Iterative estimation of 3d transformations for object alignment

Authors:
Tao Wang;Anup Basu
Affiliations:
Department of Computing Science, Univ. of Alberta, Edmonton, AB, Canada;Department of Computing Science, Univ. of Alberta, Edmonton, AB, Canada
Venue:
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
Year:
2006

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Abstract

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.