LECTURE SCHEDULE
 introduction
(slides)
(notes)
intro, course outline, origin of eyes and spatial vision
VISUAL IMAGE FORMATION
 geometry
(slides)
(notes)
visual angle, aperture, image projection, binocular disparity,
sampling, thin lens equation
 blur, photometry
(slides)
(notes)
depth of field, accommodation, aging and abnormal vision; shading, shadows, highlights, radiance
 photoreceptors, color
(slides)
(notes)
spectra: emission, reflectance, absorptance; rods and cones, metamers, color displays, color blindness
EARLY VISION PATHWAY
 retina
(slides)
(notes)
spikes, color opponency, centersurround DOGs, crosscorrelation
 orientation selectivity in V1
(slides)
(notes)
simple and complex cells, Gabor models
 retinotopic maps, binocularity in V1
(slides)
(notes)
retinal receptive field size and eccentricity, orientation columns, ocular dominance columns, binocular complex cells
 image motion
(slides)
(notes)
XYT, motion constraint equation, aperture problem, intersection of constraints (IOC), 3D Gabors, sketch of MT
3D SURFACE PERCEPTION
 depth from blur, binocular steropsis
(slides)
(notes)
blur and occlusions, slanted planes, tiltshift illusion; Panum's fusional area,
random dot stereograms, disparity space, accommodationvergence conflict
 egomotion and depth from parallax, eye movements
(slides)
(notes)
translation and rotation components; VOR, smooth pursuit, saccades
 shape from texture and shading
(slides)
(notes)
slant & tilt; texture size, density & foreshortening cues, diffuse vs. specular reflections
MEASURING AND MODELLING PERFORMANCE
 psychophysics
(slides)
(notes)
psychometric curves, thresholds, contrast and disparity sensitivity
 maximum likelihood method
(slides)
(notes)
examples of likelihoods, probability review

cue combinations, Bayesian models
(slides)
(notes)
priors, MAP, depth reversal ambiguity
LINEAR SYSTEMS THEORY & IMAGE FILTERING
The material in lectures 1416 gives another view of 'feature maps'. Its main purpose, though, will be to
provide the mathematical foundations for the audition 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
'BOTTOM UP' VERSUS 'TOP DOWN' PROCESSING
 attention
(slides)
(notes)
feature maps, saliency, visual search
 perceptual organization, object recognition (slides)
(notes)
Gestalt laws of grouping, midlevel vision, recognition: from Marr to machine learning
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

Exercises, Exams
Exercises 1
Exercises 2
Exercises 3
Exercises 4
Exercises 5
Exercises 6
Exercises 7
Midterm 1 with solutions
(PDF)
Exercises 8
Exercises 9
Exercises 10
Exercises 11
Exercises 12
Exercises 13
midterm 2 (with solutions and grading scheme)
(PDF)
posting for midterm 2 bonus (slight rewording of some questions)
(PDF)
Exercises 14
Exercises 15
Exercises 16
Exercises 17 and 18 (TODO in 2018!)
Exercises 19
Exercises 20
Exercises 21
Exercises 22
Exercises 23
final exam with solutions
(PDF)
