CN
530: Neural and Computational Models of Vision
Course Syllabus, Fall 2009
Arash Yazdanbakhsh Teaching Fellow: Stefan Berteau
Office:
Office hours: Tuesdays,
11:00 AM – 1 PM, Office Hours:
To be determined in the
first class,
by appointment
A r a s h _ Y a z d a n b a k h s h @ s t e f a n . b e r t e a u @ g m a i l . c o m
h m s . h
a r v a r d . e d u
Overview: This course explores the psychological,
biological, mathematical and computational foundations of visual perception. Lectures
and readings combine with simulation and essay assignments to provide an
intensive and self-contained examination of core issues in early and middle
visual processing. Mathematically specified neural and computational models
elucidate the structure and dynamics of the mammalian visual system. The course
elucidates the psychophysics and physiology of mammalian vision, both as a
means of better understanding our own human intelligence, and as a foundation
for tomorrow’s machine vision architectures and algorithms. While some of the
models developed in recent years at
Meeting
times: Lectures will be
given on Tuesdays, beginning on September 8 and ending on
December 8, from 1:00-4:00 PM in Room B03 (B02 in case of availability) of 677 Beacon Street. An additional hour-long discussion period at
a different time will be arranged.
SUMMARY OF WEEKLY TOPICS
Week 1
Sep
8 Fundamental problems of
vision
Week 2 Sep 15 Shunting competitive networks and
representation in early vision
Week 3 Sep 22 Early
visual pathways
Week 4 Sep 29 Contrast
sensitivity and spatial scales
Week 5 Oct 6 Brightness
and lightness perception
Oct 13 NO
CLASS – University Monday schedule
Week 6 Oct 20
Parallel visual pathways
Week 7 Oct 27 Boundary
detection, completion, and sharpening
Week 8 Nov 3 The
phenomena of motion perception
Week 9 Nov 10 Models
of motion perception
Week 10 Nov 17 An
in-class examination, covering topics in the readings and lectures
from
the first 9 weeks, will be given during this class period.
Week 11
Nov 24 Approaches to textural
segmentation and grouping
Week 12 Dec 1 Binocular
vision
Week 13 Dec
8 Visual
attention
COURSE
REQUIREMENTS AND GRADES:
All students must complete four
simulation assignments, an in-class
midterm examination, and a written
final course report. Students also participate in weekly discussion meetings and are also required to turn in weekly
updates of a personal journal, as
described below. Course grades will be based on a conventional 100 point scale,
with A = 93 or better, A-minus = 90-92, etc. The weighting of assignments and
exams on the final grade is:
40% Four simulation assignments; each counts for
10% of the total credit for the course
30% In-class midterm examination (Week 10)
10% Final report
10% Discussion meeting participation
10% Professional
growth, as documented in a personal
journal
ASSIGNMENT
DUE DATES: Printed hardcopy is
the means of submission for all assignments. Simulation assignments and the
final report should be turned in at my office; assignments may be placed under
my door if I am not in. Please do not even THINK of asking me if it
is “okay” to submit an assignment late; it is not okay, not even by a few
minutes, and your assignment grade will suffer. Please assume that
printers will not work in the hours just before an assignment is due, that the
subway will run late, and so forth. Then, get your assignments turned in on
time anyway. Simulation assignments
and the final report are due by 3:00 PM on the following dates:
Simulation Assignment 1 Wednesday, Sep
23
Simulation Assignment 2 Wednesday, Oct 7
Simulation Assignment 3 Wednesday, Oct 28
Simulation Assignment 4 Wednesday, Nov
4
Final report Wednesday, Dec 16
Personal journal units are turned in weekly at the start of lectures. The first journal unit is due on Week
2, Sep 15. No journal unit is turned in on Oct 13 (University Monday Schedule)
or Nov 17 (midterm exam). The last journal unit is due on Dec. 8, making a
total of 11 units for the semester. Journal units may not be turned in late,
absent a documented medical excuse or life crisis.
Choose a
standard citation style and stick to it throughout the semester. You are free
to choose a style from one of your readings.
Each journal unit can be
up to three single-sided pages long – no more – using 1.5 line spacing between
lines and a legible font of at least 11pt size. In the upper right hand part of the first page of each journal
unit, write your name, the date that you turn the unit in, and “Unit N,” where
N is an integer from 1 to 11, corresponding to the number of that unit – which will not, in general, correspond to the number of
that week in the course.
Journal units must be
turned in at the start of class; I will take a dim view of
any student arriving late “because” that student needed extra minutes to finish
a journal assignment. Electronic submission of journal units is not an option,
except in extreme circumstances and with prior
permission from me. Please note that the effect on your grade of turning in
less than 11 journal units is almost certain to be noticeable: With each unit
accounting for nearly 1% of your total course grade, you will slip quickly from
(say) an A to an A-minus to a B-plus if you fail to turn in all 11. At the end
of the semester, I will review all of your journal entries for evidence of professional
growth, and possibly adjust your final grade point credits for the journal units by one or two points
(plus or minus, on a 100 point scale) based on this evidence.
Journals will be graded on
a “check” system, with each unit that is turned in on time earning a default of
“full” credit. I will not in general return journal units to you throughout the
semester, although I will be happy to discuss your journal during office hours
or by appointment. I will contact individuals directly if performance on
journal units deviates significantly from expected quality. I will often share
with the class ideas raised by individuals in their journals, and my reaction
to those points. The student’s identity will not be disclosed in these cases.
SIMULATION
ASSIGNMENT SUBMISSION, CONTENTS, AND FORMAT: The following guidelines apply.
1)
Cover sheet and anonymous grading:
Simulation assignments are to be graded anonymously. Turn in all simulation
assignments on 8 1/2” x 11” paper, and include ONLY your name, the course number, the date of submission, and the
words “CN530 Simulation Assignment N” (N = assignment number) on the upper right corner of the first page. Do not include any other information on the first page. If you are printing on both sides of the
paper, please print the first page separately so that there is no information
on the back side. These assignments are to be evaluated based on their content
only, so do not include information about your identity on any pages other than the first “cover sheet.”
2)
Length: Simulation
reports are expected to be brief. “Brief” means up to 2500 words for total
report text; simulation assignments will have additional pages for graphs and
diagrams. Software such as MSWord or LaTeX typically generates approximately 250
to 350 words per page, depending on settings for margins and line spacing. You should use 1.5 line spacing. Assignments whose fonts are smaller than 12
point, or that are single spaced, or that do not have 1” margins on sides and
bottoms, or that are not paginated will be returned to be properly reformatted
before they are graded. There will be a grading penalty for such deviations
from basic formatting requirements.
3)
Required sections and headers: All simulation assignments must include an abstract,
a short introduction, a short concluding section, and a “References” section. Abstracts should be approximately
200-300 words and should be specific
enough in their wording that a person reading only the abstract should come
away with a reasonably accurate idea of the content of your report. The
simulation and final reports must begin
with a short title that is descriptive of the content of the report. Possible titles do not include “simulation assignment 2”
but do include concise phrases like “simulations of brightness filling-in by
boundary-gated diffusion.” Your introductions should be sufficiently
self-contained to make sense to someone besides me or the course teaching
assistant. That is, you should not use jargon or assume familiarity with terms not expected to be in
general use in the field of vision research. For simulation assignments you
must explicitly label which part of which
question (e.g. 3a or 1b) a given section of your report addresses.
4) Legibility: All assignments must be produced on a word-processor. Clear
handwritten annotation is acceptable in small amounts, including correction of
typos, insertion of notation in mathematical equations, graphs, or figures. Assignments containing extensive
handwritten passages will be returned ungraded. You are expected to adhere to reasonable stylistic
conventions (such as the use of margins, references, headings and so forth).
For many of you English is not a first language, and there is no expectation
that you become accomplished authors overnight. The above refers to basic
requirements that can and should be met by all: Make sure that your sentences
contain verbs and end with a period. If you use a pronoun in a sentence, make
sure its antecedent is unambiguous. Do not employ slang. Check your writing for
clarity; do not expect to be given “the benefit of the doubt” if your words are ambiguous or vague.
5)
Graphical plots: Describe simulation results in words, with
the help of graphical plots whenever possible. Include
scales on all axes, and explicitly label
the quantities being plotted on all axes. Each plot on your page should be
treated as a “figure” in a publication. That means there should be a label and
a caption (e.g. “Figure 7: Results of center-surround filtering of step
functions,” followed by some descriptive text. It also means that the body of
your report should refer to specific figures by their figure numbers. Your
plots can be generated by computer or by hand, or in combination. (For example, you may be
able to plot locations of points by computer, but prefer to label the scale of
axes by hand.) Be judicious
in choosing which outputs to display overall. Choose figures that contribute
materially to the reader’s understanding (by showing crucial “before and after”
or “with-crucial-parameter-value-equals-this-or-that” juxtapositions), rather
than showing dozens of simulations. A typical mistake made by novice simulators
is to display the results of many computer runs that vary only by a single
parameter on several pages, making it nearly impossible for the reader to
discern the overall impact of parameter variation on simulation results. Often,
some manual “cut and paste,” is necessary to get a coherent graphical
presentation. Note that it is never
sufficient to report results only by showing plots; some accompanying verbal description -- well keyed to the plots -- is necessary to receive full credit. Irrespective
of the contents of the data plots, a “sprawling” presentation where the
relevant variation occurs across pages or with insufficient labeling (of axes
and parameter variations) will be awarded reduced credit. Listing of computer
code is not desired.
Simulation
assignment software: While
it is assumed that every student in this
course is capable of writing simple applications programs for coding
assigned simulations, this is not a programming course, and programming will
not be taught in the class as such. The course’s TF can help with trouble-shooting.
The assignments are not meant to burden students with days of software
development, and they have been constructed in such a way as to minimize
program development time. You many use any commercially available software that
you feel enhances your productivity. You may legitimately ask questions of me
or of the course TF while doing the assignments. You may discuss simulation
development with fellow students, up to the point of exchanging programming
“tips” or information about available resources (for graphics, word processing,
etc.), but you are not to work in groups
for “division of labor.” If you
anticipate difficulties in performing simulations (programming, graphical
plotting, machine access), see the course teaching fellow immediately.
FINAL
REPORT: The content of
every student’s final report will be negotiated individually, but the basic
considerations of formatting described in the preceding sections about
simulation assignments continue to apply.
DISCUSSION
MEETINGS: Credit for
participation in discussion meetings
will be based on the student’s understanding of core topics from readings and
lectures, as expressed in comments
initiated by students or in response to questions from the professor.
PLAGIARISM:
What you write is to be
the original expression of your own learning. If you must employ a phrase or
more of words written by another person, clearly mark the passage used as a quotation,
and cite the source in full. Note, even if what you write is not identical to
what is written in the source document, if the key idea is from some other
document, then that document must be
cited. This requirement applies even if the source is the course lecture
notes, a web site, or any “study guide” informally circulated among students,
whether in paper or electronic form.
“EXTRA
CREDIT” WORK: There will
be none. The course already contains many pointers for “extra” work within its
assignments. The answer to any request that a student be allowed to bring their
grade up to some level (say, B-) through work not already described in course
materials -- as opposed to doing a proper job on the regular assignments --
will be “NO.”
“MAKE-UP”
WORK: (a) Assignments:
Simulation assignments turned in after the due date for whatever reason are
eligible for a maximum of 80% credit. For example, a student receiving less
than an 8 (on a 10-point scale) on a given simulation assignment may resubmit a
corrected version of that assignment within 5 weeks of the original due date,
in order to bring the grade up to 8 (i.e. 80% of full credit). If a less-than-
perfect assignment is submitted on the second round, the grade will be 80% of
what that assignment would have earned on the first round. No amount of subsequent extra work
on that assignment can make the resulting grade higher than 8. (b)
Examinations: Students who are unavoidably absent from the in-class examination
will take a special make-up examination consisting of written and oral portions
as soon as one can be scheduled.
CONFIDENTIALITY OF PERSONAL WORK: All students using
University computers for doing simulations, word processing, or figure
generation for assignments or take-home examinations are expected to
read-protect their files.
LECTURE
NOTES AND MISCELLANEOUS READINGS:
All lecture notes for the course are available in the course web site. Required
readings that are not contained in the textbooks are also available in the
course web site.
BU POLICY: The syllabus, course descriptions, and
handouts created by Professor Mingolla and minimally modified by Arash
Yazdanbakhsh. All class lectures are copyrighted by Boston University and/or
Professor Mingolla and/or Arash Yazdanbakhsh.
Except with respect to enrolled students as set forth below, the
materials and lectures may not be reproduced in any form or otherwise copied,
displayed or distributed, nor should works derived from them be reproduced,
copied, displayed or distributed without the written permission of Professor
Mingolla and Arash Yazdanbakhsh.
Infringement of the copyright in these materials, including any sale or
commercial use of notes, summaries, outlines or other reproductions of
lectures, constitutes a violation of the copyright laws and is prohibited. Students enrolled in the course are allowed
to share with other enrolled students course materials, notes, and other
writings based on the course materials and lectures, but may not do so on a
commercial basis or otherwise for payment of any kind. Please note in particular that selling or
buying class notes, lecture notes or summaries, or similar materials both
violates copyright and interferes with the academic mission of the College, and
is therefore prohibited in this class and will be considered a violation of the
student code of responsibility that is subject to academic sanctions.
BOOKS
MOST RELEVANT TO THE COURSE:
The first two books have been ordered for CN 530:
Palmer,
S. E. (1999). Vision science: From
photons to phenomenology. Cambridge, MA: MIT Press. (Approx. $80.00). The bookstore lists it
as “required,” in the sense that many required readings can be found there. You
may choose to use the CNS library edition of this book, or to purchase it. In
the weekly listing of required readings, this book is designated as “Palmer.” Note that all chapters of this
book may be available for downloading with a subscription to Cognet: http://cognet.mit.edu/
Kandel (Editor) E. R., Schwartz, J.
