GAMES Webinar 2021 – 173期(几何处理专题) | Nicholas Sharp (Carnegie Mellon University)


【GAMES Webinar 2021-173期】(几何处理专题)

报告嘉宾:Nicholas Sharp (Carnegie Mellon University)


报告题目:Intrinsic Triangulations in Geometry Processing


Triangle meshes are widely used to represent surfaces in 3D geometry. Intrinsic triangulations depart from the norm with a simple idea: what if instead of representing the geometry of a mesh by the location of its vertices, we used only the length of its edges? This alternate representation provides just the right flexibility to unlock powerful algorithms for a variety of tasks, with particular benefits for robust geometry processing. In this talk, we will introduce the basic theory and practice of intrinsic triangulations, then share advances extending intrinsic triangulations to nonmanifold meshes and point clouds, and even a new algorithm for computing geodesics on surfaces using only edge flips. Throughout, we’ll show applications to classic tasks in geometry processing, where intrinsic triangulations improve accuracy, robustness, and efficiency.


Nicholas Sharp is a final-year PhD candidate in Computer Science at Carnegie Mellon University, advised by Keenan Crane and supported by an NSF Fellowship. His research is in geometry processing, designing new algorithms and data structures for 3D data, with applications in computer graphics, vision, and 3D machine learning.




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