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Related Experiment Videos

Detecting connectedness

P R Roelfsema1, W Singer

  • 1Graduate School Neurosciences Amsterdam, The Netherlands Ophthalmic Research Institute (KNAW), Department of Visual System Analysis, Academic Medical Centre (UvA).

Cerebral Cortex (New York, N.Y. : 1991)
|August 29, 1998
PubMed
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The visual system uses connectedness to identify objects. A proposed "interaction skeleton" with recurrent connections helps neurons tag connected regions, though this may slow object recognition.

Area of Science:

  • Neuroscience
  • Computer Vision
  • Computational Neuroscience

Background:

  • Visual scenes contain multiple objects requiring segregation from background.
  • Connectedness is a key visual cue, implying connected regions belong to the same object.
  • The visual system must efficiently detect connectedness for figure-ground segmentation.

Purpose of the Study:

  • Review evidence for connectedness detection in figure-ground segmentation.
  • Propose physiological mechanisms for connectedness detection.
  • Investigate the role of recurrent connections and tagging mechanisms.

Main Methods:

  • Review of existing evidence on visual processing.
  • Theoretical modeling of neural networks.
  • Speculation on physiological mechanisms like recurrent connections.

Related Experiment Videos

Main Results:

  • Feedforward networks are insufficient for detecting connectedness.
  • A recurrent network, the "interaction skeleton," is proposed for labeling connected regions.
  • Tag-spreading via synchrony or rate modulation is a potential mechanism, but may impact recognition speed.

Conclusions:

  • Connectedness detection is crucial for visual object segmentation.
  • Recurrent connections and tagging mechanisms are likely involved.
  • The trade-off between accuracy and speed in object recognition is highlighted.