A biologically inspired model for occluded patterns

  • Authors:

  • Mohammad Saifullah

  • Affiliations:

  • Department of Computer and Information Science, Linkoping University, Sweden

  • Venue:
  • ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part I
  • Year:
  • 2011

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Abstract

In this paper a biologically-inspired model for partly occluded patterns is proposed. The model is based on the hypothesis that in human visual system occluding patterns play a key role in recognition as well as in reconstructing internal representation for a pattern's occluding parts. The proposed model is realized with a bidirectional hierarchical neural network. In this network top-down cues, generated by direct connections from the lower to higher levels of hierarchy, interact with the bottom-up information, generated from the un-occluded parts, to recognize occluded patterns. Moreover, positional cues of the occluded as well as occluding patterns, that are computed separately but in the same network, modulate the top-down and bottom-up processing to reconstruct the occluded patterns. Simulation results support the presented hypothesis as well as effectiveness of the model in providing a solution to recognition of occluded patterns. The behavior of the model is in accordance to the known human behavior on the occluded patterns.