Skip to main content
SpringerLink
Log in

Integrating Recognition Paradigms in a Multiple-path Architecture

  • Conference paper
  • First Online:
Book cover Advances in Pattern Recognition — ICAPR 2001 (ICAPR 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2013))

Included in the following conference series:

Abstract

Four decades of intensive research in computer vision have lead to numerous computational paradigms. This fact is comprehensible since problems like object recognition or scene descriptions are of high complexity, have different aspects and can be attacked by processing various features. In this paper we propose an architecture that combines the advantages of different paradigms in pattern recognition. Voting and Bayesian networks provide a computational framework to integrate approaches to knowledge based and probabilistic reasoning as well as neural computations.

This work has been supported by the German Research Foundation within SFB 360.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. D.H. Ballard and C.M. Brown. Computer Vision. Prentice Hall, 1982.

    Google Scholar 

  2. C. Bauckhage, G.A. Fink, G. Heidemann, N. Jungclaus, F. Kummert, S. Posch, H. Ritter, G. Sagerer, and D. Schliiter. Towards an image understanding architec ture for a situated artificial communicator. Int. J. of Pattern Recognition and Image Analysis, 9(4):542-, 1999.

    Google Scholar 

  3. C. Bauckhage, F. Kummert, and G. Sagerer. Modeling and recognition of assembled objects. In Proc. IEEE Conf. IECON 98, pages 2051–2056, 1998.

    Google Scholar 

  4. E. Braun, G. Heidemann, H. Ritter, and G. Sagerer. A multi-directional multiple path recognition scheme for complex objects applied to the domain of a wooden toy kit. Pattern Recognition Letters, 20:1085–1091, 1999.

    Article  Google Scholar 

  5. S. Chakrabarty and J. Wolter. A Structure-Oriented Approach to Assembly Sequence Planning. IEEE Trans, on Robotics and Automation, 13(l):14–29, 1997.

    Article  Google Scholar 

  6. D. Comaniciu and P. Meer. Robust analysis of feature space: Color image segmenta tion. In Proc. IEEE Conf. CVPR, pages 750–755, 1997.

    Google Scholar 

  7. G. Heidemann. Ein flexibel einsetzbares Objekterkennungssystem auf der Basis neuronaler Netze. PhD thesis, Universitat Bielefeld, 1998.

    Google Scholar 

  8. G. Heidemann, F. Kummert, H. Ritter, and G. Sagerer. A hybrid object recognition architecture. In Proc. ICANN 96, pages 305–310, 1996.

    Google Scholar 

  9. A. Leonardis. Image Analysis Using Parametric Models. PhD thesis, University of Ljubljana, 1993.

    Google Scholar 

  10. A. Mafimann and S. Posch. Mask-oriented grouping operations in a contour-based approach. In Proc. IEEE 2nd Asian Conf. on Computer Vision, volume III, pages 58–61, 1995.

    Google Scholar 

  11. A. Mafimann, S. Posch, G. Sagerer, and D. Schliiter. Using markov random fields for contour-based grouping. In Proc. IEEE Int. Conf. on Image Processing, volume II, pages 207–210, 1997.

    Google Scholar 

  12. B. Parhami. Voting algorithm. IEEE Trans, on Reliability, 43(4):617–629, 1994.

    Article  Google Scholar 

  13. S. Posch and D. Schliiter. Perceptual grouping using markov random fields and cue integration of contour and region information. TR 98/10, SFB 360, Univ. of Bielefeld, 1998.

    Google Scholar 

  14. L. Priese and V. Rehrmann. A fast hybrid color segmentation method. In S. Poppel and H. Handels, editors, Mustererkennung 93, pages 297–304, 1993.

    Google Scholar 

  15. D. Reisfeld, H. Wolfson, and Y. Yeshurun. Context-free attentional operators: The generalized symmetry transform. Int. J. of Computer Vision, 14:119–130, 1995.

    Article  Google Scholar 

  16. D. Schliiter, F. Kummert, G. Sagerer, and S. Posch. Integration of regions and con tours for object recognition. In Proc. 15th Int. Conf. on Pattern Recognition, volume I, pages 944–947, 2000.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Technology, Bielefeld University, Germany

    G. Sagerer, C. Bauckhage, E. Braun, G. Heidemann, F. Kummert & H. Ritter

Authors
  1. G. Sagerer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. C. Bauckhage
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. E. Braun
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. G. Heidemann
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. F. Kummert
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. H. Ritter
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. D. Schliüter
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Exeter, EX4 4PT, Exeter, UK

    Sameer Singh

  2. Computational Intelligence Group, Tuiuti University of Parana, Curitiba, Brazil

    Nabeel Murshed

  3. Institute of Computer Aided Automation PRIP-Group 1832, Vienna University of Technology, Favoritenstr. 9/2/4, 1040, Wien, Austria

    Walter Kropatsch

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Sagerer, G. et al. (2001). Integrating Recognition Paradigms in a Multiple-path Architecture. In: Singh, S., Murshed, N., Kropatsch, W. (eds) Advances in Pattern Recognition — ICAPR 2001. ICAPR 2001. Lecture Notes in Computer Science, vol 2013. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44732-6_21

Download citation

  • DOI: https://doi.org/10.1007/3-540-44732-6_21

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41767-5

  • Online ISBN: 978-3-540-44732-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation