Computational Vision

Psy 5036W, Spring 2003, 3 credits
Psychology Department , University of Minnesota

Courses URL:
courses.kersten.org

Instructor: Daniel Kersten. Office: 212 Elliott Hall. Phone: 625-2589 email: kersten@.umn.edu
Office hours: Thursday 1-2:30

The visual perception of what is in the world is accomplished continually, instantaneously, and usually without conscious thought. The very effortlessness of perception disguises the underlying richness of the problem. We can gain insight into the processes and functions of human vision by studying the relationship between neural mechanisms and visual behavior through computer analysis and simulation. Students will learn about the anatomy and neurophysiology of vision and how they related to the phenomona of perception. An underlying theme will be to treat vision as a process of statistical inference. There will be in-class programming exercises using the language Mathematica. No prior programming experience is required; however, a backround in calculus and linear algebra is helpful.

Readings

Grade Requirements

There will be a mid-term, final examination, programming assignments, as well as a final project.

The grade weights are:

The programming assignments will use the Mathematica programming environment. No prior experience with Mathematica is necessary. List of Computer Labs at the University of Minnesota with Mathematica installed.

Assignment due BEFORE class start time (11:15 am) on the day due.

ASSIGNMENT FAQs PAGE

ASSIGNMENT 3 FAQs


Lectures

Notes updated for each lecture

 

Date

Lecture

Additional Readings & supplementary material

Assignments
due

I. Introduction
 

Mathematica notebook format: 1.The interdisciplinary study of vision.nb

Adobe format: (pdf)

Wandell ch. 1

intro.nb

 
 

(2.LimitsToVision.nb)
(pdf)

 
 

3.Mathematics of inference.nb
(pdf)

Wandell ch. 2

 
 

4.MathematicsOfInferenceII.nb
(pdf)

 

II. Image formation,
pattern synthesis

  5.ProbabilityPattern.nb
(pdf)

Wandell ch. 3

#1 Ideal Discriminator (7%)

 

6.ProbabilityPatternIIb.nb
(pdf)

Mathematica psychophysics notebook template (GaborSKEDetection.nb)
(See too: http://vision.arc.nasa.gov/mathematica/psychophysica/)
and for the most complete (Matlab) psychophysics package, see: http://psychotoolbox.org

 
 

7.LinearSystemsI.nb
(pdf)

Image data files: Fourier128x128.jpeg (or FourierImageDataValues.nb)

LinearAlgebraReview.nb

(LinearAlgebraReview.nb.pdf)

 
III. Early visual coding
 

8.LinearSystemsII.nb
(pdf)
CSF.gif

Wandell ch. 5 & of ch. 8 (pp. 247-258)

 
 

9.SpatialFiltersII.nb

(pdf)

Wandell ch. 6 (pp. 153-183) &7

Tutorials:
1) Convolutions_blur.nb
2) Fourier_neural_image.nb

Assignmt #2Convolve.nb(7%)
 

10.ImageProcessing.nb

(pdf)

Gopen & Swan, 1990

 
 

11.CodingEfficiency.nb
(pdf)
Science Writing

Wandell ch. 4 & 9
Graygranite256x256.jpg
Grass64x64.jpg
granite64x64.jpg

 
 

12.CodingEfficiencyII.nb

GrayLonesome256x256.jpg

 
IV. Intermediate-level vision,
integration, grouping
 

13.CodingEffEdgeDet.nb

13.CodingEffEdgeDet2.nb

(pdf)

Wandell ch. 10 (pp. 341-357)

deer.jpg
(from "Walter Wick's Optical Tricks")

Assignmt3_ImageStats.nb

(7%)

  MID-TERM

MID-TERM Study guide (pdf)

MID-TERM (16%)
 

14.ScenesfromImages.nb
(pdf)

 
 

15.SurfaceGeometryDepth.nb
(pdf)

Wandell ch. 10 (pp. 357-358)

 
 

16. Shape-from-X
(pdf)

Wandell ch. 6 (pp. 182-183) & 10 (pp. 375-385)
RDS.m, ShowStereo.m, ImplicitSolids.m

 
 

17.basrelief.nb
(pdf)

#4 (7%)
Assignmt4SceneImageModels.nb
 

18.MotionI.nb

aperturedemomovie.mov(quicktime)

 
 

19.MotionII.nb
(pdf)

http://psych.la.psu.edu/clip/Perception.htm
http://epunix.biols.susx.ac.uk/Home/George_Mather/Motion/index.html

 
 

 

(20. Surface material)

 

Final project title & paragraph outline (2%)
 

 

 

 
V. High-level vision
 

22.

20.SurfaceMaterial.nb

http://www-bcs.mit.edu/persci/high/gallery/checkershadow_illusion.html

http://vision.psych.umn.edu/www/kersten-lab/demos/transparency.html

diamondocclusion3.mov

 
  THANKSGIVING    
 

23.
21.Texture.nb

   
  24.
22.CooperativeComp.nb
(pdf)

  Complete Draft of Final Project (5%: 2 pts for completing Introduction, 2 pts for completing Methods, 1 pt for completing Discussion)
 

25.
Introduction to visual tasks, Object Recognition
23.ObjectRecognition.nb
(pdf)

   
 

26.
24.StructureMotion.nb
(pdf)

Vision for heading
Vision for scene layout
Vision for reach and grasp

  (Drafts returned)
    FINAL EXAM Final Study Guide (pdf) FINAL EXAM (16%)
      Final Revised Draft of Project (33%)

 

 


Final Project Assignment.

Goal: This course integrates the behavioral, neural and computational principles of perception. Students often find the interdisciplinary integration to be the most challenging aspect of the course. Through writing, you will learn to synthesize results from diverse and typically isolated disciplines. By writing about your project work, you will learn to think through the broader implications of their projects, and to effectively communicate the rationale and results of your computer projects in words. You will do a final page research report in which you will describe, in the form of a scientific paper, the results of an original computer simulation.

Completing the final paper involves 3 steps:

  1. You will submit a working title and paragraph outline. These outlines will be critiqued in order to help you find an appropriate focus for your papers. (2% of grade)
  2. You will then submit a complete draft of your paper. Each paper will be reviewed with specific recommendations for improvement. (5% of grade)
  3. You will submit a final revision for grading. (33% of grade)

Your final project will involve: 1) a computer simulation and; 2) a 2000-3000 word final paper describing your simulation. For your computer project, you will do one of the following: 1) Write a program to simulate a model from the computer vision literature ; 2) Design and program a method for solving some problem in perception. 3) Design and program a psychophysical experiment to study an aspect of human visual perception. The results of your final project should be written up in the form of a short scientific paper or Mathematica Notebook, describing the motivation, methods, results, and interpretation.

If you choose to write your program in Mathematica, your paper and program can be combined can be formated as a Mathematica notebook. See: Books and Tutorials on Notebooks.

Your paper will be critiqued and returned for you to revise and resubmit in final form. You should write for an audience consisting of your class peers.

You may elect to have your final paper published in the course's web-based electronic journal.

    1. Outline. You must submit a title and paragraph outline of your intended paper by the deadline noted in the syllabus. (Consult with the instructor or TA for ideas well ahead of this first deadline).
    2. Complete draft. A double-spaced, complete draft of the paper must be turned in by the deadline noted in the syllabus. Papers should be between 2000 and 3000 words. Papers must include the following sections: Introduction, Methods, Results, Discussion, and Bibliography. Use citations to motivate your problem and to justify your claims. Cite authors by name and date, e.g. (Marr & Poggio, 1979). Use a standard citation format, such as APA . (The UM library has information on research, citation style, and in particular APA style.) Papers must be typed, with a page number on each page.
    3. Final draft. The final draft must be turned in by the date noted on the syllabus. Students who wish to submit their final papers to be published in the class electronic journal should turn in both paper and electronic copies of their reports.