CAD based 3d object recognition on range images
In industrial manufacturing the production process still is separated from the design level. But, the growing need for a higher standard of quality, a higher variety of products and a more flexible production forces to bring the separated fields together. Only a broad communication between all levels can guarantee that the causes for malfunctions are eliminated early and quickly. Thus, it is desirable to use general CAD descriptions at all levels of manufacturing. One step towards this direction is the new field called CAD Based Vision (CBV) introducing usual CAD object representations into the computer vision community (e. g. [7, 13, 16]).
KeywordsFeature Point Range Image Correct Match Polygonal Approximation Image Order
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- J. C. Bezdek and S. K. Pal. Fuzzy Models For Pattern Recognition. IEEE Press, New York, 1992.Google Scholar
- B. Krebs and F. M. Wahl. Efficient planar patch segmentation of range images via 3d approximation. Technical Report 12–94–1, Institute of Robotics and Computer Control, TU Braunschweig, 1994.Google Scholar
- G. E. Farin. Curves and Surfaces for Computer Aided Geometric Design, a Practical Guide 3rd. ed. Academic Press, New York, 1993.Google Scholar
- K. Higuchi, M. Hebert, and K. Ikeuchi. Bulding 3-d models from unregisterd range images. In Proc. IEEE International Conference on Robotics and Automation, San Diego, California, pages 2248–2253, 1994.Google Scholar
- J. Mao, A. K. Jain, and P. J. Flynn. Integration of multiple feature groups and multiple views into an 3d object recognition system. In Proc.CAD-Based Vision Workshop, Champion, Pennsylvania, pages 184–192, 1994.Google Scholar
- L. G. Shapiro, S. L. Tanimoto, and J. F. Brinkley. A visual database system for data experiment management in model-based computer vision. In Proc. CAD-Based Vision Workshop, Champion, Pennsylvania, pages 64–74, 1994.Google Scholar
- D. A. Simon, M. Hebert, and T. Kanade. Real-time 3-d pose estimation using a high-speed range sensor. In Proc. IEEE International Conference on Robotics and Automation, San Diego, California, volume 3, pages 2235–2240, 1994.Google Scholar
- T. Stahs and F. Wahl. Fast and versatile range data acquisition in a robot work cell. In Proc IEEE International Conference on Intelligent Robots and Systems, Raleigh, North Carolina, pages 1169–1174, 1992.Google Scholar
- T. Stahs and F. M. Wahl. Object recognition and pose estimation with a fast and versatile 3d robot sensor. In Proc. International Conference on Pattern Recognition, The Hague, Netherlands, 1992.Google Scholar
- F. M. Wahl. A coded light approach for depth map aquisition. In G. Hartmann, editor, 8. DA G M- Sympo sium Paderborn. Springer-Verlag, 1986.Google Scholar