Skip to main content
SpringerLink
Log in

Affine Invariant Harris-Bessel Interest Point Detector

  • Conference paper
Advances in Visual Computing (ISVC 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8888))

Included in the following conference series:

  • 2446 Accesses

Abstract

An affine invariant interest point detector named here as Harris-Bessel detector employing Bessel filters is proposed in this paper. The Harris-Bessel detector is applied on the images a well-known database in the literature. Our numerical results indicate that this detector is competitive and has better repeatability and localization measures than those of the affine invariant Harris-Laplace interest point detector. We also numerically demonstrate in this paper that the Harris-Bessel detector is affine invariant and is in average 450 times faster than the affine invariant Harris-Laplace detector for the images of the database.

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 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. Mahmoodi, S.: Edge Detection Filter based on Mumford-Shah Green Function. SIAM J. Imag. Sci. 5(1), 343–365 (2012)

    Article  MATH  MathSciNet  Google Scholar 

  2. Mahmoodi, S., Gunn, S.: Scale Space Smoothing, Image Feature Extraction and Bessel Filters. In: Heyden, A., Kahl, F. (eds.) SCIA 2011. LNCS, vol. 6688, pp. 625–634. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  3. Mikolajczyk, K., Schmid, C.: An Affine Invariant Interest Point Detector. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002, Part I. LNCS, vol. 2350, pp. 128–142. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  4. Schaffalitzky, F., Zisserman, A.: Multi-view Matching for Unordered Image Sets, or How Do I Organize My Holiday Snaps? In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002, Part I. LNCS, vol. 2350, pp. 414–431. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  5. Tuytelaars, T., van Gool, L.: Wide Baseline Stereo Matching based on Local Affinely Invariant Regions. In: The British Machine Vision Conference (BMVC 2000), pp. 412–425 (2000)

    Google Scholar 

  6. Matas, J., Chum, O., Urban, M., Pajdla, T.: Robust Wide Baseline Stereo from Maximally Stable Extremal Regions. In: The British Machine Vision Conference (BMVC 2002), pp. 384–393 (2002)

    Google Scholar 

  7. Kadir, T., Zisserman, A., Brady, M.: An Affine Invariant Salient Region Detector. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3021, pp. 228–241. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  8. Lowe, D.G.: Distinctive Image Features from Scale-Invariant Features. Intl. J. Comput. Vis. 60(2), 91–110 (2004)

    Article  Google Scholar 

  9. Mikolajczyk, K., Schmid, C.: A Performance Evaluation of Local Descriptors. IEEE Trans. Pattern Anal. Mach. Intel. 27(10), 1615–1630 (2005)

    Article  Google Scholar 

  10. Moreels, P., Perona, P.: Evaluation of Features Detectors and Descriptors based on 3D Objects. Intl. J. Comput. Vis. 73(3), 263–284 (2007)

    Article  Google Scholar 

  11. Gauglitz, S., Hollerer, T., Turk, M.: Evaluation of Interest Point Detectors and Feature Descriptors for Visual Tracking. Intl. J. Comput. Vis. 94, 335–360 (2011)

    Article  MATH  Google Scholar 

  12. Harris, C., Stephens, M.: A Combined Corner and Edge Detector. In: Alvey Vision Conference, pp. 147–151 (1988)

    Google Scholar 

  13. Mikolajczyk, K., Schmid, C.: Scale & Affine Invariant Interest Point Detectors. Intl. J. Comput. Vis. 60(1), 63–86 (2004)

    Article  Google Scholar 

  14. The link to this database is, http://www.robots.ox.ac.uk/~vgg/research/affine/index.html

Download references

Author information

Authors and Affiliations

  1. School of Electronic and Computer Science, University of Southampton, UK

    Sasan Mahmoodi & Nasim Saba

Authors
  1. Sasan Mahmoodi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nasim Saba
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada at Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. The University of Texas at Dallas, 75080, Richardson, TX, USA

    Ryan McMahan

  6. NextGen Interactions, 27604, Raleigh, NC, USA

    Jason Jerald

  7. Indiana University, 46202, Indianapolis, IN, USA

    Hui Zhang

  8. Microsoft Research, 1 Microsoft Way, 98052, Redmond, WA, USA

    Steven M. Drucker

  9. University of Delaware, 19716-2712, Newark, DE, USA

    Chandra Kambhamettu

  10. Intel Corp., 95054, Sata Clara, CA, USA

    Maha El Choubassi

  11. Computer Graphics and Interactive Media Lab, Department of Computer Science, University of Houston, 77004, Houston, TX, USA

    Zhigang Deng

  12. NVIDIA, 34788, Leesburg, FL, USA

    Mark Carlson

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Mahmoodi, S., Saba, N. (2014). Affine Invariant Harris-Bessel Interest Point Detector. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2014. Lecture Notes in Computer Science, vol 8888. Springer, Cham. https://doi.org/10.1007/978-3-319-14364-4_35

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-14364-4_35

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14363-7

  • Online ISBN: 978-3-319-14364-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation