A Neural Network Model of Visual Attention and Group Classification, and Its Performance in a Visual Search Task

  • Hayden Walles
  • Anthony Robins
  • Alistair Knott
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8272)


Humans can attend to and categorise objects individually, but also as groups. We present a computational model of how visual attention is allocated to single objects and groups of objects, and how single objects and groups are classified. We illustrate the model with a novel account of the role of stimulus similarity in visual search tasks, as identified by Duncan and Humphreys [1].


Spatial Frequency Visual Search Visual Attention Visual Feature Search Task 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Duncan, J., Humphreys, G.W.: Visual search and stimulus similarity. Psychological Review 91(3), 433–458 (1989)CrossRefGoogle Scholar
  2. 2.
    Nieder, A., Miller, E.K.: A parieto-frontal network for visual numerical information in the monkey. Proceedings of the National Acadamey of Sciences 101(19), 7457–7462 (2004)CrossRefGoogle Scholar
  3. 3.
    Izard, V., Dehaene-Lambertz, G., Dehaene, S.: Distinct cerebral pathways for object identity and number in human infants. PLoS Biology 6(2), 275–285 (2008)CrossRefGoogle Scholar
  4. 4.
    Walles, H., Knott, A., Robins, A.: A model of cardinality blindness in inferotemporal cortex. Biological Cybernetics 98(5), 427–437 (2008)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Treisman, A.M., Gelade, G.: A feature-integration theory of attention. Cognitive Psychology 12, 97–136 (1980)CrossRefGoogle Scholar
  6. 6.
    Moran, J., Desimone, R.: Selective attention gates visual processing in the extrastriate cortex. Science 229(4715), 782–784 (1985)CrossRefGoogle Scholar
  7. 7.
    Zhang, Y., Meyers, E., Bichot, N., Serre, T., Poggio, T., Desimone, R.: Object decoding with attention in inferior temporal cortex. Proceedings of the National Academy of Sciences of the USA 108(21), 8850–8855 (2011)CrossRefGoogle Scholar
  8. 8.
    Kadir, T., Brady, M.: Saliency, scale and image description. International Journal of Computer Vision 45(2), 83–105 (2001)CrossRefzbMATHGoogle Scholar
  9. 9.
    Kadir, T., Hobson, P., Brady, M.: From salient features to scene description. In: Workshop on Image Analysis for Multimedia Interactive Services (2005)Google Scholar
  10. 10.
    Riesenhuber, M., Poggio, T.: Hierarchical models of object recognition in cortex. Nature Neuroscience 2(11), 1019–1025 (1999)CrossRefGoogle Scholar
  11. 11.
    Fink, G., Halligan, P., Marshall, J., Frith, C., Frackowiak, R., Dolan, R.: Where in the brain does visual attention select the forest and the trees. Nature 382, 626–628 (1996)CrossRefGoogle Scholar
  12. 12.
    Flevaris, A., Bentin, S., Robertson, L.: Local or global? attentional selection of spatial frequencies binds shapes to hierarchical levels. Psychological Science 21(3), 424–431 (2010)CrossRefGoogle Scholar
  13. 13.
    Flevaris, A., Bentin, S., Robertson, L.: Attention to hierarchical level influences attentional selection of spatial scale. Journal of Experimental Psychology: Human Perception and Performance 37(1), 12–22 (2011)CrossRefGoogle Scholar
  14. 14.
    Logothetis, N.K., Sheinberg, D.L.: Visual object recognition. Annual Review of Neuroscience 19, 577–621 (1996)CrossRefGoogle Scholar
  15. 15.
    Itti, L., Koch, C.: A saliency-based search mechanism for overt and covert shifts of visual attention. Vision Research 40, 1489–1506 (2000)CrossRefGoogle Scholar
  16. 16.
    Moore, T., Armstrong, K.M.: Selective gating of visual signals by microstimulation of frontal cortex. Nature 421, 370–373 (2003)CrossRefGoogle Scholar
  17. 17.
    Sowden, P., Schyns, P.: Channel surfing in the visual brain. Trends in Cognitive Sciences 10(12), 538–545 (2006)CrossRefGoogle Scholar
  18. 18.
    Walles, H., Robins, A., Knott, A.: A neural network model of visual attention and object classification: technical details. Technical Report OUCS-2013-09, Dept of Computer Science, University of Otago (2013)Google Scholar
  19. 19.
    Treisman, A.: Perceptual grouping and attention in visual search for features and for objects. Journal of Experimental Psychology: HPP 8(2), 194–214 (1982)CrossRefGoogle Scholar
  20. 20.
    Treisman, A., Gormican, S.: Feature analysis in early vision: Evidence from search asymmetries. Psychological Review 95(1), 15–48 (1988)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Hayden Walles
    • 1
  • Anthony Robins
    • 1
  • Alistair Knott
    • 1
  1. 1.Dept of Computer ScienceUniversity of OtagoNew Zealand

Personalised recommendations