Abstract
A key challenge in reconstructing high-quality 3D scans is registering data from different viewpoints. Existing global (multiview) alignment algorithms are restricted to rigid-body transformations, and cannot adequately handle non-rigid warps frequently present in real-world datasets. Moreover, algorithms that can compensate for such warps between pairs of scans do not easily generalize to the multiview case. We present an algorithm for obtaining a globally optimal alignment of multiple overlapping datasets in the presence of low-frequency non-rigid deformations, such as those caused by device nonlinearities or calibration error. The process first obtains sparse correspondences between views using a locally weighted, stability-guaranteeing variant of iterative closest points (ICP). Global positions for feature points are found using a relaxation method, and the scans are warped to their final positions using thin-plate splines. Our framework efficiently handles large datasets---thousands of scans comprising hundreds of millions of samples---for both rigid and non-rigid alignment, with the non-rigid case requiring little overhead beyond rigid-body alignment. We demonstrate that, relative to rigid-body registration, it improves the quality of alignment and better preserves detail in 3D datasets from a variety of scanners exhibiting non-rigid distortion.
Supplemental Material
- Allen, B., Curless, B., and Popović, Z. 2003. The space of human body shapes: Reconstruction and parameterization from range scans. ACM Trans. Graphics (Proc. SIGGRAPH) 22, 3, 587--594. Google ScholarDigital Library
- Benjemaa, R., and Schmitt, F. 1998. A solution for the registration of multiple 3d point sets using unit quaternions. In Proc. ECCV. Google ScholarDigital Library
- Bergevin, R., Soucy, M., Gagnon, H., and Laurendeau, D. 1996. Towards a general multi-view registration technique. IEEE Trans. PAMI 18, 5, 540--547. Google ScholarDigital Library
- Bernardini, F., Rushmeier, H., Martin, I. M., Mittle-Man, J., and Taubin, G. 2002. Building a digital model of Michelangelo's Florentine Pietà. IEEE Computer Graphics and Applications 22, 1, 59--67. Google ScholarDigital Library
- Besl, P. J., and McKay, N. D. 1992. A method for registration of 3-D shapes. IEEE Trans. PAMI 14, 2, 239--256. Google ScholarDigital Library
- Bookstein, F. L. 1989. Principal warps: Thin-plate splines and the decomposition of deformations. IEEE Trans. PAMI 11, 6 (June), 567 -- 585. Google ScholarDigital Library
- Brown, B., and Rusinkiewicz, S. 2004. Non-rigid range-scan alignment using thin-plate splines. In Proc. 3DPVT. Google ScholarCross Ref
- Chen, Y., and Medioni, G. 1992. Object modelling by registration of multiple range images. Image and Vision Computing 10, 3, 145--155. Google ScholarDigital Library
- Chui, H., and Rangarajan, A. 2003. A new point matching algorithm for non-rigid registration. CVIU 89, 2--3 (February-March), 114--141. Google ScholarDigital Library
- Curless, B., and Levoy, M. 1996. A volumetric method for building complex models from range images. In Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, ACM Press, 303--312. Google ScholarDigital Library
- Duchon, J. 1977. Splines minimizing rotation-invariant seminorms in Sobolev spaces. In Constructive Theory of Functions of Several Variables, Springer-Verlag, Berlin, 85--100.Google Scholar
- Gelfand, N., Ikemoto, L., Rusinkiewicz, S., and Levoy, M. 2003. Geometrically stable sampling for the ICP algorithm. In Proc. 3DIM.Google Scholar
- Hähnel, D., Thrun, S., and Burgard, W. 2003. An extension of the ICP algorithm for modeling nonrigid objects with mobile robots. In Proc. IJCAI, IJCAI. Google ScholarDigital Library
- Huang, Q.-X., Flöry, S., Gelfand, N., Hofer, M., and Pottmann, H. 2006. Reassembling fractured objects by geometric matching. In SIGGRAPH '06: ACM SIGGRAPH 2006 Papers, ACM Press, New York, NY, USA, 569--578. Google ScholarDigital Library
- Ikemoto, L., Gelfand, N., and Levoy, M. 2003. A hierarchical method for aligning warped meshes. In Proc. 3DIM.Google Scholar
- Jian, B., and Vemuri, B. 2005. A robust algorithm for point set registration using mixture of gaussians. In Proc. ICCV. Google ScholarDigital Library
- Krishnan, S., Lee, P., Moore, J., and Venkatasubramanian, S. 2005. Simultaneous registration of multiple 3d point sets via optimization on a manifold. In Proc. Symposium on Geometry Processing. Google ScholarDigital Library
- Levoy, M., Pulli, K., Curless, B., Rusinkiewicz, S., Koller, D., Pereira, L., Ginzton, M., Anderson, S., Davis, J., Ginsberg, J., Shade, J., and Fulk, D. 2000. The Digital Michelangelo Project: 3-D scanning of large statues. In Proc. SIGGRAPH. Google ScholarDigital Library
- Li, X., and Guskov, I. 2005. Multiscale features for approximate alignment of point-based surfaces. In Symposium on Geometry Processing, 217--226. Google ScholarDigital Library
- Nehab, D., Rusinkiewicz, S., Davis, J., and Ramamoorthi, R. 2005. Efficiently combining positions and normals for precise 3D geometry. ACM Transactions on Graphics (Proc. SIGGRAPH) 24, 3 (Aug.). Google ScholarDigital Library
- Neugebauer, P. J. 1997. Geometrical cloning of 3D objects via simultaneous registration of multiple range images. In Proc. SMA, IEEE Computer Society, 130. Google ScholarDigital Library
- Pulli, K. 1999. Multiview registration for large data sets. In Proc. 3DIM. Google ScholarDigital Library
- Rusinkiewicz, S. 2001. Efficient variants of the ICP algorithm. In Proc. 3DIM.Google ScholarCross Ref
- Shum, H.-Y, and Szeliski, R. 2000. Construction of panoramic mosaics with global and local alignment. International Journal of Computer Vision 36, 2, 101--130. Google ScholarDigital Library
- Sorkine, O., Lipman, Y., Cohen-Or, D., Alexa, M., Rössl, C., and Seidel, H.-P. 2004. Laplacian surface editing. In Proceedings of the Eurographics/ACM SIGGRAPH Symposium on Geometry Processing, ACM Press, 179--188. Google ScholarDigital Library
- Wahba, G. 1990. Spline Models for Observational Data. Society for Industrial and Applied Mathematics, Philadelphia, PA, ch. 2.4.Google Scholar
- Wen, G., Zhu, D., Xia, S., and Wang, Z. 2005. Total least squares fitting of point sets in m-d. In Computer Graphics International. Google ScholarDigital Library
- Williams, J., and Bennamoun, M. 2000. A multiple view 3D registration algorithm with statistical error modeling. IEICE Transactions on Information and Systems E83-D(8) (August), 1662--1670.Google Scholar
- Woodham, R. J. 1980. Photometric method for determining surface orientation from multiple images. Optical Engineering 19, 1, 139--144.Google ScholarCross Ref
Index Terms
- Global non-rigid alignment of 3-D scans
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