Affine Alignment of Occluded Shapes (bibtex)
by Zsolt Santa, Zoltan Kato
Abstract:
A novel affine registration technique is proposed which efficiently handles the partial occlusion problem. The proposed method is working without pointwise correspondences or radiometric informations. The aligning transformation is found by solving a system of non-linear equations and minimizing the area of occlusions. Each equation is generated by integrating a non-linear function over the foreground domains of the shapes. In order to deal with occlusions, the shapes are approximated by polygons and the occluded areas are determined with simple boolean operators. Based on the tests on a large synthetic dataset, the proposed approach outperforms state of the art algorithms.
Reference:
Zsolt Santa, Zoltan Kato, Affine Alignment of Occluded Shapes, In Proceedings of International Conference on Pattern Recognition, Stockholm, Sweden, pp. 2155-2160, 2014, IEEE.
Bibtex Entry:
@string{icpr="Proceedings of International Conference on Pattern Recognition"}
@INPROCEEDINGS{Santa-Kato2014,
  author =	 {Zsolt Santa and Zoltan Kato},
  title =	 {Affine Alignment of Occluded Shapes},
  booktitle =	 icpr,
  year =	 2014,
  address =	 {Stockholm, Sweden},
  month =	 aug,
  organization = {IAPR},
  publisher =	 {IEEE},
  pages =	 {2155-2160},
  keywords={image registration;nonlinear equations;nonlinear functions;affine alignment;affine registration technique;aligning transformation;large synthetic dataset;nonlinear equations;nonlinear function;occluded shapes;partial occlusion problem;Approximation algorithms;Approximation methods;Equations;Mathematical model;Minimization;Robustness;Shape},
  isbn =	 {ISBN 978-1-4799-5208-3},
  doi = {10.1109/ICPR.2014.375},
  abstract =	 {A novel affine registration technique is proposed
                  which efficiently handles the partial occlusion
                  problem. The proposed method is working without
                  pointwise correspondences or radiometric
                  informations. The aligning transformation is found
                  by solving a system of non-linear equations and
                  minimizing the area of occlusions. Each equation is
                  generated by integrating a non-linear function over
                  the foreground domains of the shapes. In order to
                  deal with occlusions, the shapes are approximated by
                  polygons and the occluded areas are determined with
                  simple boolean operators. Based on the tests on a
                  large synthetic dataset, the proposed approach
                  outperforms state of the art algorithms.}
}
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