Class Web Board: Piazza
Class web page: http://cseweb.ucsd.edu/classes/fa13/cse252Aa
Final exam, Thursday 12/12/13 8:00am10:59am TBA Sample final exam
Instructor: David
Kriegman
Office: EBU3B, Room 4120
Phone: (858) 8222424
Email: kriegman at cs.ucsd.edu
Office Hours: Tuesday 4:30 – 5:30pm
TA: Oscar Beijbom
Email: obeijbom at ucsd.edu
Office: EBU3b Room B275
Office Hours: Wednesday: 121pm
Class Description:
Comprehensive introduction to computer vision providing broad coverage
including low level vision (image formation, photometry, color, image feature
detection), inferring 3D properties from images (shapefromshading, stereo
vision, motion interpretation) and object recognition. A companion course,
CSE252B, Computer Vision II is taught in the spring quarter. 4 units.
Required
Text:
"Computer vision: A Modern Approach," (2nd ed.) David
A. Forsyth, Jean
Ponce, Prentice Hall, ISBN: 013608592X
Supplemental Text:
“Computer Vision: Algorithms and Applications”, Richard Szeliski, is available at: http://szeliski.org/Book/.
Prerequisites:
Linear algebra and Multivariable calculus (e.g., Math 20A & 20F),
programming, data structure/algorithms (e.g., CSE100). Probability can also be
useful.
Programming:
Assignments will include both written problem sets and programming assignments
in Matlab. Students can either purchase the Matlab student edition or use
copies available on University machines such as are available in the
APE Lab.
Grading:
Assignments: 60%
Final Exam: 40%
Late Policy:
Written homework will be due in class and accepted thereafter with a penalty of
10% per day starting from the due date. Programming assignments will
have a handin procedure described with the assignment, and also has a 10% per
day late penalty. No assignments will be accepted after the graded assignments
have been returned or the solutions have been released.
Collaboration Policy:
You may work together on homework assignments to discuss ideas and methods only, however what you turn in should be your own work and any code should be your own coding. Copying is not permitted.
Homework 0 [Due 10/3]: Getting Started with Matlab. Updated text to appread on Thursay Sep. 26.
Homework 1 [Due 10/17]: Camera Models and Homography
Homework 2 [Due 10/31]. New due date: [11/05].
Homework 3 [Due 11/19] New due date: [11/21].
Homework 4 [Due 12/06]
[Note that this Syllabus is
tentative & subject to change ]

Date / Link to lecture notes 
Topic / Readings 
Intro to Computer Vision 

Human Visual System, F&P sec. 1.3. RS 118 

Image Formation and Cameras. Projective Geometry. Homogenous Coordinates. Homography 

Homography. Perspective, Affine, orthographic projection and geometry. Camera Models. Lenses 

Lenses Continued. SO(3) Transformations. Radiometry (Irradiance, Radiance, BRDF), F&P Chapter 4 

Radiometry Continued. Radiance and Irradiance. Special BRDF's, Light Sources, Photometric Stereo. 

Lighting and Photometric Stereo F&P Section 2.2 

Photometric Stereo F&P Section 2.2 

Illumination Cones, Belhumeur, Kriegman, What Is the Set of Images of an Object under All Possible Illumination Conditions?, IJCV 28(3), 1998, 245260 

Color, Dichromatic model, RS 67 

Color, Dichromatic Model Continued. SUV Space. Filtering F&P Chap. 7, 8, RS. 1011.22 

Edges RS 238=249 

Epipolar Constraint and Stereo I, F&P Sec. 10.1, RS 530544 

Stereo II, Dynamic Programming, Chapter 11, 545548, 552556 

Optical Flow, Trucco and Verri, pp. 178194, RS 4381414 

Infinitesimal structure from Motion, Trucco and Verri pp. 195202, 208211 

Tracking, F&P Chap.17, RS 235237, 282284, 551552, 605609 

Statistical Pattern Recognition, F&P 22.122.3 

Support Vector Machines & Kernel Methods, F&P Sec. 22.5, 22.8 

Appearancebased Recognition and Modelbased recognition, F&P Chap. 18, RS 655722 
Programming languages:
The primary language will be Matlab. Click here for Serge
Belongie's Matlab resource links.
Other
excellent textbooks:
Introductory
Techniques for 3D Computer Vision, Trucco and Verri (textbook for CSE152)
An Invitation to 3D Vision: From Images
to Geometric Models, Ma, Soatto, Kosecka and Sastry, Springer Verlag, 2003,
ISBN 0387008934 (textbook for CSE252B)
Some useful
links:
Camera Calibration
Toolbox for Matlab (Bouguet)
Microsoft Camera
Calibration Code (Zhang)
Intel OpenCV
CVonline
The Computer Vision Home
Page
Handy Math reference: MathWorld