Scale invariant robust registration of 3d-point data and a triangle mesh by global optimization

Authors:
Onay Urfalıoḡlu;Patrick Mikulastik;Ivo Stegmann
Affiliations:
Information Technology Laboratory (LFI), University of Hannover;Information Technology Laboratory (LFI), University of Hannover;Information Technology Laboratory (LFI), University of Hannover
Venue:
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
Year:
2006

Citing 3
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Abstract

A robust registration of 3D-point data and a triangle mesh of the corresponding 3D-structure is presented, where the acquired 3D-point data may be noisy, may include outliers and may have wrong scale. Furthermore, in this approach it is not required to have a good initial match so the 3D-point cloud and the according triangle mesh may be loosely positioned in space. An additional advantage is that no correspondences have to exist between the 3D-points and the triangle mesh. The problem is solved utilizing a robust cost function in combination with an evolutionary global optimizer as shown in synthetic and real data experiments.