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Visual search for schematic emotional faces: angry faces are more than crosses
Daina S E Dickins1, Ottmar V Lipp
1a School of Psychology , The University of Queensland , Brisbane , QLD , Australia.
Cognition & Emotion
|July 9, 2013
Summary
The face in the crowd effect, faster angry face detection, may not stem from simple features. Specific facial element arrangements are crucial for this visual search advantage.
Area of Science:
- Cognitive Psychology
- Visual Perception
- Human-Computer Interaction
Background:
- The face in the crowd effect describes faster detection of angry versus happy faces in visual search.
- Previous research suggested this effect in schematic faces relies on perceptual features like inward-pointing lines, not emotional expressions.
Purpose of the Study:
- To investigate whether perceptual features alone, or specific facial configurations, drive the faster detection of angry schematic faces.
- To identify the critical elements and their spatial relationships necessary for the anger advantage in visual search.
Main Methods:
- Replication of preferential detection for stimuli with inward-pointing lines (Experiments 1-2).
- Testing schematic faces with critical anger-related features (inward brows, upturned mouth) with and without eyes/noses (Experiments 3-7).
- Manipulation of line thickness and contrast for key facial elements.
Main Results:
- Inward-pointing lines alone, within a surrounding circle, did not guarantee faster detection.
- Faster detection of anger emerged only when eyes or eyes and noses were included with correct first-order relational placement.
- Enhanced line contrast/thickness yielded a smaller anger advantage compared to complete schematic faces.
Conclusions:
- A prevalence of inward-pointing lines is insufficient to explain the angry schematic face detection advantage.
- The spatial configuration and presence of key facial elements (eyes, nose) are critical for the face in the crowd effect in schematic faces.
- Emotional expression is not the sole driver; structural facial information plays a significant role in rapid visual search.
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