Context-Free Detection of Events

  • Benedikt Kaiser
  • Gunther Heidemann
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4522)


The detection of basic events such as turning points in object trajectories is an important low-level task of image sequence analysis. We propose extending the SUSAN algorithm to the spatio-temporal domain for a context-free detection of salient events, which can be used as a starting point for further motion analysis. While in the static 2D-case SUSAN returns a map indicating edges and corners, we obtain in a straight forward extension of SUSAN a 2D+1D saliency map indicating edges and corners in both space and time. Since the mixture of spatial and temporal structures is still unsatisfying, we propose a modification better suited for event analysis.


Image Retrieval Machine Intelligence Interest Point Sudden Appearance Pattern Recognition Letter 
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.


  1. 1.
    Martin, D.R., Fowlkes, C.C., Makik, J.: Learning to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture Cues. IEEE Trans. on Pattern Analysis and Machine Intelligence vol. 26(1) (2004)Google Scholar
  2. 2.
    Reisfeld, D., Wolfson, H., Yeshurun, Y.: Context-Free Attentional Operators: The Generalized Symmetry Transform. Int. J. of Computer Vision 14, 119–130 (1995)CrossRefGoogle Scholar
  3. 3.
    Goldberger, J., Greenspan, H.: Context-Based Segmentation of Image Sequences. IEEE Trans. on Pattern Analysis and Machine Intelligence 28(3), 463–468 (2006)CrossRefGoogle Scholar
  4. 4.
    Harris, C., Stephens, M.: A Combined Corner and Edge Detector. In: Proc. 4th Alvey Vision Conf., pp. 147–151 (1988)Google Scholar
  5. 5.
    Laptev, I., Lindeberg, T.: Space-time Interest Points. In: Proc. ICCV 2003. pp. 432–439 (2003)Google Scholar
  6. 6.
    Tian, Q., Sebe, N., Lew, M.S., Loupias, E., Huang, T.S.: Image Retrieval Using Wavelet-Based Salient Points. J. of Electronic Imaging 10(4), 835–849 (2001)CrossRefGoogle Scholar
  7. 7.
    Backer, G., Mertsching, B., Bollmann, M.: Data- and Model-Driven Gaze Control for an Active-Vision System. IEEE Trans. on Pattern Analysis and Machine Intelligence 23(12), 1415–1429 (2001)CrossRefGoogle Scholar
  8. 8.
    Heidemann, G.: Focus-of-Attention from Local Color Symmetries. IEEE Trans. on Pattern Analysis and Machine Intelligence 26(7), 817–830 (2004)CrossRefGoogle Scholar
  9. 9.
    Privitera, C.M., Stark, L.W.: Algorithms for Defining Visual Regions-of-Interest: Comparison with Eye Fixations. IEEE Trans. on Pattern Analysis and Machine Intelligence 22(9), 970–982 (2000)CrossRefGoogle Scholar
  10. 10.
    Moravec, H.P.: Towards Automatic Visual Obstacle Avoidance. In: Proc. 5th Int’l Joint Conf. on Artificial Intelligence, Cambridge, Massachusetts, USA, pp. 584–587 (1977)Google Scholar
  11. 11.
    Schmid, C., Mohr, R.: Local Grayvalue Invariants for Image Retrieval. IEEE Trans. on Pattern Analysis and Machine Intelligence 19(5), 530–535 (1997)CrossRefGoogle Scholar
  12. 12.
    Smith, S., Brady, J.: SUSAN – A New Approach to Low Level Image Processing. Int. J. of Computer Vision 23(1), 45–78 (1997)CrossRefGoogle Scholar
  13. 13.
    Zheng, Z., Wang, H., Teoh, W.: Analysis of Gray Level Corner Detection. Pattern Recognition Letters 20, 149–162 (1999)CrossRefzbMATHGoogle Scholar
  14. 14.
    Zitová, B., Kautsky, J., Peters, G., Flusser, J.: Robust detection of significant points in multiframe images. Pattern Recognition Letters 20(2), 199–206 (1999)CrossRefzbMATHGoogle Scholar
  15. 15.
    Heidemann, G., Kaiser, B., Bax, I., Bekel, H., Ritter, H.: Spatiotemporal Events and Action Sequences. Technical report, Bielefeld Univ., Neuroinformatics Group (2005)Google Scholar
  16. 16.
    Heidemann, G.: Unsupervised image categorization. Image and Vision Computing 23, 861–876 (2005)CrossRefGoogle Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Benedikt Kaiser
    • 1
  • Gunther Heidemann
    • 2
  1. 1.University of Karlsruhe, Institute for Process Control and Robotics, Building 40.28, Kaiserstr. 12, D-76128 KarlsruheGermany
  2. 2.University of Stuttgart, Intelligent Systems Group, Universitätsstr. 38, D-70569 StuttgartGermany

Personalised recommendations