New results in 3D views of polyhedron generation on view sphere with perspective projection

  • M. Frydler
  • W.S. Mokrzycki


This article concerns generating of 3D multiview model of convex polyhedron that are a complete representation of this polyhedron, according to viewing sphere with perspective projection. Those models are going to be used for visual identification based on them and a scene depth map. We give a new concept and an algorithm for face-depended generation of multi-face views. It does not require any preprocessing nor auxiliary mechanisms or complex calculations connected with them.

Key words

Object visual identification depth map 3D multiview precise model viewing sphere with perspective projection model completion state of viewing representation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

9 References

  1. [1]
    Connell J.H., Brady M. 1987: Generating and generalizing models of visual objects. AI, 31, 159–183.Google Scholar
  2. [2]
    Bowyer K.W., Dyer Ch.R. 1990: Aspect Graphs: An Introduction and Survey of Recent Results. SPIE, 1395.Google Scholar
  3. [3]
    Gigus Z., Canny J., Seidel R. 1991: Efficiently computing and representing aspect graph of polyhedral object. IEEE Trans. PAMI, 13(6), 542–551.Google Scholar
  4. [4]
    Zhank S., Sullivan G.D., Baker K.D. 1993: The automatic construction of a view-independent relational modelfor 3D object recognition. IEEE Trans. PAMI, 15(6). 531–544.Google Scholar
  5. [5]
    Leonardis A., Kovacic S., Pernus F. 1995: Recognition and pose determination of 3D objects using multiple views. Proc. CAIP'95, LNCS 970, Springer-verlag, Berlin, 778–783.Google Scholar
  6. [6]
    Suk T., Flusser J. 1995: The projective invariants for polygon. Proc. CAIP'95, LNCS 970, Springer-Verlag, 729–734.Google Scholar
  7. [7]
    Arbel T., Ferrie F.P. 1996: Informative views and sequential recognition. Proc. ECCV'96, Cambridge, UK, April, 469–481.Google Scholar
  8. [8]
    Hlavac V., Leonardis A., Werner T. 1996: Automatic selection of reference views for image-based scene representation. Proc. ECCV'96, Cambridge, UK, April, 526–535.Google Scholar
  9. [9]
    Arbel T., Ferrie F.P. 1997: Informative views and sequential recognition. Proc. ECCV'96, Cambridge, UK, April, 469–481.Google Scholar
  10. [10]
    Dąbkowska M., Mokrzycki W.S. 1997: Multi-view models of convex polyhedron. MG&V, 6(4), 419–450.Google Scholar
  11. [11]
    Madsen C.B., Christensen H.I. 1997: A viewpoint planning strategy for determining true angles on polyhedral objects by camera alignment. IEEE Trans. PAMI, 19(2), 158–163.Google Scholar
  12. [12]
    Shimshoni I., Ponce J. 1997: Finite-resolution aspect graphs of polyhedral objects.Google Scholar
  13. [13]
    Dąbkowska M., Mokrzycki W.S. 1998: A new view model of convex polyhedron with feature dependent view. MG&V, 7(l//2), (Proc. GKPO'98, Borki, Poland, 18–22 May), 325–334.Google Scholar
  14. [14]
    Dąbkowska M., Mokrzycki W.S. 1998: Conditions on models for object visual identification. Proc. ACS'98, Szczecin, 19–20 Nov.Google Scholar
  15. [15]
    Kovacic S., Leonardis A. 1998: Planning sequences of views for 3D object recognition and pose determination. PR, 31(10), 1407–1417.Google Scholar
  16. [16]
    Kowalczyk M., Mokrzycki W.S. 1999: Determining complete object's view model by joining one-view areas. Proc. ACS'99, Szczecin, 18–19 Nov., 68–72.Google Scholar
  17. [17]
    Kowalczyk M., Mokrzycki W.S. 2002: A new method of finding one-view areas and tight view sphere covering. Proc. ICCVG'02, Zakopane, Poland, Sept. 25–29, 443–449.Google Scholar
  18. [18]
    Kowalczyk M., Mokrzycki W.S. 2001: Obtaining complete 2 1/2D view representation of polyhedron using concept of seedling single-view area. CV &IU 91, 208–301.Google Scholar

Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  • M. Frydler
    • 1
  • W.S. Mokrzycki
    • 2
  1. 1.Institute of Mathematical MachinesWarsaw
  2. 2.Institute of Computer Science PASWarsaw

Personalised recommendations