Skip to main content
SpringerLink
Log in

A Spectral Graph Approach to Object Recognition

  • Chapter
Affective Computing and Intelligent Interaction

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 137))

  • 164 Accesses

Abstract

A spectral graph approach to 3D object recognitionfrom its 2D images is presented. Each image of an object is represented by a weighted graph and the feature is extracted by the eigenvectors of the affinity matrix of this graph. The proposed approach is validated on COIL data set. Experimental results show that this method is efficient for object recognition.

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 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
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. Pope, A.R.: Model-based Object Recognition, A Survey of Recent Research. Technical Report, University of Columbia (1994)

    Google Scholar 

  2. Veltkamp, R.C., Hagedoorn, M.: State of Art in Shape Matching. Technical Report UU-CS-1999-27, Universiteit Utrecht (1999)

    Google Scholar 

  3. Hagedoorn, M.: Pattern Matching Using Similarity Measures. PhD thesis, Universiteit Utrecht (2000)

    Google Scholar 

  4. Shi, J., Malik, J.: Motion Segmentation and Tracking Using Normalized Cut. IEEE Transaction on Pattern Recognition and Machine Intelligent 22(8), 888–905 (2000)

    Article  Google Scholar 

  5. Fowlkes, C., Belongie, S., Chung, F., Malik, J.: Specral Grouping Using the Nyström Method. IEEE Transaction on Pattern Recognition and Machine Intelligent 23(3), 861–869 (2004)

    Google Scholar 

  6. Huttenlocher, D., Klanderman, G., Rucklidge, W.: Comparing Images Using the Hausdorff Distance. IEEE Transaction on Pattern Recognition and Machine Intelligent 15(9), 850–863 (1993)

    Article  Google Scholar 

  7. Sclaroff, S., Pentland, A.: Modal Matching for Correspondence and Recognition. IEEE Transaction on Pattern Recognition and Machine Intelligent 17(6), 545–561 (1995)

    Article  Google Scholar 

  8. Belongie, S., Chung, F., Malik, J., Puzicha, J.: Shape Matching and Object Recogniton Using Shape Contexs. IEEE Transaction on Pattern Recognition and Machine Intelligent 24(24), 509–522 (2002)

    Article  Google Scholar 

  9. Lades, M., Vorbuggen, C., Buhmann, J., et al.: Distortion Invariant Object Recognition in teh Dynamic Link Architechture. IEEE Transaction on Computers 42(3), 300–311 (1993)

    Article  Google Scholar 

  10. Oren, M., Papageorgiou, C.,Sinha, P., Osuna, E., et al.: Pedestrian Detection Using Wavelet Templates. In: Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 191–199 (1997)

    Google Scholar 

  11. Ng, A.Y., Jordan, M.I., Weiss, Y.: On Specral Clustering: Analysis and an algorithms. In: Proc. Neural Information Processing System (NIPS), pp. 857–864 (2002)

    Google Scholar 

  12. He, X.F., Yan, S.C., Niyogi, P.: Face Recognition Using Laplacianface. IEEE Transaction on Pattern Recognition and Machine Intelligent 27(3), 328–340 (2005)

    Article  Google Scholar 

  13. Jain, V., Zhang, H.: Shape-based Retrieval of Articulated 3D Models Using Spectral Embbedings. In: Kim, M.-S., Shimada, K. (eds.) GMP 2006. LNCS, vol. 4077, pp. 299–312. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  14. Elad, A., Kimmel, R.: On Embedding Invariant Signature of Surfaces. IEEE Transaction on Pattern Recognition and Machine Intelligent 25(10), 1285–1295 (2003)

    Article  Google Scholar 

  15. Chung, F.R.K.: Spectral Graph Theory. Am. Math. Soc. (1997)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Electrical and Electronic Engineering, Shanghai University of Engineering Science, Shanghai, China

    Xiang Liu

  2. School of Computer Science, Fudan University, Shanghai, China

    Haishan Wu

Authors
  1. Xiang Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Haishan Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. National Kinmen Institute of Technology, Jinning Township 892, Kinmen, Taiwan R.O.C.

    Jia Luo

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag GmbH Berlin Heidelberg

About this chapter

Cite this chapter

Liu, X., Wu, H. (2012). A Spectral Graph Approach to Object Recognition. In: Luo, J. (eds) Affective Computing and Intelligent Interaction. Advances in Intelligent and Soft Computing, vol 137. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27866-2_33

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-27866-2_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27865-5

  • Online ISBN: 978-3-642-27866-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation