Optimal faces for gender and expression: a new technique for measuring dynamic templates used in face perception

Area of Science:

• Cognitive Psychology
• Neuroscience
• Computer Vision

Background:

• Facial expressions are crucial for human communication.
• Traditional face perception studies often use degraded stimuli to test recognition.
• A novel approach using rich, undegraded stimuli is needed to better understand internal representations.

Purpose of the Study:

• To introduce and validate a novel face perception technique.
• To measure optimal facial expression representations.
• To explore the internal representations of emotions, pain, and gender.

Main Methods:

• Participants used sliders to adjust 53 facial components (37 dynamic) to create optimal expressions.
• Stimuli included six emotions, pain, gender, and neutral conditions.
• Weighted sum morphing was used for stimulus generation.

Main Results:

• Distinct features were identified for specific expressions (e.g., anger, happiness).
• Happiness and surprise showed unique patterns compared to other emotions.
• Correlations were found between head size, feature scaling, eyebrow height, and eye openness with gender, surprise, and fear.

Conclusions:

• The developed method effectively measures optimal facial expressions.
• This technique provides a more direct assessment of internal facial expression representations.
• Findings contribute to understanding the perception and internal coding of facial cues.