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3D Modeling Based on Attributed Hypergrphs

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Part of the book series: The International Series in Engineering and Computer Science ((SECS,volume 762))

Abstract

This chapter introduces a mathematical framework for 3D visions and modeling based on attributed hypergraph representation (AHR). It presents the data structure and algorithms that build, manipulate and transform augmented AHRs. The AHR model is built upon irregular triangular meshes. A net-like data structure is designed to handle the dynamic changes in AHR to give flexibility to the graph structure. Our research and implementation demonstrate the integration of machine vision and computer graphics.

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References

  1. A. H. Barr. “Superquadrics and angle-preserving transformations”. IEEE Computer Graphics Applications, vol. 18, pp. 21–30, 1981.

    Google Scholar 

  2. T. S. Chua, K. H. Hay and W. N. Chin. “Optimization constraint model for dynamic animation”. Computer Graphics and Applications, Proc. of Pacific Graphics ‘93, vol. 1, pp. 61–72, 1993.

    Google Scholar 

  3. P. Dierckx, Curve and Surface Fitting with Splines, Oxford University Press, 1993.

    Google Scholar 

  4. R. E. Fayek and A. K. C. Wong, “Triangular mesh model for natural terrain”. Proc. of SPIE: Intelligent Robots and Computer Vision, October, 1994.

    Google Scholar 

  5. M. A. Fischler and R. C. Bolles. “Random sample consensus: A paradigm for model fitting applications to image analysis and automated cartography”. ACM Communications, vol. 24, pp. 381–395, 1981.

    MathSciNet  Google Scholar 

  6. L. De Floriani and E. Puppo. “Constrained delaunay triangulation for multi-resolution surface description”. Pattern Recognition, pp. 566–569, 1988.

    Google Scholar 

  7. Q. C. Gao and A.K.C. Wong. “A curve detection approach based on perceptual organization”. Pattern Recognition, vol. 26, no. 7, pp. 1039–1046, August, 1993.

    Article  Google Scholar 

  8. H. C. Longufet-Higgins. “A computer algorithm for reconstructing a scene from two projections”. Nature, vol. 293, pp. 133–135, 1981.

    Google Scholar 

  9. W. Niem and H. Broszio. “Mapping texture from multiple camera views onto 3D object models for computer animation”. Proc. of the Int. Workshop on Stereoscopic and 3D Imaging, Santorini, Greece, September, 1995.

    Google Scholar 

  10. M. Pave. Fundamentals of Pattern Recognition. 2nd edition, Marcel Dekker Inc., 1993.

    Google Scholar 

  11. A. C. Shaw. “Parsing of graph-representation pictures”. Journal of ACM, vol. 17, pp. 453–481, 1970

    Article  MATH  Google Scholar 

  12. D. Terzopoulos and D. Metaxas. “Dynamic 3D models with local and global deformations: Deformable Superquadrics”. IEEE Trans. PAMI, vol. 13, no. 7, pp. 703–714, 1991.

    Google Scholar 

  13. D. Terzopoulos and K. Waters. “Analysis and synthesis of facial image sequences using physical and anatomical models”. IEEE Trans. PAMI, vol. 15, no. 6, pp. 569–579, 1993.

    Google Scholar 

  14. A. K. C. Wong and W. Liu. “Hypergraph representation for 3-D object model synthesis and scene interpretation”. Proc. the 2nd Workshop on Sensor Fusion and Environment Modeling (ICAR), Oxford, UK, 1991.

    Google Scholar 

  15. A. K. C. Wong and B. A. McArthur. “Random graph representation for 3-D object models”. SPIE Milestone Series, Model-Based Vision, vol. 72, pp. 229–238, 1991.

    Google Scholar 

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© 2004 Kluwer Academic Publishers

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Rong, L., Wong, A.K.C. (2004). 3D Modeling Based on Attributed Hypergrphs. In: Zhang, D.D., Kamel, M., Baciu, G. (eds) Integrated Image and Graphics Technologies. The International Series in Engineering and Computer Science, vol 762. Springer, Boston, MA. https://doi.org/10.1007/1-4020-7775-0_3

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  • DOI: https://doi.org/10.1007/1-4020-7775-0_3

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4020-7774-6

  • Online ISBN: 978-1-4020-7775-3

  • eBook Packages: Springer Book Archive

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