L6: Face Perception, Depth Perception
Face Recognition and Perception
Overview of face production and recognition by components (RBC).
Definition of geons: Simple geometrical shapes used in object recognition.
Example: A brick having three parallel edges that are invariant to viewpoint changes.
Discussion of subordinate, basic, and superordinate levels of categorization.
Subordinate level: Highly specific recognition (e.g., recognizing a specific person's face).
Basic level: General category (e.g., identifying an animal as a dog).
Exploration of expertise in face recognition and the importance of metric properties in facial features.
Example: Celebrity recognition highlighted among varied faces.
Holistic processing of faces:
Unlike other objects, faces are recognized as wholes rather than parts.
Inverted Face Perception:
Difficulty in recognizing features of inverted faces, emphasizing holistic processing.
Demonstrated through class activity with disturbing vs. normal face images to illustrate this phenomenon.
Behavioral Studies in Face Recognition
Description of experiments using behavioral studies to analyze face recognition skills:
Training participants on unique features (e.g., different shaped noses) in fictional individuals.
Comparison of recognition performance between isolated features and features within context.
Result: Better memory performance with faces presented as wholes rather than individual features.
Neurophysiological Evidence
Study of neural activity related to face processing during surgical procedures:
Recording action potentials from various parts of the brain.
Discussion on face-selective areas with increased neural responses observed in these areas when subjects viewed faces compared to cars or other objects.
Discovery of Prosopagnosia: A condition characterized by the inability to recognize faces due to damage in the ventral stream of the cerebral cortex.
Evidence of brain damage and the impact on facial recognition abilities.
Fusiform Face Area (FFA)
Definition and location: Area responsible for face processing discovered through MRI studies by Nancy Kanwisher.
Method of assessing brain response:
Participants view faces vs. general objects and measurement through percent signal change in FFA.
Alternative explanations challenged:
Studies involving intact vs. scrambled faces revealed that the FFA responds more to complete faces, supporting the hypothesis of holistic processing.
FFA's selectivity tested against other biological stimuli (e.g., hands) revealed stronger responses for faces.
Depth Perception
Exploration of how the brain interprets 2D images to perceive depth through various cues:
Monocular cues (can work with one eye):
Linear perspective: Parallel lines converge in the distance.
Shape and texture gradients: Density and clarity decrease with distance.
Relative size: Comparing sizes of objects to determine depth based on expected sizes.
Interposition: Overlapping objects indicate positional closeness.
Shadows: The direction and shape of shadows provide information about 3D space and light sources.
Accommodation: The lens of the eye adjusts focus, indicating object distance.
Motion parallax: Nearby objects move quickly across the field of vision compared to distant ones.
Binocular cues (require both eyes):
Retinal disparity: Each eye perceives slightly different images due to their physical separation; greater disparity indicates closer objects.
Convergence: The eyes rotate inward when focusing on close objects; the degree of this rotation indicates distance from the viewer.
Course Overview and Fellowship Program Introduction
Importance of UX knowledge and experiences discussed, including UX design definitions and principles.
Role of UX in enhancing user interactions with products and ensuring good user experiences.
Presentation of the UX life cycle: Stages including empathizing, defining, ideation, prototyping, testing, and implementing.
Discussion on the significance of personal projects for the fellowship program:
Encouragement to develop user experience skills through practical application, including projects like app redesigns.
Emphasis on hands-on workshops to enhance skills in tools like Figma.
Importance of feedback and collaboration in project development, as well as the possibility to partner with fellow peers for collaborative learning.