H., and Jessell, T. M. (Eds), Principles of Neural Science, Edition 4. New
York: McGraw-Hill (hardcover $85.00) The 4th edition of “KSJ” is by now well out of date, and the fifth edition is supposed to appear
soon (the promise was January 2009, if you hear about it someday, let all the
class know). You may
wish to hold off on purchasing, unless you find a good price on a used volume.
Many present CNS students own copies of this.
You may wish to consider
additional purchases, which have not been ordered for CN 530. Some comments are
included below to help you make purchasing decisions. Books are interest in the
order in which they are most likely to be useful for most students.
Yantis,
S. (2000) Visual
Perception: Essential Readings. Psychology Press, (Approx $45, paperback.) In the weekly listing of required
readings, this book is designated as “Yantis.”
Strunk, W., Jr., and White, E.B. The Elements of style. 4th edition.
Boston, Allyn & Bacon, 2000.
At $6.95 (paperback) this may be the best book, on a price/performance basis,
you ever purchase. One cannot overstate the importance of being able to
communicate your ideas in forceful and direct English.
Grossberg,
S. (Ed.) (1987). The adaptive brain II:
Vision, speech, language, and motor control. Amsterdam: North Holland. ($61.50, paperback) This book includes
core papers describing the work on vision done at the Center for Adaptive
Systems. It also contains many other papers that will be used for other courses
in CNS.
Wandell,
B. A. (1995). Foundations of vision.
Sunderland, Massachusetts: Sinauer Assoc., Inc. The bookstore lists this book as
“optional.” This book contains an overview of current research issues in visual
perception. Several chapters of this book were required reading in past
editions of CN 530; in the weekly listing of supplementary readings, this book
is designated as “BAW.” This book is
tutorial in organization, with a clear emphasis on “vision science,” rather
than visual perception. (Please ask me if you do not know the difference.)
(Approx. $50.00).
Kosslyn,
S. M. & Anderson, R. A. (Eds.) (1992). Frontiers
in cognitive neuroscience. Cambridge, MA: MIT Press. ($70.00, hardbound) This collection reprints “classic”
papers in many in areas besides vision. In the weekly listing of required
readings, this book is designated as “K
& A.”
Answers to CN 530 FAQs:
Question
1: Why is there so much
required reading? (In other words, what do I really have to do to get an A?
What parts of this stuff can I skip?)
Answer: Through points
raised in lectures, notes interspersed throughout the syllabus, the creation of
a study guide to be as explicit about what you are expected to know. Further suggestions
are welcomed. There’s simply a lot to know about vision before you can even
start to model it.
Question
2: Aren’t you really
making us read more than is really important? Couldn’t you tell us more
explicitly which sections, figures, equations, paragraphs, or sentences really
matter?
Answer: Yes, it’s true.
There remain a few places where I could have been even more explicit than I
have been about how you should separate wheat from chaff. By electing to take
this course, however, you have embarked on study of an area so unformed that,
for many topics, consensual “textbook” knowledge does not exist. Soon enough you
will have to confront primary source material without any of the aids provided
in this course! Part of my job is to train you to meet the challenge of
transitioning from “undergraduate mode” to “researcher mode.” I have done this
in part by assigning -- in a few places -- entire chapters or articles for
which I know that whole sections could be skipped without undue harm! Part of
your job is to figure out
which are those sections, and not to worry about them.
Question 3: Some parts of some readings contradict
parts of other readings. What’s going on?
Answer:
Welcome to the real world of science.
Question
4: Why do I have to
bother with all this silly psychology and complicated physiology? How is this
going to help me design real world vision applications?
Answer:
Let’s talk about this during our discussion periods.
Question
5: Why are so many of
the course readings from primary sources (original research articles, as
opposed to textbook chapters)? The authors use different terminology for the
same concepts, and often contradict one another, and they take way more pages
to explain things than a textbook does.
Answer: No single textbook
appropriate for the entire course exists. The books that exist are either too
elementary, too narrow, or too detailed
in scope, and they barely cover much of the core material in the course.
For certain ideas, there simply is no present substitute for primary sources.
(Remember, that’s correlated with our department being involved in emerging,
new, exciting, interdisciplinary, lime-scented research!) Even in the case of
psychophysics, and physiology, which the textbooks cover at least moderately
well, I have asked you to read some primary sources. I believe that the extra
effort required to read them will be rewarded by deeper understanding than can
be gotten from textbooks. In any case, I encourage you to go back and forth,
between the two types of readings, until you have satisfied yourself that you
can master the material outlined in the study guide and presented in class.
Question
6: How will I know when
I’m “getting it,” given how amorphous and confusing some of the readings are?
How do I know which version of several descriptions of, for example,
physiological functions of some visual area, is right?
Answer: Where experts
disagree, you are entitled to make an informed choice among reasonable
alternatives. You are, however, expected to understand the issues underlying
the disagreement.
Question 7: How should I study for the in-class
midterm?
Answer: During the
mid-term, you will not be reading
long articles, or reviewing lecture notes, so do not spend all of you
preparation time in those activities! During the exam you will primarily be writing. You should practice writing.
You should practice writing concise answers to short questions in limited time. I will do my best to make
the exam less a measure of your rate of expression and more a matter of
assessing your mastery of content. You can help avoid unpleasant surprises by
giving yourself one or two “practice” tests based on the study guide, without
notes or readings, and in a realistically short amount of time. I would be
happy to give you feedback on sample answers that you show me.
Question
8: Much of this course
seems rigidly laid out; what if we want to do things differently (e.g. read
unassigned articles, or do different simulations than required in assignments.)
Answer: Everything about
this course is evolving, and everything is negotiable. Remember, though, that
any proposed improvement has a cost (in human effort) that must be budgeted.
The class motto is: “To suggest is to volunteer.”
WEEKLY TOPICS AND READINGS
The readings are listed
along with a short synopsis of the theme of each week’s lecture. Readings for each week are designated
under the headings Required Reading, Supplementary Reading, and BONUS Reading. You will be responsible
(in the sense of possibly being tested) for material covered under the
“required” heading only – but note, a few “required” readings are also labeled
by a boldface PLUS. These readings
are typically recent reviews, and may seem dense with references to unfamiliar
material. Spend about an hour on such readings and get what you can, but do not
worry that material in these readings will be “on the test.” I will not include
items on the midterm that are intended to probe these readings, nor are you
likely to find basic definitions of fundamental concepts or terms in these
readings. Material listed as supplementary generally falls into one of two
categories. The first includes “enrichment” or “remedial” readings of relatively
broad interest; these are generally followed by short parenthetical comments.
The second category includes technical or scholarly citations. Those supplementary readings that are
indicated by a bullet (•) are likely to be the most useful to you, ask me about
them if you have any trouble locating copies. BONUS readings are listed
because reading them might be fun. (Those contemplating careers as university
professors can use these as a diagnostic; if you do not enjoy a significant
portion of the bonus readings, you may wish to explore another line of work!) NOTE: Students will be expected to have
read all of the required readings listed for a given week by the time that
lecture is given, in the sense that the contents of the lecture will assume
some familiarity with the readings. That is, the lectures will often comment
upon the readings, rather than acting as a substitute for doing the readings.
Week
1: Fundamental problems of vision
1) Unit formation and
grouping
2) Seeing and recognizing
-- form/color interactions
3) Retinal veins and blind
spot
4) Perceiving surface
color: Constancy, contrast, and discounting the illuminant
5) Stabilized images:
Boundaries and featural color and brightness
6) Complementary
processing: Unoriented and oriented detectors
7) The noise--saturation
dilemma
8) Reflectances and
ratios; shunting and mass action
Required Reading:
There are no “required”
readings for Week 1, insofar as you could not be expected to know what to read
to prepare for the first lecture. However, three of the readings listed below
are special in the sense that reading them is a “requirement” for saying that
you know anything about current
approaches to vision. Those readings are (parts of) Gibson (1969), Köhler
(1947), and Marr (1982) listed below on this page. In the best of all possible
worlds, you would have been exposed to these three authors before starting this
course. In any case: (1) Grossberg’s early career overlapped the abbreviated
career of Marr; the two were intellectual rivals. (2) The intellectual
underpinnings of the modeling of grouping and segmentation processes considered
in the middle of the course are clarified by the Köhler reading, and (3) Gibson
was a legitimate genius, whose views changed the course of 20th century
research on vision. In particular, his views on the specification of environmental structure by information in the
optic array were adapted by Marr and his colleagues into their tenets on the
development of “computational theory.” (Note that Gibson is the only intellectual
rival attacked by name in Marr’s first chapter.) If pressed for time, consider
Marr the first priority. Köhler can wait
for several weeks into the course, and Gibson can wait until later.
Supplementary Reading:
• Gibson, J. J.
(1979). The ecological approach to visual perception. Chapter 14: “The
theory of information pickup and its consequences.” Boston, Houghton-Mifflin. Reprinted in Yantis, Chapter 4.
• Köhler, W. (1947). Gestalt Psychology. New York, New
American Library. Chapter IV, “Dynamics as opposed to machine theory”, 60-79.
(This chapter contains some obscure allusions to old psychological concepts,
but is still one of the most inspiring statements of the “dynamical systems”
view of psychological processes!) PDF.
• Marr, D. (1982). Vision, Chapter 1. “The philosophy and the approach.” San Francisco, W.H. Freeman. Marr argues clearly and persuasively
for a point of view that has enjoyed considerable popularity in recent years.
Much of the CAS/CNS work in vision can be cast in counterpoint -- explicit or
implicit -- to Marr’s views. Reprinted in Yantis,
Chapter 5.
Week
2: Shunting competitive networks and representation in early vision
1) Brightness: Constancy
and contrast
2) Shift property and
Weber law
3) Retinal physiology
4) Hyperpolarization and
featural noise suppression
5) Distance--dependent
shunting networks
6) Another approach (Marr)
7) Recurrent competitive
networks
Required Readings: (To be read BEFORE
class)
PALMER. Read Chapters 1 and 2 for “background.” Also read Ch. 4,
Sec. 3.
Grossberg, S. (1982). Why
do cells compete? UMAP Unit 484, The UMAP
Journal, Vol. III, No. 1. (Education Development Center,
0197-3622/82/010101.) (This is by far the “easiest” introduction to shunting
inhibition Grossberg has ever written.) PDF.
KSJ. Read Ch. 25 and Ch. 26. Also, skim Ch.
21 if you have had no undergraduate introduction to perception or cognition.
Ch. 26 contains some details of the pharmacology of receptor phototransduction
that will not be “on the test for CN 530,” as clarified in class.
Yantis.
Chapter 14. Wallach, H.
(1948) Brightness constancy and the nature of achromatic colors. Journal of Experimental Psychology, 38, 310-324.
(A “light touch” on reading this one is okay. Read the summary first.)
Supplementary Reading:
Note: While not
“required,” the second article listed below will be of particular interest to those
of you concerned with computer vision (and is very short!)
• Grossberg, S. (1973).
Contour enhancement, short term memory, and constancies in reverberating neural
networks. Studies in Applied Mathematics LII, 213-257. Reprinted in S.
Grossberg, Studies of mind and brain (1982), Boston, Reidel. This is one of the
foundational papers in the area of recurrent competitive networks. PDF.
• Boyer, K. L., and
Sarkar, S. Computer Vision and Image
Understanding. Perceptual Organization in Computer Vision: Status,
Challenges, and Potential. Vol. 76, No. 1, October, pp. 1–5, 1999, Article ID
IV990797. PDF.
Cornsweet, T. (1970). Visual Perception. New York, Academic Press. Chapter XI, “The
psychophysiology of brightness -- I”, 268-310. (While this discussion is
somewhat dated, it is lucid; also, Cornsweet’s views about subtractive
inhibition are illustrative of views that many of Grossberg’s discussions of shunting inhibition are directed
against.)
Borg-Graham LJ, Monier C, Fregnac Y (1998). Visual input evokes transient and strong shunting inhibition
in visual cortical neurons, Nature, 393(6683),
369-373. PDF.
BONUS Reading:
Yantis,
Ch 2. Barlow, H. B.
(1972) Single units and sensation: A neuron doctrine for perceptual psychology?
Perception 1:371-394. Reprinted as
Chapter 14 of J. A. Anderson, A. Pellionisz, and E. Rosenfeld (Eds.)
Neurocomputing 2, Directions for Research. Cambridge, MA, MIT Press, 1988. This
is one of the foundational papers from the recent “single unit” era in
physiological psychology.
1) Anatomical and
physiological techniques
2) Retinal structure and
function
3) ON and OFF channels
4) Anatomy and physiology
of the early visual pathways
Required Reading: (To
be read BEFORE class)
KSJ. Read Ch. 27.
Schiller, P. H. On the
specificity of neurons and visual areas. Behavioural
Brain Research, 1996, 76 (21-35).
PDF.
PLUS: Bullier J. (2001). Integrated model of
visual processing. Brain Res Brain Res
Rev.36(2-3):96-107. PDF.
This paper may seem “dense,” particularly if you are new to the physiology of vision.
Such papers are intended to provoke thought rather than to add to the list of
items that you will appear on the mid-term exam. For now, just make an honest
effort to read with some care.
PLUS: http://ohzawa-lab.bpe.es.osaka-u.ac.jp/ohzawa-lab/teaching/AA_RFtutorial.html
Spend an hour on this site, viewing demos
and downloading Receptive-field dynamics in the central visual pathways
(TINS 1995) by DeAngelis,
Ohzawa, and Freeman.
