Skip to main content

Chi-Square Goodness-of-Fit Test of 3D Point Correspondence for Model Similarity Measure and Analysis

  • Conference paper
Image and Video Retrieval (CIVR 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3568))

Included in the following conference series:

Abstract

Accurate and robust correspondence calculations are the pre-requisite step in many 3D model query and retrieval process. However, the correspondence problem is particularly difficult for 3D biomedical model surfaces, especially for roundish and approximate symmetric organs such as liver, stomach, kidney etc. In this paper, we define a new feature representation called the Neighborhood Relative Angle context Distribution (NRACD) for each vertex and, based upon it, we apply the Chi-Square Goodness-of-Fit test to establish 3D point correspondence. We further define the similarities between correspondence ready models by Chi-Square test statistic values. The experimental results demonstrate that this approach is efficient and robust for surface point matching and is particularly applicable to the retrieval and analysis of 3D deformable objects.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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. Chua, C.S., Jarvis, R.: 3D Free-Form Surface Registration and Object Recognition. Int’l J. Computer Vision 17, 77–99 (1996)

    Article  Google Scholar 

  2. Besl, P.J., McKay, N.D.: A Method for Registration of 3-D Shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence 14(2), 239–256 (1992)

    Article  Google Scholar 

  3. Kolonias, L., Tzovaras, D., Malassiotis, S., Strintzis, M.G.: Fast content-based search of VRML models based on shape descriptors. In: Proceedings of International Conference on Image Processing, vol. 2, pp. 133–136 (2001)

    Google Scholar 

  4. Rivilin, E., Weiss, I.: Local Invariants For Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(3), 226–238 (1995)

    Article  Google Scholar 

  5. Mokhtarian, F.: Sihouette-based object recognition with occlusion through curvature-scale space. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(5), 539–544 (1995)

    Article  Google Scholar 

  6. Osada, R., Funkhouser, T., Chazelle, B., Dobkin, D.: Matching 3D models with shape distributions. In: Proceedings of International Conference on Shape Modeling and Applications (SMI 2001), pp. 154–166 (2001)

    Google Scholar 

  7. Scalroff, S., Pentland, A.P.: Modal Matching for Correspondence and Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(6), 545–561 (1995)

    Article  Google Scholar 

  8. Carcassoni, M., Hancock, E.R.: Correspondence Matching with Modal Clusters. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(12), 1609–1615 (2003)

    Article  Google Scholar 

  9. Chua, C.S., Jarvis, R.: Point Signatures: A New Representation for 3D Object Recognition. International Journal of Computer Vision 25(1), 63–85 (1997)

    Article  Google Scholar 

  10. Dorai, C., Jain, A.: View organization and matching of free-form objects. In: Proceedings of International Symposium on Computer Vision, pp. 25–30 (1995)

    Google Scholar 

  11. Yamany, S.M., Farag, A.A.: Surface signatures: an orientation independent free-form surface representation scheme for the purpose of objects registration and matching. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(8), 1105–1120 (2002)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Feng, J., Ip, H.H.S. (2005). Chi-Square Goodness-of-Fit Test of 3D Point Correspondence for Model Similarity Measure and Analysis. In: Leow, WK., Lew, M.S., Chua, TS., Ma, WY., Chaisorn, L., Bakker, E.M. (eds) Image and Video Retrieval. CIVR 2005. Lecture Notes in Computer Science, vol 3568. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11526346_48

Download citation

  • DOI: https://doi.org/10.1007/11526346_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27858-0

  • Online ISBN: 978-3-540-31678-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics