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Mechanisms of Adaptive Spatial Integration in a Neural Model of Cortical Motion Processing

  • Stefan Ringbauer
  • Stephan Tschechne
  • Heiko Neumann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6593)

Abstract

In visual cortex information is processed along a cascade of neural mechanisms that pool activations from the surround with spatially increasing receptive fields. Watching a scenery of multiple moving objects leads to object boundaries on the retina defined by discontinuities in feature domains such as luminance or velocities. Spatial integration across the boundaries mixes distinct sources of input signals and leads to unreliable measurements. Previous work [6] proposed a luminance-gated motion integration mechanism, which does not account for the presence of discontinuities in other feature domains. Here, we propose a biologically inspired model that utilizes the low and intermediate stages of cortical motion processing, namely V1, MT and MSTl, to detect motion by locally adapting spatial integration fields depending on motion contrast. This mechanism generalizes the concept of bilateral filtering proposed for anisotropic smoothing in image restoration in computer vision.

Keywords

Motion Estimation Neural Modeling Motion Integration Diffusion 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Stefan Ringbauer
    • 1
  • Stephan Tschechne
    • 1
  • Heiko Neumann
    • 1
  1. 1.Faculty of Engineering and Computer Science Institute for Neural Information ProcessingUlm UniversityUlmGermany

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