PLUS:
Callaway EM (1998). Local circuits in primary visual cortex of the macaque monkey Annual
Review of Neuroscience 21, 47-74 1998. Comprehensive review. PDF.
Supplementary Reading:
• Levine, D. and
Grossberg, S. (1976). Visual illusions in neural networks: Line neutralization,
tilt after-effect, and angle expansion. Journal
of Theoretical Biology, 61, 477-504. Levine was Grossberg’s first Ph.D.
student PDF.
•
Izhikevich,
E.M. (2004). Which model to use for cortical spiking neurons? IEEE Transactions on Neural Networks, vol.
15 (5), pp.1063-1070. PDF.
Gilbert, C. D. Plasticity
in visual perception and physiology. Current
Opinion in Neurobiology 1996, 6:269-274. PDF.
Bullier, J. and Nowak, L.
G. Parallel versus serial processing:
new vistas on the distributed organization of the visual system. Current Opinion in Neurobiology, 1995,
5:497-503. PDF.
BAW: Read Chapter 7.
• Schiller, P. H. (1986).
The central visual system. Vision
Research, 26, (9), 1351-1386.
This is a scholarly and entertaining review of early work in neurophysiology. See Part A, pages 1351-1362. PDF.
Ellias, S. and Grossberg,
S. (1975). Pattern formation, contrast control, and oscillations in the short
term memory of shunting on-center off-surround networks. Biological Cybernetics, 20, 69-98. PDF.
BONUS Reading:
Sacks, O. (1995). The case
of the colorblind painter. Pages 3-41 in O. Sacks, An anthropologist on Mars. New York: Alfred Knopf.
Week
4: Contrast sensitivity and spatial scales
1) Structural scales: functional scales :: kernels: receptive
fields
2) Peak shifts and lateral inhibition
3) Detectors and filters -- linear systems approach to vision
4) Contrast sensitivity and spatial scales
5) Brightness perception: Quantifying percepts
6) Isomorphistic and nonisomorphistic theories
7) Craik-O’Brien-Cornsweet (COCE) effect
8) Retinex algorithm
Required Reading: (To be
read BEFORE class)
PALMER. Ch. 4.
Kaufman, L., (1974). Sight and Mind. New York, Oxford
University Press. Chapter 5, “Contrast and contour”, 128-152. (This is a good
overview of some classic issues in spatial vision. Don’t worry if a few parts
seem obscure.) PDF.
Grossberg, S. (1983). The
quantized geometry of visual space: The coherent computation of depth, form,
and lightness. Behavioral and Brain
Sciences, 6, 625-692. Reprinted as Chapter 1 of Grossberg, S. (Ed.) (1987).
The adaptive brain II: Vision, speech, language, and motor control. Amsterdam:
North Holland. Read Sections 1-3 and 21-25, 27, and 28, and the commentaries of
Grimson and Stevens and Grossberg’s reply to those commentaries. Note that the
Commentary section appears only in the journal article and is not reprinted in
the book. Sections 21-25 restate and extend the discussion of the “UMAP Module”
reading. PDF.
Adelson, E.H.
(2000). Lightness Perception and Lightness Illusions, in M. Gazzaniga, M.S.,
ed., The New Cognitive Neurosciences,
2nd Ed.Cambridge, MA: MIT Press, pp. 339-351. PDF.
This is a clearly written article that explains much of the important
terminology used in the study of lightness perception.
PLUS: Sincich, L. C. and Horton, J. C. (2005). The circuitry of V1 and V2:
Integration of color, form, and motion. Annual
Review of Neuroscience, 28:303-26. While this article is dense and contains
a lot more information than “will be on the test,” you should spend an hour or
so on this reading, as an antidote to the simplifications of the KSJ treatment
of these areas. PDF.
Supplementary Reading:
• Neumann H. (1996). Mechanisms of neural architecture for visual contrast and brightness perception. Neural Networks, 9(6), 921-936. NOTE: You may wish to consult this paper while doing Simulation Assignment 2. (Downloadable at: http://www.sciencedirect.com)
• Kiper, D. and Carandini,
M. The neural basis of pattern vision. Encyclopedia
of cognitive science , 2000, Macmillan Reference, Ltd. PDF.
• Westheimer G., The
Fourier theory of vision. Perception, 30(5), 531-541. This article is
particularly lucid and worthwhile, if you have the background to appreciate
it. PDF.
Gaudiano P. (1994). A
nonlinear model of spatiotemporal retinal processing: simulations of X and Y
retinal ganglion cell behavior. Vision
Research, 34, 1767--1784. PDF.
Week 5: Brightness and lightness
1) Brightness assimilation
2) Grossberg and Todorovi (T) implementation of
BCS/FCS
3) G
& T simulations
4) Integration models
(e.g. Retinex)
5) Challenges to brightness models
Required Reading: (To
be read BEFORE class)
PALMER. Skim Ch 3. Read Sec. 3.3 carefully.
Todorovi, D. (1987). The
Craik--O’Brien--Cornsweet effect: New varieties and their theoretical
implications. Perception &
Psychophysics, 42, 545-560. Do not fret the details; read for gist and
concentrate on the distinction between isomorphistic and nonisomorphistic
theories. While a bit dense, this article provides a useful way to partition
contemporary “styles” of modeling. PDF.
Grossberg, S. and Todorovi, D. (1988). Neural dynamics of 1-D and
2-D brightness perception: A unified model of classical and recent phenomena. Perception & Psychophysics, 43,
241-277. PDF. Do a “first pass”
on this paper. Concentrate on the role of boundaries and diffusion in explaning percepts. The lecture covers the
Appendix in detail, and you will revisit this paper in Simulation Assignment 3.
Gilchrist A, Kossyfidis C,
Bonato F, Agostini T, Cataliotti J, Li X, Spehar B, Annan V, Economou E. An
anchoring theory of lightness perception. Psychological
Review, 1999 Oct;106(4):795-834. PDF.
Daugman, John. (1990)
Brain metaphor and brain theory. Chapter 2 of Eric Schwartz (Ed.) Computational Neuroscience. Cambridge,
MA: MIT Press. Reprinted as Chapter 2 in Philosophy
and the Neurosciences, edited by
W. Bechtel et al. Oxford: Blackwell Publishers. (Scanned .PDF file here).
(This essay is a timely and entertaining polemic on the meaning of the
word “computational.”)
Check out Retinex-based commercial image processing at: http://dragon.larc.nasa.gov/retinex/
Compare
Simon Hong’s results by following “projects” link at: http://cns-alumni.bu.edu/~yhong/
Supplementary Reading:
For Retinex Matlab code, go to:http://www.cs.sfu.ca/~colour/publications/IST-2000/
Marr,
D. (1982). Vision. New York, W.H.
Freeman. Pages 250-258. Marr gives a lucid overview of Land’s Retinex theory;
read this before Land (1986). PDF.
Cornsweet, T. (1970). Visual Perception. New York, Academic
Press. Chapter XII, “Psychophysiology of brightness -- II, Modulation transfer
functions,” 311-364.
