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Attentional Selection for Object Recognition — A Gentle Way

  • Dirk Walther
  • Laurent Itti
  • Maximilian Riesenhuber
  • Tomaso Poggio
  • Christof Koch
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2525)

Abstract

Attentional selection of an object for recognition is often modeled using all-or-nothing switching of neuronal connection pathway from the attended region of the retinal input to the recognition units. However, there is little physiological evidence for such all-or-none modulation in early areas. We present a combined model for spatial attention and object recognition in which the recognition system monitors the entire visual field, but attentional modulation by as little as 20% at a high level is sufficient to recognize multiple objects. To determine the size and shape of the region to be modulated, a rough segmentation is performed, based on pre-attentive features already computed to guide attention. Testing with synthetic and natural stimuli demonstrates that our new approach to attentional selection for recognition yields encouraging results in addition to being biologically plausible.

Keywords

Object Recognition Recognition System Spatial Attention Attention System Attentional Modulation 
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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Dirk Walther
    • 1
  • Laurent Itti
    • 2
  • Maximilian Riesenhuber
    • 3
  • Tomaso Poggio
    • 3
  • Christof Koch
    • 1
  1. 1.Computation and Neural Systems ProgramCalifornia Institute of TechnologyPasadenaUSA
  2. 2.Computer Science DepartmentUniversity of Southern CaliforniaLos AngelesUSA
  3. 3.Center for Biological and Computational LearningMassachusetts Institute of TechnologyCambridgeUSA

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