Iterative Estimation of 3D Transformations for Object Alignment

  • Tao Wang
  • Anup Basu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4291)


An Iterative Estimation Algorithm (IEA) of 3D transformations between two objects is presented in this paper. Skeletons of the 3D objects are extracted using a fully parallel thinning technique, feature point pairs (land markers) are extracted from skeletons automatically with a heuristic rule, and a least squares method and an iterative approach are applied to estimate the 3D transformation matrix. The algorithm has three advantages. First of all, no initial transformation matrix is needed. Secondly, user interaction is not required for identifying the land markers. Thirdly, the time complexity of this algorithm is polynomial. Experiments show that this method works quite well with high accuracy when the translations and rotation angles are small, even when noise exists in the data.


Object Point Heuristic Rule Point Correspondence Line Point Airway Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Tao Wang
    • 1
  • Anup Basu
    • 1
  1. 1.Department of Computing ScienceUniv. of AlbertaEdmontonCanada

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