Graham, N. (1980). Spatial
frequency channels in human vision: Detecting edges without edge detectors. In
C. S. Harris, Ed., Visual coding and
adaptability. Hillsdale, NJ, Earlbaum, 215-262. The experiment described in
Figure 6 (page 226) and the accompanying text is of fundamental importance to
understanding issues related to “spatial frequency channels” in human vision.
BONUS READING
Land,
E. H. (1986). Recent advances in Retinex theory. Vision Research, 26(1),
7-21. You will be
expected to understand
this approach, an example of an “integration theory,” in excruciating detail. PDF.
Week 6: Parallel visual
pathways, boundaries and surfaces
1) A simple BCS-FCS model
2) Diffusion and time
3) Symbolic models and
energy models
4) Edge detection?
5) How thin is “thin”?
6) Spatial and
orientational competition
7) Hyperacuity
8) Neon color spreading
Required Reading: (To be read BEFORE
class)
PALMER. Ch 6.
Neumann, H. and Mingolla,
E. (2003) Contour and surface perception. In M.A. Arbib, Ed., Handbook of brain
theory and neural networks, II. Cambridge, MA: MIT Press. PDF.
PLUS: Komatsu H. (2006) The neural mechanisms of
perceptual filling-in. Nat Rev Neurosci. 7(3):220-31. Actually, this is NOT a
“required reading,” (in the sense of a reading whose material will be “on the
test.”) I have included it here to get the attention of any skeptics who might
thing that this “filling-in” idea is just some obsession of a handful of
researchers. PDF.
PLUS:
Hegdé J, Van Essen DC.
(2007) A comparative study of shape
representation in macaque visual areas v2 and v4, Cereb Cortex, 17(5):1100-16. PDF.
Supplementary Reading:
• Pessoa, L., Thompson,
E., & Noe, A. Finding
out about filling-in: a guide to perceptual completion for visual science and
the philosophy of perception. Behavioral
and Brain Sciences, 1998 Dec;21(6):723-48. PDF.
Davey, M. P., Maddess, T.,
and Srinivasan M. V. (1998). The
spatiotemporal properties of the Craik-O’Brien-Cornsweet effect are consistent
with “filling-in”. Vision Research, 38(13),
2037-2046. The title speaks for itself. PDF.
BAW: Read Chapter 6.
Hung
CP, Ramsden BM, Chen LM, Roe AW., Building surfaces from borders in Areas 17
and 18 of the cat., Vision Res. 2001;41(10-11):1389-407. PDF. Take
a look for some electrophysiological evidence regarding the effect of boundary
contrast on surface lightness.
Paradiso, M. A. and
Nakayama, K. (1991). Brightness perception and filling-in. Vision Research, 31, 1221-1236. PDF.
Gerrits, H. J. M., and
Vendrick, A. J. H. (1970) Simultaneous contrast, filling-in process and
information processing in man’s visual system. Experimental Brain Research, 11, 411-430.
Grossberg, S. and
Mingolla, E. (1985). Neural dynamics of form perception: Boundary completion,
illusory figures, and neon color spreading. Psychological
Review, 92(2), 173-211. Reprinted as Chapter 2 of Grossberg, S. (Ed.)
(1987). The adaptive brain II: Vision, speech, language, and motor control.
Bressan, P., Mingolla, E., Spillmann, L.
and Watanabe, T. (1997). Neon color spreading: A review. Perception, 26(11), 1353-1366. PDF.
Badcock, D. R., and
Westheimer, G. (1985). Spatial location and hyperacuity: The center/surround
localization contribution function has two substrates. Vision Research, 25, 1259-1267. PDF.
BONUS
Westheimer, G. (1983). Herman Helmholtz and the origins of
sensory physiology. Trends in
Neurosciences, Jan., 5-9. (Did you know that Helmholtz is considered by
many to be the greatest sensory psychologist who ever lived?) PDF.
Week
7: Boundary detection, completion, and sharpening
1) How thin is “thin”
2) Spatial and orientational competition
3) Hyperacuity
4) Neon color spreading
5) Cooperative-Competitive (CC)
6) Bipole cells, then and now
7) von der Heydt, Peterhans, & Baumgartner, 1984
8) Spatial impenetrability
Required
Grossberg, S. and
Mingolla, E. (1985). Neural dynamics of perceptual grouping: Textures,
boundaries, and emergent segmentations. Perception
& Psychophysics, 38, 141-171. Reprinted as Chapter 3 of Grossberg, S.
(Ed.) (1987). The adaptive brain II: Vision, speech, language, and motor
control.
KSJ. Read
Yazdanbakhsh, A. and M. S. Livingstone
(2006). End stopping in V1 is sensitive to contrast. Nature Neuroscience 9
(5): 697-702. PDF.
von der Heydt, R., Peterhans, E., and Baumgartner, G. (1984). Illusory contours and cortical neuron
responses. Science, 224, 1260-1262. PDF. (This paper describes some striking evidence
for long- range cooperative interactions in early vision. Reprinted as
PLUS: Pasupathy, A. and Connor, C.E. (2002)
Population coding of shape in area V4. Nature Neuroscience 5: 1332-1338. PDF.
PLUS: Roelfsema PR. (2006) Cortical algorithms for perceptual
grouping. Annu Rev Neurosci. 29:203-27. PDF.
PLUS: Takeichi H, Shimojo S, Watanabe T. (1992). Neon flank and
illusory contour: interaction between the two processes leads to color
filling-in. Perception 21(3):313-24. PDF.
This shows how psychophysics can help localize the areas responsible for
boundary and surface formation.
Supplementary
Francis, G., Grossberg, S., and Mingolla, E. (1994).
Cortical dynamics of feature binding and reset: Control of visual persistence. Vision Research , 34 (8), 1089-1104. PDF.
Koffka, K. (1935/1963). Principles of Gestalt psychology.
Spillmann, L., Werner,
J.S. Long-range interactions in visual perception. TRENDS NEUROSCI 19: (10) 428-434 OCT 1996. PDF.
Fitzpatrick,D. Seeing
beyond the receptive field in primary visual cortex. CURR OPIN NEUROBIOL 10: (4) 438-443 AUG 2000. PDF.
Lamme VAF, Super H,
Spekreijse H Feedforward, horizontal, and feedback processing in the visual
cortex. CURR OPIN NEUROBIOL 8: (4)
529-535 AUG 1998. PDF.
Sarti A, Malladi R,
Sethian JA Subjective surfaces: A method for completing missing boundaries
P
NATL ACAD SCI USA 97:
(12) 6258-6263 JUN 6 2000. (Of interest to students concerned with computer vision.) PDF.
Neumann, H. and Mingolla,
E. 2001 Computational neural models of spatial integration in perceptual
grouping. In From Fragments to Objects:
Grouping and Segmentation in Vision. T.F.Shipley & P.J.
Kellman, Editors.
Gove, A., Grossberg, S.,
and Mingolla, E. (1995). Brightness perception, illusory contours, and
corticogeniculate feedback. Visual
Neuroscience, 12, 1027--1052. PDF.
Grossberg, S. Mingolla, E.
& Ross, W. D. (1997). Visual brain and visual perception: A
corticogeniculate model of perceptual grouping. Trends in Neurosciences (TINS), 20(3), 106-111. PDF.
Lesher, G. W. (1995).
Illusory contours: Toward a neurally based perceptual theory. Psychonomic Bulletin and Review, 2(3),
279-321. (This is the literature
review on illusory contours, at least up to its publication date.)
Lesher, G. W. &
Mingolla, E. (1993). The role of edges in line-ends in the formation of
illusory contours. Vision Research,
36(16), 2253--2270. B & G: Chapter 5. PDF.
Redies,
C. and Spillmann, L. (1981). The neon color effect in the Ehrenstein illusion. Perception, 10, 667-681.
S. Petry and G. E. Meyer,
Eds. (1987), The perception of illusory
contours.
Ullman, S. (1984). Visual
routines. Cognition, 18, 97-106.
Reprinted in M. A. Fischler and O. Firschein, Eds.,
Zucker, S. W. (1985).
Early orientation selection: Tangent fields and the dimensionality of their
support. Computer Vision, Graphics, and
Image Processing, 32(1), 74-103. Also in M. A. Fischler and O. Firschein,
Eds.,
Ramsden BM, Hung CP, Roe
AW. (2001). Real and illusory contour processing in area V1 of the primate: a
cortical balancing act., Cereb Cortex.
Jul;11(7):648-65. This article shows
the difference between V1 and V2 units in response to illusory contours.
Reading the abstract, figure legends and discussion suffices. PDF.
BONUS
Bateson, G. (1979). Every
schoolboy knows... Chapter 2 of Mind and
Nature.
Week 8: The phenomena of motion
perception
1) What is motion?
Apparent motion and real motion
2) Long-range motion:
Arguments for short and long range mechanisms
3) Korte’s
laws and figural affinity:
Traveling Gaussian waves (G-waves -- Grossberg and Rudd)
4) Short and long-range
motion
5) Fourier and non-Fourier
stimuli
6) Gradient models
(Marr/Ullman)
7) Energy models
(Adelson/Bergen)
8) Correlation models
(Reichardt; van Santen/Sperling
Required
PALMER. Ch 10.
Grossberg, S. and Rudd, M.
E. (1989). A neural architecture for visual motion perception: Group and
element apparent motion. Neural Networks,2,
421-450. Read pages 421-433. Do not get “bogged down” in the description of the
5 levels of the model and on oddities such as “rightward propagation of
leftward motion signals.” Concentrate on the traveling Gaussian wave mechanism,
period. PDF.
Supplementary
BAW, Chapter 10
• Cavanagh, P. and Mather,
G. (1990). Motion: The long and the short of it. Spatial Vision, 4, 103- 129. PDF.
Nakayama, K. (1985).
Biological image motion processing: A review. Vision Research, 25(5), 625-660. Read 625-651. PDF.
Kolers,
P. A. (1972). Aspects of motion
perception.
Adelson, E. H. and
Anstis, S. (1988). Motion
perception in the frontal plane. Chapter 16 of K. R. Boff, L. Kaufman, and J.
P. Thomas, Eds., Handbook of perception
and performance, Volume I, Sensory processes and perception, pages 16-1 to
16-27.
van Santen, J. P. H. and
Sperling, G. (1985). Elaborated Reichardt detectors. Journal of the Optical Society of
BONUS
Yantis, Chapter 4. Gibson, J. J. (1979). The
ecological approach to visual perception. Chapter 14: The theory of information
pickup and its consequences (pp. 238-263).
Week
9: Models of motion perception
1) Group and element
motion
2) Motion pooling and
aperture problem
3) Motion detection,
segmentation and grouping
Required
Grossberg, S., Mingolla,
E. and Viswanathan, L. (2001). Neural dynamics of motion integration and
segmentation within and across apertures. Vision
Research, 41(19), 2521-53. PDF.
Pack CC, Born RT.
(2001). Temporal dynamics of a neural solution to the aperture problem in
visual area MT of macaque brain. Nature. Feb 22;409(6823):1040-2. PDF. This is a great paper.
Simoncelli, E. P., & Heeger, D. J. (1998). A model of neuronal responses in visual
Supplementary
• Born RT,
Bradley DC. (2005) Structure and function of visual area MT.Annu Rev Neurosci.
2005;28:157-89. PDF.
• Allman, J., Miezin, F., &
McGuiness, E. (1985). Direction- and velocity-specific responses from beyond
the classical receptive field in the middle temporal visual area (MT). Perception, 14, 105- 126. Reprinted as
Grossberg, S. and Rudd, M.
E. (1992). Cortical dynamics of visual motion perception: Short-range and
long-range apparent motion. Psychological
Review, 99(1), 78-121. Read pages 78-82 and 90- 96. PDF.
Livingstone
MS, Pack CC, Born RT. (2001). Two-dimensional substructure of MT receptive
fields. Neuron. Jun;30(3):781-93. PDF. This article teaches you experimental
techniques in motion electrophysiology with classic citations about each aspect
of the technique. Figure captions are clear, therefore you can use the
abstract-figure captions-discussion strategy again!
Mingolla, E., Todd, J. T., & Norman, J. F. (1992). The perception of globally coherent
motion. Vision Research, 32(6), 1015--1031.
PDF.
Albright,
T. D., Desimone, R., and Gross, C. G. (1984). Columnar organization of
directionally sensitive cells in visual area MT of the macaque. Journal of Neurophysiology, 51, 16-31.
BONUS
Gregory, R. L. (1991).
What is caught in neural nets? Perception,
19, 561-568. Gregory is the most influential exponent of the “cognitivist”
position in vision today, though his views resist simple categorization.
Regardless of whether you agree or disagree with him, this essay is fun!
There
will be an in-class EXAMINATION, covering the topics in the readings and
lectures from the first 9 weeks, during the class period.
BONUS
Thompson,
D. A., (1917/61). On magnitude. Chapter 2 of On growth and form (Abridged edition).
Week 11: Approaches to textural segmentation and grouping
1) What is texture?
2) Textural segmentation
-- textons?
3) Representations for
segmentation
4) LaminART
Required
Yantis, Chapter 17. Mishkin, M. Ungerleider, L.
G., and Macko, K. A. (1983). Object vision and spatial vision: Two cortical
pathways. Trends in Neurosciences, 6,
414-417. This classic paper launched decades of research and debate.
Beck, J. (1993). The
British Aerospace Lecture: Visual processing in texture segregation. In D.
Brogan, A. Gale and K. Carr, Eds. Visual
Search 2.
Malik, J. and Perona, P.
(1990). Preattentive texture discrimination with early vision mechanisms. Journal of the Optical Society of
Grossberg, S.
and Raizada, R. (2000) Contrast-sensitive perceptual grouping and object-based
attention in the laminar circuits of primary visual cortex. Vision Res. 40(10-12):1413-32. PDF.
