GEncode: geometry-driven compression for general meshes

GEncode: geometry-driven compression for general meshes
Thomas Lewiner, Marcos Craizer, Hélio Lopes, Sinésio Pesco, Luiz Velho, Esdras Medeiros

Computer Graphics Forum 25(4): pp. 685-695 (december 2006)
Selected for publication from the Sibgrapi 2005 conference


Performances of actual mesh compression algorithms vary significantly depending on the type of model it encodes. These methods rely on prior assumptions on the mesh to be efficient, such as regular connectivity, simple topology and similarity between its elements. However, these priors are implicit in usual schemes, harming their suitability for specific models. In particular, connectivity-driven schemes are difficult to generalize to higher dimensions and to handle topological singularities. GEncode is a new single-rate, geometry-driven compression scheme where prior knowledge of the mesh is plugged into the coder in an explicit manner. It encodes meshes of arbitrary dimension without topological restrictions, but can incorporate topological properties, such as manifoldness, to improve the compression ratio. Prior knowledge of the geometry is taken as an input of the algorithm, represented by a function of the local geometry. This suits particularly well for scanned and remeshed models, where exact geometric priors are available. Compression results surfaces and volumes are competitive with existing schemes.


PDF paper (1.4 MB)
GEncode: geometry-driven compression for general meshes


    author = {Thomas Lewiner and Marcos Craizer and Hélio Lopes and Sinésio Pesco and Luiz Velho and Esdras Medeiros},
    title = {GEncode: geometry-driven compression for general meshes},
    year = {2006},
    month = {december},
    journal = {Computer Graphics Forum},
    volume = {25},
    number = {4},
    pages = {685--695},
    publisher = {Eurographics},
    doi = {10.1111/j.1467-8659.2006.00990.x},
    url = {\url{}}

Last modifications on July 3rd, 2013