Early Clustering Approach towards Modeling of Bottom-Up Visual Attention

1. Wolfe, J.M., Horowitz, T.S.: What attributes guide the deployment of visual attention and how do they do it? Nature Reviews, Neuroscience 5, 1–7 (2004)

   Article  Google Scholar 

2. Neri, P.: Attentional effects on sensory tuning for single-feature detection and double-feature conjunction. In: Vision Research, pp. 3053–3064 (2004)

   Google Scholar 

3. Koch, C.: Biophysics of Computation. Oxford University Press, New York (1999)

   Google Scholar 

4. Weaver, B., Lupianez, J., Watson, F.L.: The effects of practice on object-based, location-based, and static-display inhibition of return. Perception & Psychophysics 60, 993–1003 (1998)

   Article  Google Scholar 

5. Itti, L., Koch, U., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. Transactions on Pattern Analysis and Machine Intelligence 20, 1254–1259 (1998)

   Article  Google Scholar 

6. Itti, L., Koch, C.: A saliency based search mechanism for overt and covert shifts of visual attention. In: Vision Research, pp. 1489–1506 (2000)

   Google Scholar 

7. Park, S.J., Shin, J.K., Lee, M.: Biologically inspired saliency map model for bottom-up visual attention. In: Bülthoff, H.H., Lee, S.-W., Poggio, T.A., Wallraven, C. (eds.) BMCV 2002. LNCS, vol. 2525, pp. 418–426. Springer, Heidelberg (2002)

   Chapter  Google Scholar 

8. Heidemann, G., Rae, R., Bekel, H., Bax, I., Ritter, H.: Integrating context-free and context-dependant attentional mechanisms for gestural object reference. In: Crowley, J.L., Piater, J.H., Vincze, M., Paletta, L. (eds.) ICVS 2003. LNCS, vol. 2626, pp. 22–33. Springer, Heidelberg (2003)

   Chapter  Google Scholar 

9. Backer, G., Mertsching, B., Bollmann, M.: Data- and model-driven gaze control for an active-vision system. Transactions on Pattern Analysis and Machine Intelligence 23, 1415–1429 (2001)

   Article  Google Scholar 

10. Meur, O.L., Callet, P.L., Barba, D., Thoreau, D.: A coherent computational approach to model bottom-up visual attention. Transactions on Pattern Analysis and Machine Intelligence 28, 802–817 (2006)

    Article  Google Scholar 

11. Sun, Y., Fischer, R.: Object-based visual attention for computer vision. Artificial Intelligence 146, 77–123 (2003)

    Article  MathSciNet  MATH  Google Scholar 

12. Avraham, T., Lindenbaum, M.: Esaliency - a stochastic attention model incorporating similarity information and knowledge-based preferences. In: WRUPKV-ECCV 2006, Graz (2006)

    Google Scholar 

13. Aziz, M.Z., Mertsching, B.: Color segmentation for a region-based attention model. In: Workshop Farbbildverarbeitung (FWS 2006), Ilmenau, Germany, pp. 74–83 (2006)

    Google Scholar 

14. Aziz, M.Z., Mertsching, B.: Fast and robust generation of feature maps for region-based visual attention. Transactions on Image Processing 17, 633–644 (2008)

    Article  MathSciNet  Google Scholar 

15. Kutter, O., Hilker, C., Simon, A., Mertsching, B.: Modeling and simulating mobile robots environments. In: 3rd International Conference on Computer Graphics Theory and Applications (GRAPP 2008), Funchal, Portugal (2008)

    Google Scholar 

Download references