“Predictive Point-Cloud Compression” by Gumhold, Kami, Isenburg and Seidel

  • ©Stefan Gumhold, Zachi Kami, Martin Isenburg, and Hans-Peter Seidel

  • ©Stefan Gumhold, Zachi Kami, Martin Isenburg, and Hans-Peter Seidel




    Predictive Point-Cloud Compression



    Point clouds have recently become a popular alternative to polygonal meshes for representing three-dimensional geometric models. 3D photography and scanning systems acquire the geometry and appearance of real-world objects in form of point samples. Rendering directly with points eliminates the complex task of reconstructing a surface and allows handling of non-surfaces like models such as trees. With modern acquisition techniques producing larger and larger amounts of points, efficient schemes for compressing such data have become necessary.


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