Abstract
Complete 3-D modeling of a free-form object requires acquisition from multiple view-points. These views are then required to be registered in a common coordinate system by establishing correspondence between them in their regions of overlap. In this paper, we present an automatic correspondence technique for pair-wise registration of different views of a free-form object. The technique is based upon a novel robust representation scheme reported in this paper. Our representation scheme defines local 3-D grids over the object’s surface and represents the surface inside each grid by a fourth order tensor. Multiple tensors are built for the views which are then matched, using a correlation and verification technique to establish correspondence between a model and a scene tensor. This correspondence is then used to derive a rigid transformation that aligns the two views. The transformation is verified and refined using a variant of ICP. Our correspondence technique is fully automatic and does not assume any knowledge of the viewpoints or regions of overlap of the data sets. Our results show that our technique is accurate, robust, efficient and independent of the resolution of the views.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Mian, A.S., Bennamoun, M., Owens, R.: Automatic Correspondence for 3D Modeling: An Extensive Review (2004) (submitted to a journal)
Besl, P.J., McKay, N.D.: Reconstruction of Real-world Objects via Simultaneous Registration and Robust Combination of Multiple Range Images. IEEE Transactions on Pattern Analysis and Machine Intelligence 14(2), 239–256 (1992)
Chen, Y., Medioni, G.: Object Modeling by Registration of Multiple Range Images. In: IEEE International Conference on Robotics and Automation, pp. 2724–2729 (1991)
Rangarajan, A., Chui, H., Duncan, J.S.: Rigid point feature registration using mutual information. Medical Image Analysis 3(4), 425–440 (1999)
Chen, C., Hung, Y., Cheng, J.: RANSAC-Based DARCES: A New Approach to Fast Automatic Registration of Partially Overlapping Range Images. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(11), 1229–1234 (1991)
Wyngaerd, J., Gool, L., Koth, R., Proesmans, M.: Invariant-based Registration of Surface Patches. In: IEEE International Conference on Computer Vision, vol. 1, pp. 301–306 (1999)
Chua, C.S., Jarvis, R.: 3D Free-Form Surface Registration and Object Recognition. International Journal of Computer Vision 17, 77–99 (1996)
Higuchi, K., Hebert, M., Ikeuchi, K.: Building 3-D Models from Unregistered Range Images. In: IEEE International Conference on Robotics and Automation, vol. 3, pp. 2248–2253 (1994)
Ashbrook, A.P., Fisher, R.B., Robertson, C., Werghi, N.: Finding Surface Correspondence for Object Recognition and Registration Using Pairwise Geometric Histograms. International Journal of Pattern Recognition and Artificial Intelligence 2, 674–686 (1998)
Stephens, R.S.: A probabilistic approach to the Hough transform. In: British Machine Vision Conference, pp. 55–59 (1990)
Roth, G.: Registering Two Overlapping Range Images. In: IEEE International Conference on 3-D Digital Imaging and Modeling, pp. 191–200 (1999)
Johnson, A.E., Hebert, M.: Surface Registration by Matching Oriented Points. In: International Conference on Recent Advances in 3-D Imaging and Modeling, pp. 121–128 (1997)
Johnson, A.E.: Spin Images: A Representation for 3-D Surface Matching. PhD. Thesis, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213 (1997)
Foley, J., van Dam, A., Feiner, S.K., Hughes, J.F.: Computer Graphics-Principles and Practice, 2nd edn. Addison-Wesley, Reading (1990)
Zhang, Z.: Iterative Point Matching for Registration of Free-form Curves and Surfaces. International Journal of Computer Vision 13(2), 119–152 (1994)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mian, A.S., Bennamoun, M., Owens, R. (2004). Matching Tensors for Automatic Correspondence and Registration. In: Pajdla, T., Matas, J. (eds) Computer Vision - ECCV 2004. ECCV 2004. Lecture Notes in Computer Science, vol 3022. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24671-8_39
Download citation
DOI: https://doi.org/10.1007/978-3-540-24671-8_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-21983-5
Online ISBN: 978-3-540-24671-8
eBook Packages: Springer Book Archive