FaReT

FaReT generates and manipulates parametric 3D facial stimuli for controlled studies of face perception.

Key Features:

• Database of Models: A validated database comprising 27 identity models and six expression pose models representing sadness, anger, happiness, disgust, fear, and surprise.
• Interpolation-based morphing: Generates sequences of renders by interpolating between multiple 3D models to produce morphing sequences across identities, expressions, or poses.
• Extrapolation and caricature generation: Performs extrapolation within face space to create anti-faces and caricatures.
• Dynamic animation from static images: Produces dynamic facial animations (videos) from static rendered images.
• Statistical and standardization tools: Computes average face models and standardizes sets of models so they vary only in selected facial shape features.
• Integration with experimental software: Integrates with PsychoPy to enable dynamic rendering of faces during experiments.

Scientific Applications:

• Controlled stimulus generation: Enables precise control of facial stimuli to reduce confounds in face perception experiments.
• Perception of identity and expression: Facilitates studies of perceptual judgments across morphing sequences, anti-faces, and caricatures.
• Population-level facial analysis: Supports computation of average face models for analyses of population trends in facial features.
• Temporal dynamics of facial perception: Provides dynamic stimuli for experiments on the temporal perception of expressions and identity changes.

Methodology:

FaReT expands MakeHuman’s capabilities by creating a validated database of 27 identity models and six expression pose models and implements software routines for interpolation, extrapolation, averaging, standardization, and conversion of static renders into dynamic facial animations.