Fast Blended Transformations for Partial Shape Registration

Alon Shtern, Matan Sela, Ron Kimmel

Research output: Contribution to journalArticlepeer-review

Abstract

Automatic estimation of skinning transformations is a popular way to deform a single reference shape into a new pose by providing a small number of control parameters. We generalize this approach by efficiently enabling the use of multiple exemplar shapes. Using a small set of representative natural poses, we propose to express an unseen appearance by a low-dimensional linear subspace, specified by a redundant dictionary of weighted vertex positions. Minimizing a nonlinear functional that regulates the example manifold, the suggested approach supports local-rigid deformations of articulated objects, as well as nearly isometric embeddings of smooth shapes. A real-time nonrigid deformation system is demonstrated, and a shape completion and partial registration framework is introduced. These applications can recover a target pose and implicit inverse kinematics from a small number of examples and just a few vertex positions. The resulting reconstruction is more accurate compared to alternative reduced deformable models.

Original languageEnglish
Pages (from-to)913-928
Number of pages16
JournalJournal of Mathematical Imaging and Vision
Volume60
Issue number6
DOIs
StatePublished - 1 Jul 2018

Keywords

  • Geometric modeling
  • Shape correspondence
  • Shape deformation
  • Skinning

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modelling and Simulation
  • Condensed Matter Physics
  • Computer Vision and Pattern Recognition
  • Geometry and Topology
  • Applied Mathematics

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