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Updated: Mar 20, 2026

Automated Joint Space Detection Improves Bone Segmentation Accuracy
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Depth-dependent noise interference reveals scene-structure constraints on contour completion.

Rong Liu1, Yifeng Zhou1, Zili Liu2

  • 1State Key Laboratory of Eye Health, Hefei National Laboratory for Physical Science at the Microscale and Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230026, PR China.

Vision Research
|March 18, 2026
PubMed
Summary
This summary is machine-generated.

Visual contour completion relies on 3-D surface information, not just local image geometry. Noise on the same depth plane disrupts object perception more than noise displaced in depth.

Keywords:
Depth perceptionIllusory contoursKanizsa figuresPerceptual completionScene analysisStereopsis

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Area of Science:

  • Visual perception
  • Computational neuroscience
  • Cognitive psychology

Background:

  • Contour completion enables object recognition from incomplete visual input.
  • Debate exists on whether completion relies on local image cues or global scene analysis.
  • Existing models differ on the role of depth and surface layout in contour interpolation.

Purpose of the Study:

  • To test whether contour completion mechanisms are sensitive to three-dimensional (3-D) surface layout.
  • To differentiate between local, 2-D image-based models and global, scene-based models of contour completion.
  • To investigate the impact of luminance noise on contour completion when noise is coplanar versus depth-displaced.

Main Methods:

  • Utilized stereoscopic Kanizsa figures embedded in luminance noise.
  • Manipulated noise position relative to the figure (coplanar vs. depth-displaced).
  • Measured thin-fat shape discrimination thresholds as a measure of contour completion performance.

Main Results:

  • Shape discrimination thresholds were significantly higher (20%) for coplanar noise compared to depth-displaced noise.
  • This effect was independent of whether the figure was in front of or behind the noise plane.
  • A control experiment confirmed that the results were not due to between-eye noise sampling.

Conclusions:

  • Contour completion is influenced by 3-D surface assignment, challenging purely local, bottom-up models.
  • Luminance noise interferes with, rather than aids, contour completion when on the same depth surface.
  • The visual system evaluates scene structure, including depth, before interpolating contours, suggesting distinct processing for illusory contours and noise.