@string{iciar="International Conference on Image Analysis and Recognition"}
@string{lncs="Lecture Notes in Computer Science"}
@string{springer="Springer"}
@INPROCEEDINGS{Kato2012,
  author = {Zoltan Kato},
  title = {A Unifying Framework for Correspondence-less Linear Shape Alignment},
  booktitle = iciar,
  year = {2012},
  editor = {A. Campilho and M. Kamel},
  volume = {7324},
  series = lncs,
  pages = {277--284},
  address = {Aveiro, Portugal},
  month = jun,
  publisher = springer,
  abstract = {We consider the estimation of linear transformations aligning a known
	binary shape and its distorted observation. The classical way to
	solve this registration problem is to find correspondences between
	the two images and then compute the transformation parameters from
	these landmarks. Here we propose a unified framework where the exact
	transformation is obtained as the solution of either a polynomial
	or a linear system of equations without establishing correspondences.
	The advantages of the proposed solutions are that they are fast,
	easy to implement, have linear time complexity, work without landmark
	correspondences and are independent of the magnitude of transformation.},
  pdf = {papers/iciar2012.pdf}
}