Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-25T04:12:49.113Z Has data issue: false hasContentIssue false
  • English
  • Français

Complete 3D boundary representation from multiple range images: exploiting geometric constraints*

Published online by Cambridge University Press:  09 March 2009

Kamal Gupta  and
Zukang Xu
Get access Rights & Permissions [Opens in a new window]

Summary

We describe an approach that generates a complete b-rep description of a polyhedral object from (geometric primitives derived from) dense range images taken from multiple view-points. Our approach, starting from basic face models of visible surfaces of objects in each local view, matches certain geometric features, extracts rigid-body transformations that relate the local views, and incrementally merges the face models (in local views) into a global 3-dimensional b-rep description of the object. A convenient and effective termination criterion is designed to monitor the merging process. The emphasis is on the use of geometric constraints in building a complete 3-dimensional model of the object.

We have implemented this system in C, running on a SUN Sparcstation. The system, as presented, has been tested on face models derived from several synthetic and real range images and performs successfully with realistic noise levels.

Keywords

Geometric constraintsPolyhedral object3-dimensional modelMultiple range images
Type
Articles
Information
Robotica , Volume 13 , Issue 4 , July 1995 , pp. 339 - 349
Copyright
Copyright © Cambridge University Press 1995

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Besl, P.J., “Active, optical range imaging sensors”. Machine Vision and Applications 1, 127–152 (1988).CrossRefGoogle Scholar
2.Foley, J.D.Dam, A.V., Feiner, S.K. and Hughes, J.F., Computer Graphics (Addison-Wesley, second edition, Reading, Mass., 1991) pp. 533–546.Google Scholar
3.Latombe, Jean-Claude, Robot Motion Planning (Kluwer Academic, Amsterdam, 1991).CrossRefGoogle Scholar
4.Gupta, Kamal Kant, “Fast collision avoidance for manipulator arms: A sequential search strategy” IEEE Transactions on Robotics anil Automation 6(5) 522–532 (07, 1990).CrossRefGoogle Scholar
5.Henderson, T.C., “Efficient 3d object representations for industrial vision systems” IEEE Transactions on Pattern Analysis and Machine Intelligence 5 609–617 (1983).CrossRefGoogle ScholarPubMed
6.Kim, H.-S., Jain, R.C. and Volz, R.A., “Object recognition using multiple views” IEEE International Conference on Robotics and Automation (1985) pp.28–33.Google Scholar
7.Parvin, H. and Medioni, G., “B-rep from unregistered multiple range images” IEEE International Conference on Robotics and Automation, Nice France (1992) pp.1602–1607.Google Scholar
8.Stenstrom, J.R. and Connolly, C.I., “Building wire frames from multiple range views” IEEE International Conference on Robotics and Automation (1986) pp. 615–620.Google Scholar
9.Potmesil, M., “Generating models of solid objects by matching 3D surface segments” The International Joint Conference on Artificial Intelligence (1983) pp. 1089–1093.Google Scholar
10.Ferrie, F.P., “Reconstructing and Interpreting the 3D Shape of Moving Objects” PhD thesis (McGill University. Montreal, Quebec. Canada, 1986).Google Scholar
11.Gaston, P.C. and Lozano-Perez, T.. “Tactile recognition and localization using object models: The case of polyhedra on a plane” IEEE Transactions on Pattern Analysis and Machine Intelligence 6(3) 257–266 (1984).CrossRefGoogle ScholarPubMed
12.Requicha, A. and Voelcker, H., “Boolean operations in solid modelling: Boundary evaluations and merging algorithms” Proceedings of the IEEE 73(1) 30–44 (1985).CrossRefGoogle Scholar
13.Gupta, Kamal Kant and Zhu, Xiaoming, “A hybrid approach to building boundary descriptions of visible polyhedral surfaces in a range image” (Basu, A., editor) Computer Vision: Systems, Theory, and Applications (World Scientific Press, 1992).Google Scholar
14.Zhu, X.M., “Extracting polyhedral models from a range image – a hybrid approach” Master's thesis (School of Engineering Science, Simon Fraser University, Burnaby. B.C. Canada, 1991).Google Scholar
15.Xu, Zukang, “Extracting b-reps for robotic tasks from multiple range images” Master's thesis (School of Engineering Science, Simon Fraser University. B.C.. Canada, 1992).Google Scholar
16.Faugeras, O.D. and Herbert, M., “A 3-D recognition and positioning algorithm using geometrical matching between primitive surfaces” The International Joint Conference on Artificial Intelligence (1983) pp. 996–1002.Google Scholar
17.Angeles, J., “Automatic computation of the screw parameters of rigid-body motion” J. Dynamic Systems, Measurement, and Control 108(3), 32–38 (03, 1986).CrossRefGoogle Scholar
18.Craig, John, Introduction to Robotics (Addison Wesley. Reading, Mass., 1986).Google Scholar