Occlusion, Attention and Object Representations

  • Neill R. Taylor
  • Christo Panchev
  • Matthew Hartley
  • Stathis Kasderidis
  • John G. Taylor
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4131)


Occlusion is currently at the centre of analysis in machine vision. We present an approach to it that uses attention feedback to an occluded object to obtain its correct recognition. Various simulations are performed using a hierarchical visual attention feedback system, based on contrast gain (which we discuss as to its relation to possible hallucinations that could be caused by feedback). We then discuss implications of our results for object representations per se.


Firing Rate Inferior Frontal Gyrus Object Representation Lateral Geniculate Nucleus Dorsal Stream 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Neill R. Taylor
    • 1
  • Christo Panchev
    • 2
  • Matthew Hartley
    • 1
  • Stathis Kasderidis
    • 3
  • John G. Taylor
    • 1
  1. 1.Department of MathematicsKing’s College LondonLondonU.K.
  2. 2.School of Computing and TechnologySunderland UniversitySunderlandU.K.
  3. 3.Institute of Computer ScienceFoundation for Research & Technology HellasHeraklionGreece

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