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Multi-level Partition of Unity Implicits

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons45141

Ohtake,  Yutaka
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44112

Belyaev,  Alexander
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45449

Seidel,  Hans-Peter
Computer Graphics, MPI for Informatics, Max Planck Society;

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Zitation

Ohtake, Y., Belyaev, A., Alexa, M., Turk, G., & Seidel, H.-P. (2003). Multi-level Partition of Unity Implicits. ACM Transactions on Graphics, 22, 463-470.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-2D7E-0
Zusammenfassung
We present a shape representation, the {\em multi-level partition of unity} implicit surface, that allows us to construct surface models from very large sets of points. There are three key ingredients to our approach: 1) piecewise quadratic functions that capture the local shape of the surface, 2) weighting functions (the partitions of unity) that blend together these local shape functions, and 3) an octree subdivision method that adapts to variations in the complexity of the local shape. Our approach gives us considerable flexibility in the choice of local shape functions, and in particular we can accurately represent sharp features such as edges and corners by selecting appropriate shape functions. An error-controlled subdivision leads to an adaptive approximation whose time and memory consumption depends on the required accuracy. Due to the separation of local approximation and local blending, the representation is not global and can be created and evaluated rapidly.Because our surfaces are described using implicit functions, operations such as shape blending, offsets, deformations and CSG are simple to perform.