Advertisement

Detection of Interest Points on 3D Data: Extending the Harris Operator

  • Przemysław Głomb
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 57)

Summary

We consider a problem of interest point detection, i.e. location of points with standing out neighborhood, for a 3D mesh data. Our research is motivated by the need of general, robust characterization of a complexity of the mesh fragment, to be used for mesh segmentation and description methods. We analyze the reasoning behind traditional Harris operator for 2D images [4] and propose several possible extensions to 3D data. We investigate their performance on several sets of data obtained with laser digitizer.

Keywords

Interest Point Quadratic Surface Interest Operator Mesh Data Mesh Segmentation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Akagunduz, E., Ulusoy, I.: 3D object representation using transform and scale invariant 3D features. In: Proc. of the IEEE 11th International Conference on Computer Vision, pp. 1–8 (2007)Google Scholar
  2. 2.
    Bustos, B., Keim, D.A., Saupe, D., Schreck, T., Vranić, D.V.: Feature-based similarity search in 3D object databases. ACM Computing Surveys 37(4), 345–387 (2005)CrossRefGoogle Scholar
  3. 3.
    Chen, H., Bhanu, B.: 3D free-form object recognition in range images using local surface patches. Pattern Recognition Letters 28, 1252–1262 (2007)CrossRefGoogle Scholar
  4. 4.
    Harris, C., Stephens, M.: A combined corner and edge detector. In: Proc. of the 4th Alvey Vision Conference, pp. 147–151 (1988)Google Scholar
  5. 5.
    Katz, S., Leifman, G., Tal, A.: Mesh segmentation using feature point and core extraction. The Visual Computer 21(8-10), 649–658 (2005)CrossRefGoogle Scholar
  6. 6.
    Meek, D.S., Walton, D.J.: On surface normal and gaussian curvature approximations given data sampled from a smooth surface. Computer Aided Geometric Design 17, 521–543 (2000)CrossRefzbMATHMathSciNetGoogle Scholar
  7. 7.
    Mikolajczyk, K., Tuytelaars, T., Schmid, C., Zisserman, A., Matas, J., Schaffalitzky, F., Kadir, T., van Gool, L.: A comparison of affine region detectors. International Journal of Computer Vision 65(1/2), 43–72 (2005)CrossRefGoogle Scholar
  8. 8.
    Moreels, P., Perona, P.: Evaluation of features detectors and descriptors based on 3D objects. International Journal of Computer Vision 73(3), 263–284 (2007)CrossRefGoogle Scholar
  9. 9.
    Schmid, C., Mohr, R., Bauckhage, C.: Evaluation of interest point detectors. International Journal of Computer Vision 37(2), 151–172 (2000)CrossRefzbMATHGoogle Scholar
  10. 10.
    Vincent, E., Laganiére, R.: Detecting and matching feature points. Journal of Visual Communication and Image Representation 16, 38–54 (2005)CrossRefGoogle Scholar
  11. 11.
    Zhou, Y., Huang, Z.: Decomposing polygon meshes by means of critical points. In: Proc. of the 10th International Multimedia Modelling Conference, pp. 187–195 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Przemysław Głomb
    • 1
  1. 1.Institute of Theoretical and Applied Informatics of PASGliwicePoland

Personalised recommendations