Supplementary
•
BAW, Chapters 8.
• Beck, J. (1983).
Textural segmentation, second-order statistics, and textural elements. Biological Cybernetics, 48, 125-130.
• Julesz, B. and
Zucker, S. W., Dobbins,
A., and Iverson, L., (1989). Two stages of curve detection suggest two styles
of visual computation. Neural
Computation, 1(1), 68-81.
Beck, J., Prazdny, K. and
Rosenfeld, A. (1983). A theory of textural segmentation. In J. Beck, B. Hope,
& A. Rosenfeld (Eds.), Human and
machine vision.
BONUS
Stevens, P. S., (1974). Basic patterns
(Chapter 2) and Spirals, meanders, and explosions. Chapter 4 of Patterns in Nature.
1) Disparity and depth
2) Projection theories
3) The correspondence
problem
4) Matching algorithms
5) Prazdny’s algorithm
6) Grimson’s wedding cake
7) Kaufman’s stereogram:
Rivalry
8) Occlusion, depth, and
da Vinci stereopsis
9) Modal and amodal perception
(NOT transparency)
Required
PALMER. Ch 5, Secs. 1-3.
Kaufman, L. (1974).
Binocular stereopsis. In L. Kaufman, Sight
and Mind.
Grossberg, S. 1983. The
quantized geometry of visual space: The coherent computation of depth, form,
and lightness. Behavioral and Brain
Sciences, 6, 625-692. Reprinted as Chapter 1 of Grossberg, S. (Ed.) (1987).
The adaptive brain II: Vision, speech, language, and motor control.
DeAngelis GC Seeing in
three dimensions: the neurophysiology of stereopsis TRENDS COGN SCI 4: (3) 80-90 MAR 2000. PDF.
Blake
R, Wilson HR. Neural models of stereoscopic vision. Trends in Neurosciences, 1991 Oct;14(10):445-52. PDF.
Supplementary
• Yazdanbakhsh, A. and T. Watanabe
(2004). Asymmetry between horizontal and vertical illusory lines in determining
the depth of their embedded surface. Vision Res 44(22): 2621-7. PDF.
• Nakayama K, & Shimojo S. (1990). da
Vinci stereopsis: depth and subjective occluding contours from unpaired image
points. Vision Res. 30(11): 1811-25.
This paper is a good example of how psychophysical techniques can
constrain the search for physiological substrates.
• I.P.
Howard & B. J. Rogers, Seeing in
depth: Vol. II. Depth perception.
•
Grossberg, S. (1993) A
solution of the figure-ground problem for biological vision. Neural Networks, 6, 463-493.
Blake,
R. (1989) A neural theory of binocular rivalry. Psychological Review, 96(1), 145-167. Read for gist.
Nakayama, K. Shimojo, S.
and Ramachandran, V.S. (1990) Transparency: relation to depth, subjective
contours, luminance, and neon color spreading. Perception, 19, 497-513.
Dev, P. (1975). Perception
of depth surfaces in random-dot stereograms: A neural model. International Journal of Man-Machine Studies, 7, 511-528.
Marr,
D. (1982). Vision.
Sperling, G. (1981).
Mathematical models of binocular vision. In
Prazdny, K. (1985).
Detection of binocular disparities.
Biological Cybernetics, 52, 93-99. Also in M. A. Fischler and O. Firschein,
Eds.,
Prazdny, K. (1985). On the
disparity gradient limit for binocular fusion. Perception and Psychophysics, 37 (1), 81-83.
Grossberg, S. and
Marshall, J. (1989). Stereo boundary fusion by cortical complex cells: A system
of maps, filters, and feedback networks for multiplexing distributed data, Neural Networks, 2, 29- 51.
Yeshurun, Y. and Schwartz,
E. L. (1987). An ocular dominance column map as a data structure for stereo
segmentation. Proceedings of the IEEE
First International Conference on Neural Networks,
Grossberg, S. (1987).
Cortical dynamics of three-dimensional form, color, and brightness perception:
II. Binocular theory. Perception & psychophysics, 41(2), 117-158. Reprinted
as Chapter 2 of Neural Networks and Natural Intelligence.
BONUS
Schwartz, E. (Ed.) (1990).
Computational Neuroscience. Cambridge,
MA: MIT Press.
Introduction,
ix-xiii. Schwartz offers unvarnished
statements of contrasting presuppositional attitudes.
Week
13: Visual attention, pop-out, and search
1) Facets of attention:
Bottom-up and top-down
2) Feature integration
theory
3) Search rate asymmetries:
Pop-out and slow search
4) Guided search and
iconic bottleneck
5) Surfaces and features
6) Attentional modulation
of receptive fields
7) Change blindness
Required
PALMER. Ch 11.
Kastner,
S. and Ungerleider, L. G. (2000)
Mechanisms of visual attention in the human cortex. Annu. Rev. Neurosci. 23:315-341. PDF.
Yantis, Chapter 22. Moran, J., & Desimone, R. (1985). Selective
attention gates visual processing in the extrastriate cortex. Science, 229, 782-784.
Itti, L. Koch, C. and Niebur, E. (1998).
A model of saliency-based visual attention for Rapid Scene Analysis. IEEE
Transactions on Pattern Analysis and Machine Intelligence, vol. 20(11),
1254-1259. PDF.
Serre, T., Oliva, A. and Poggio, T.
(2007). A feedforward architecture accountsfor rapid categorization. PNAS, vol.
104, pp6424-6429. PDF.
Supplementary
• Duncan J, Humphreys G, Ward
R Competitive brain activity in visual attention CURR OPIN NEUROBIOL 7: (2) 255-261 APR 1997. PDF.
Grossberg, S., Mingolla,
E. & Ross, W. (1994). A neural theory of attentive visual search:
Interactions of visual, spatial, and object representations. Psychological Review, 101(3), 470-489.
Eriksen, C. W. (1990)
Attentional search of the visual field. In Visual
search, D. Brogan, Ed. London: Taylor and Francis.
Duncan, J. (1995). Target
and nontarget grouping in visual search.
Perception & Psychophysics, 57, 117-120.
Wolfe, J. M. (1994).
Guided Search 2.0: A revised model of visual search. Psychonomic Bulletin and Review, 1(2), 202-238.
Moran, J. & Desimone,
R. (1985). Selective attention gates visual processing in the extrastriate
cortex. Science, 229, 782-784.
Reprinted as
Crick, F. (1984). Function
of the thalamic reticular complex: The searchlight hypothesis. Proceedings of the National
The
great beyond
Hochstein
S & Ahissar M. (2002). View from the top: hierarchies and reverse
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Arash Y. says (the latter phrase by Ennio): The experiment in the paper is
doable by yourself when you read the paper, and the explanation seems exciting,
however it worth trying a simpler null hypothesis to interpret the result.
Yantis, all the other chapters . . .