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Vision • Photoreceptor cells • Rod & Cone cells • Bipolar Cells • Connect in between • Ganglion Cells • Go to the brain Vision LGN V1 V1 LGN ganglion cells optic chiasm: where the ganglion cells cross so the left side of each eye goes to the right side of the brain, and vice versa. The Eye rod cells: cone cells: • periphery • movement • black and white • fovea (center) • detail • color 500 nm light blue green red (broad tuning) cone firing The Eye rod cells: cone cells: • periphery • movement • black and white • fovea (center) • detail • color blue green red (broad tuning) cone firing The Eye rod cells: cone cells: • periphery • movement • black and white • fovea (center) • detail • color bipolar & horizontal cells b b b b h h h h h h The Eye rod cells: cone cells: • periphery • movement • black and white • fovea (center) • detail • color bipolar & horizontal cells • lateral inhibition + - - - - - - - + + + + Lateral Inhibition 9 9 9 9 1 1 1 1 1 9 9 9 9 - 0 + 0 - Lateral Inhibition 9 9 9 9 1 1 1 1 1 9 9 9 9 0 - 0 + 4 - Lateral Inhibition 9 9 9 9 1 1 1 1 1 9 9 9 9 0 0 - 4 + -4 - Lateral Inhibition 9 9 9 9 1 1 1 1 1 9 9 9 9 0 0 4 - -4 + 0 - Lateral Inhibition 9 9 9 9 1 1 1 1 1 9 9 9 9 0 0 4 -4 0 0 0 -4 4 - 0 + 0 - The Eye rod cells: cone cells: • periphery • movement • black and white • fovea (center) • detail • color bipolar & horizontal cells • lateral inhibition • edge detection ganglion cells Bipolar cells front view The Eye rod cells: cone cells: • periphery • movement • black and white • fovea (center) • detail • color bipolar & horizontal cells receptive field • lateral inhibition • edge detection ganglion cells - + The Eye rod cells: cone cells: • periphery • movement • black and white • fovea (center) • detail • color bipolar & horizontal cells receptive field • lateral inhibition • edge detection ganglion cells • center/surround - + Center-Surround (Blob detector) firing frequency + light position time Center-Surround firing frequency + light position time Center-Surround firing frequency + light position time Center-Surround firing frequency + light position time Center-Surround firing frequency + light position time Center-Surround firing frequency + light position time Center-Surround firing frequency + light position time Center-Surround firing frequency + light position time Center-Surround firing frequency + light position time Center-Surround How’s it done? Difference of Gaussians (Mexican hat) light position Distributed Visual Representation • Different cells respond to different properties, such as bars of light at different orientations (i.e. the simple cells in V1). • Different areas of the brain are dedicated to processing form and location information (i.e. the “what” and “where” systems, in the temporal and parietal lobes, respectively) How does your brain put it together again? Binding Problem •“red” neurons •“blue” neurons •“square” neurons •“circle” neurons •“upper-right” •“lower-left” How do we know which feature goes with which object? Binding Problem •“red” neurons •“blue” neurons •“square” neurons •“circle” neurons •“upper-right” •“lower-left” How do we know which feature goes with which object? Binding Problem •“red” neurons •“blue” neurons •“square” neurons •“circle” neurons •“upper-right” •“lower-left” How do we know which feature goes with which object? The Computations of Human Vision Visual system must calculate Object color (Mostly known) Object shape Begin with edges (Known) Find blobs (Known) How edges/blobs combine to form objects (Mostly Unknown) Object movement (Mostly known) The Computational System of Vision Object Motion Marr’s levels: Computational Determine motion Representation & Algorithm Mostly known (but not by us!) Physical Implementation Neurons in the eye and brain Hierarchical processing High-level processing Examples Biological motion Object motion Optic flow Low-level processing Retinal motion Hierarchical processing High-level processing/High complexity … Superior Temporal Sulcus (STS) Medial Superior Temporal area (MST) Middle Temporal Area (MT/V5) Primary visual cortex (V1) Lateral Geniculate Nucleus (LGN) Retina • • • • Biological motion Object motion Optic flow Retinal motion Low-level processing/Low complexity Limits of motion perception We can’t perceive motion that is either too FAST or too SLOW. Vertical position Upward motion time Downward motion Apparent Motion • “Broken” motion • Stimulus flashing at different positions at different times Flicker Rate Very fast Somewhat fast Phi Movement Optimal Beta Movement Very slow Phi Movement/Motion • A “pure sense” of motion without seeing the intermediate steps • No link-up/fill-in Beta Movement/Motion • Perceptually linking up the frames • Smooth motion • Motion picture technology The Correspondence Problem ? The Correspondence Problem • How do we figure out which frame-2 dot should match with each of the frame-1 dots? Frame 1 Frame 2 ? The Wagon-wheel illusion t1 Perceived direction Real direction Perception: Reality: Slow CW Slow CW Ambiguous Medium CW t2 Slow CCW Fast CW The Aperture Problem • Following from the correspondence problem • When the line’s motion is viewed through an aperture, how do we figure out the “correct” motion? The Aperture Problem • There are “infinitely many” possibilities. … or or … • The Aperture Problem: a solution It’s not a problem: if the line has texture, or if the line has endings, or if the line is not straight, or… …as long as there’s a UNIQUE POINT! The Barberpole Illusion • Perceived motion direction is parallel to the orientation of the rectangle • Can be explained by “Unique-point heuristic” Perceived direction – Unique points are assumed to be on the long edge Optic Flow Optic Flow • Background scene flows as our we move • We process motion signals at different locations to understand the optic flow pattern • Optic flow is useful for inferring the direction of self-motion Optic Flow • Most studied flow patterns Translational - object movement, eye movement, etc. Rotational (or circular) - head movement, eye movement, etc. Radial (expansion/contraction) - motion in depth, self-motion, etc. – They can represent most of the optic flows we see – Computationally, rotational and radial flows are more complex than translational ones Retina Motion vs REAL Motion • Motion constancy – try tracking your moving finger! • Retinal motion is combined with eyemovement to generate motion percepts Motion in depth • Retina is flat Motion signals are only 2D • How can we know when something is moving towards/away from us? • Try moving your finger towards your nose Motion in depth • The brain combines motion signals from the two eyes to infer motion in depth Left eye Right eye Far Right eye: leftward +) Left eye: rightward Approaching Right eye: rightward +) Left eye: leftward Receding Close Biological Motion • We are very sensitive to biological motion • An analogy: Face in object perception • Appears to require – extremely complex computations – a special motion processing mechanism Motion Blindness • Patient LM – Certain brain areas damaged through stroke – Almost all cognitive functions were intact except for MOTION perception – She reported • What she saw when pouring coffee into a cup: appears frozen like a glacier, does not perceive the fluid rising, often spills or overflows it • “When I'm looking at the car first it seems far away, but then when I want to cross the road suddenly the car is very near” – YouTube: http://www.youtube.com/watch?v=B47Js1MtT4w Title: Akinetopsia (4:01) (a reproduced documentary for a class project)