Societies: Cognitive Science Society, Debate Team, ACM Programming Team

Publications

  • Tetrahedral embedded boundary methods for accurate and flexible adaptive fluids

    Computer Graphics Forum (Eurographics)

    When simulating fluids, tetrahedral methods provide flexibility and ease of adaptivity that Cartesian grids find difficult to match. However, this approach has so far been limited by two conflicting requirements. First, accurate simulation requires quality Delaunay meshes and the use of circumcentric pressures. Second, meshes must align with potentially complex moving surfaces and boundaries, necessitating continuous remeshing. Unfortunately, sacrificing mesh quality in favour of speed yields…

    When simulating fluids, tetrahedral methods provide flexibility and ease of adaptivity that Cartesian grids find difficult to match. However, this approach has so far been limited by two conflicting requirements. First, accurate simulation requires quality Delaunay meshes and the use of circumcentric pressures. Second, meshes must align with potentially complex moving surfaces and boundaries, necessitating continuous remeshing. Unfortunately, sacrificing mesh quality in favour of speed yields inaccurate velocities and simulation artifacts. We describe how to eliminate the boundary-matching constraint by adapting recent embedded boundary techniques to tetrahedra, so that neither air nor solid boundaries need to align with mesh geometry.

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  • Hierarchical RLE level set: A compact and versatile deformable surface representation

    ACM Transactions on Graphics

    This article introduces the Hierarchical Run-Length Encoded (H-RLE) Level Set data structure. This novel data structure combines the best features of the DT-Grid (of Nielsen and Museth [2004]) and the RLE Sparse Level Set (of Houston et al. [2004]) to provide both optimal efficiency and extreme versatility. In brief, the H-RLE level set employs an RLE in a dimensionally recursive fashion.

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  • RLE sparse level sets

    ACM SIGGRAPH

    The RLE (run-length encoded) sparse level set is a novel scalable level set representation. This compact level set representation, and it's ability to represent animated characters, was used in the creation of the "Tar Monster" CG character featured in the movie Scooby Doo 2.

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Projects

  • Exocortex Species

    - Present

    Python programming and Softimage plug-in development of Species which allows users to quickly iterate through the character development process and transition seamlessly into animation of the same character using the build in auto-rigging system.

    Other creators
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