“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

Conference:


Type:


Title:

    Predictive Point-Cloud Compression

Presenter(s)/Author(s):



Abstract:


    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.

References:


    Devillers, O., and Gandoin, P.-M. 2000. Geometric compression for interactive transmission. In Visualization 2000, 319–326.
    Kronrod, B., and Gotsman, C. 2002. Optimized compression of triangle mesh geometry using prediction trees. In Proceedings of 3DPVT-02, 602–608.
    Peng, J., and Kuo, C. C. J. 2003. Octree-based progressive geometry encoder. In Proceedings of the SPIE, 301–311.
    Waschbüsch, M., Gross, M., Eberhard, F., Lamboray, E., and Würmlin, S. 2004. Progressive compression of point-sampled models. In Eurographics Symposium on Point Based Graphics, 95–102.


ACM Digital Library Publication:



Overview Page: