LECTURE SCHEDULE
 introduction
(slides)
levels of analysis in perception, course outline
VISUAL IMAGE FORMATION
 geometry
(slides)
(notes)
origins of spatial vision, visual angle, aperture, image projection, binocular disparity
 focus and blur
(slides)
(notes)
sampling, thin lens equation, depth of field, accommodation, aging and abnormal vision
 photoreceptors, color
(slides)
(notes)
spectra: emission, reflectance, absorptance; rods and cones, metamers, color displays, color blindness
EARLY VISION
 retina
(slides)
(notes)
spikes, color opponency, centersurround DOGs, crosscorrelation
 orientation selectivity
(slides)
(notes)
retinotopic maps, simple cells, Gabor models
 disparity tuned cells
(slides)
(notes)
complex cells in V1, monocular vs. binocular
 image motion 1
(slides)
(notes)
XYT, time dependent receptive fields, 3D Gabors and sine waves, normal velocity
 image motion 2
(slides)
(notes)
motion constraint equation, intersection of constraints, velocity tuned cells (MT)
3D SURFACE AND SPACE PERCEPTION
 egomotion
(slides)
(notes)
translation and direction of heading; rotation: VOR, smooth pursuit eye movements
 depth from blur, binocular steropsis
(slides)
(notes)
blur on slanted planes, Panum's fusional area, accommodationvergence conflict,
random dot stereograms
 shape from X: perspective, texture, shading
(slides)
(notes)
vanishing points, depth gradient and texture cues, slant & tilt; curvature, Lambert's law
 illumination and reflectance
(slides)
(notes)
shape from shading (linear & cloudy day), lightness & color constancy
MEASURING AND MODELLING PERFORMANCE
 psychophysics
(slides)
(notes)
psychometric curves, thresholds, contrast and disparity sensitivity
 maximum likelihood
(slides)
(notes)
examples of likelihoods, probability review

cue combinations, Bayesian models
(slides)
(notes)
priors, MAP, depth reversal ambiguity
LINEAR SYSTEMS THEORY
I will remove some of this material in Winter 2018 to reduce to 2 lectures.
 convolution
(slides)
(notes)
impulse response functions
 Fourier transform
(slides)
(notes)
examples, convolution theorem, inverse Fourier transform
filtering
(slides)
(notes)
white noise, low/band/high pass filters, Gaussian and Gabor,
2D Fourier transforms
AUDITORY IMAGE FORMATION
 sound 1
(slides)
(notes)
waves, intensity, dB, interaural differences
 sound 2
(slides)
(notes)
music and speech sounds, spectrograms
AUDITORY SYSTEM & SPATIAL HEARING
 head and ear
(slides)
(notes)
head and outer ear (HRIR, HRTF), inner ear and neural coding, critical bands
 auditory pathway in brain, source localization
(slides)
(notes)
from brain stem to cortex (A1), duplex theory, level and timing differences
 echolocation and recognition by bats and porpoises
(slides)
(notes)
constant frequency, frequency modulation, echos
[MAYBE DROP THIS IN 2018]
MID AND HIGHLEVEL VISION & AUDITION (TIME PERMITTING)
I will try to add some audition material to these lectures (and remove some stuff).
 attention
(slides)
(notes)
feature maps, saliency, visual search
 perceptual organization (slides)
(notes)
Gestalt laws of grouping, computational auditory scene analysis
 object recognition
Biederman, Marr, RSVP, machine learningbased models

Exercises
Exercises 1  image formation geometry
Exercises 2  focus
Exercises 3  color
Exercises 4  retina
Exercises 5  orientation: simple cells
Exercises 6  complex cells
Exercises 7  motion 1
Exercises 8  motion 2
Exercises 9  egomotion
Exercises 10  blur and stereopsis
Exercises 11  shape from texture
Exercises 12  illumination and reflectance
