Robust matching of 3D contours using iterative closest point algorithm improved by M-estimation
✍ Scribed by Shun'ichi Kaneko; Tomonori Kondo; Atsushi Miyamoto
- Publisher
- Elsevier Science
- Year
- 2003
- Tongue
- English
- Weight
- 333 KB
- Volume
- 36
- Category
- Article
- ISSN
- 0031-3203
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✦ Synopsis
An extension of the iterative closest point matching by M-estimation is proposed for realization of robustness to non-overlapping data or outlying data in two sets of contour data or depth images for rigid bodies. An objective function which includes independent residual components for each of x, y and z coordinates is originally deÿned and proposed to evaluate the ÿtness, simultaneously dealing with a distribution of outlying gross noise. The proposed procedure is based on modiÿed M-estimation iterations with bi-weighting coe cients for selecting corresponding points for optimization of estimating the transforms for matching. The transforms can be represented by 'quaternions' in the procedure to eliminate redundancy in representation of rotational degree of freedom by linear matrices. Optimization steps are performed by the simplex method because it does not need computation of di erentiation. Some fundamental experiments utilizing real data of 2D and 3D measurement show e ectiveness of the proposed method. When reasonable initial positions are given, the unique solution of position could be provided in spite of surplus point data in the objects. And then the outlying data could be ÿltered out from the normal ones by the proposed method.