@string{tpami="IEEE Transactions on Pattern Analysis and Machine Intelligence"}
@ARTICLE{Domokos-etal2012,
  author = {Domokos, Csaba and Nemeth, Jozsef and Kato, Zoltan},
  title = {Nonlinear Shape Registration without Correspondences},
  journal = tpami,
  year = {2012},
  volume = {34},
  pages = {943--958},
  number = {5},
  month = may,
  abstract = {In this paper, we propose a novel framework to estimate the parameters
	of a diffeomorphism that aligns a known shape and its distorted observation.
	Classical registration methods first establish correspondences between
	the shapes and then compute the transformation parameters from these
	landmarks. Herein, we trace back the problem to the solution of a
	system of nonlinear equations which directly gives the parameters
	of the aligning transformation. The proposed method provides a generic
	framework to recover any diffeomorphic deformation without established
	correspondences. It is easy to implement, not sensitive to the strength
	of the deformation, and robust against segmentation errors. The method
	has been applied to several commonly used transformation models.
	The performance of the proposed framework has been demonstrated on
	large synthetic data sets as well as in the context of various applications.},
  doi = {10.1109/TPAMI.2011.200},
  issn = {0162-8828},
  pdf = {papers/pami2012.pdf}
}