Abstract
Recent developments in shape-based modeling and data acquisition have brought three-dimensional models to the forefront of computer graphics and visualization research. New data acquisition methods are producing large numbers of models in a variety of fields. Three-dimensional registration (alignment) is key to the useful application of such models in areas from automated surface inspection to cancer detection and surgery. The algorithms developed in this research accomplish automatic registration of three-dimensional voxelized models. We employ features in a wavelet transform domain to accomplish registration. The features are extracted in a multi-resolutional format, thus delineating features at various scales for robust and rapid matching. Registration is achieved by using a voting scheme to select peaks in sets of rotation quaternions, then separately identifying translation. The method is robust to occlusion, clutter, and noise. The efficacy of the algorithm is demonstrated through examples from solid modeling and medical imaging applications.
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Acknowledgments
This work was supported in part by the National Defense Science and Engineering Graduate (NDSEG) Fellowship to the first author, by U.S. National Science Foundation grant DMI-062933 and by the SMART Center for Environmental Sensing and Modeling (CENSAM) sponsored by the Singapore National Research Foundation. The authors thank Drs. D. C. Gossard, V. Goyal, W. Cho, and M. K. Reuter for their comments on earlier versions of this work.
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Chalfant, J.S., Patrikalakis, N.M. Three-dimensional object registration using wavelet features. Engineering with Computers 25, 303–318 (2009). https://doi.org/10.1007/s00366-009-0126-5
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DOI: https://doi.org/10.1007/s00366-009-0126-5