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Facial expression recognition is most effective using horizontal spatial information, particularly from the mouth and eye regions. Vertical orientations significantly reduce accuracy in identifying emotions like anger, fear, happiness, and sadness.

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Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Computer Vision

Background:

  • Facial expression recognition relies on specific facial regions.
  • Horizontal spatial information may be crucial for identifying emotions.

Purpose of the Study:

  • To investigate the impact of spatial orientation on facial expression recognition accuracy.
  • To determine if pixel-level image differences explain performance variations.

Main Methods:

  • Applied orientation filters (bandwidth 23°) to face images at various angles (0° to 150°).
  • Tested recognition of four expressions (angry, fearful, happy, sad) under filtered and unfiltered conditions.
  • Measured recognition accuracy (normalized d') for each orientation.

Main Results:

  • Recognition performance was highest for horizontal (0°) and near-horizontal (-30°, 30°) orientations.
  • Accuracy systematically decreased as filter orientation approached vertical.
  • Mouth and eye regions were identified as key predictors of correct categorization.

Conclusions:

  • Young adults with normal vision optimally categorize facial expressions using horizontal spatial information.
  • Horizontal orientation captures essential facial feature changes across expressions.
  • Mouth and eye regions significantly contribute to facial expression categorization across all orientations.