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Empirical Inference Conference Paper 2005

Object correspondence as a machine learning problem

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Empirical Inference
Bernhard Schölkopf
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Empirical Inference
Florian Steinke

We propose machine learning methods for the estimation of deformation fields that transform two given objects into each other, thereby establishing a dense point to point correspondence. The fields are computed using a modified support vector machine containing a penalty enforcing that points of one object will be mapped to ``similar‘‘ points on the other one. Our system, which contains little engineering or domain knowledge, delivers state of the art performance. We present application results including close to photorealistic morphs of 3D head models.

Author(s): Schölkopf, B. and Steinke, F. and Blanz, V.
Book Title: Proceedings of the 22nd International Conference on Machine Learning
Pages: 777-784
Year: 2005
Day: 0
Editors: L De Raedt and S Wrobel
Publisher: ACM
Bibtex Type: Conference Paper (inproceedings)
Address: New York, NY, USA
Event Name: ICML 2005
Event Place: Bonn, Germany
Electronic Archiving: grant_archive
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik
Links:

BibTex 

@inproceedings{3386,
  title = {Object correspondence as a machine learning problem},
  booktitle = {Proceedings of the 22nd International Conference on Machine Learning},
  abstract = {We propose machine learning methods for the estimation of
  deformation fields that transform two given objects into each other, thereby establishing a dense point to point correspondence. The fields are computed using a modified support vector machine
  containing a penalty enforcing that points of one object
  will be mapped to ``similar‘‘ points on the other one. Our system,
  which contains little engineering or domain knowledge, delivers
  state of the art performance. We present application results including close to
  photorealistic morphs of 3D head models.},
  pages = {777-784},
  editors = {L De Raedt and S Wrobel},
  publisher = {ACM},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {New York, NY, USA},
  year = {2005},
  slug = {3386},
  author = {Sch{\"o}lkopf, B. and Steinke, F. and Blanz, V.}
}