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Variational harmonic maps for space deformation
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ACM Transactions on Graphics (TOG) archive
Volume 28 ,  Issue 3  (August 2009) table of contents
Proceedings of ACM SIGGRAPH 2009
SESSION: Shape editing and deformation table of contents
Article No. 34  
Year of Publication: 2009
ISSN:0730-0301
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Authors
Mirela Ben-Chen  Technion -- Israel Institute of Technology
Ofir Weber  Technion -- Israel Institute of Technology
Craig Gotsman  Technion -- Israel Institute of Technology
Publisher
ACM  New York, NY, USA
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APPENDICES and SUPPLEMENTS
ZIP contents: variational_harmonic_maps.mov - The movie accompanying the paper.


ABSTRACT

A space deformation is a mapping from a source region to a target region within Euclidean space, which best satisfies some userspecified constraints. It can be used to deform shapes embedded in the ambient space and represented in various forms -- polygon meshes, point clouds or volumetric data. For a space deformation method to be useful, it should possess some natural properties: e.g. detail preservation, smoothness and intuitive control. A harmonic map from a domain ω ⊂ Rd to Rd is a mapping whose d components are harmonic functions. Harmonic mappings are smooth and regular, and if their components are coupled in some special way, the mapping can be detail-preserving, making it a natural choice for space deformation applications. The challenge is to find a harmonic mapping of the domain, which will satisfy constraints specified by the user, yet also be detail-preserving, and intuitive to control. We generate harmonic mappings as a linear combination of a set of harmonic basis functions, which have a closed-form expression when the source region boundary is piecewise linear. This is done by defining an energy functional of the mapping, and minimizing it within the linear span of these basis functions. The resulting mapping is harmonic, and a natural "As-Rigid-As-Possible" deformation of the source region. Unlike other space deformation methods, our approach does not require an explicit discretization of the domain. It is shown to be much more efficient, yet generate comparable deformations to state-of-the-art methods. We describe an optimization algorithm to minimize the deformation energy, which is robust, provably convergent, and easy to implement.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Collaborative Colleagues:
Mirela Ben-Chen: colleagues
Ofir Weber: colleagues
Craig Gotsman: colleagues