Computer Engineering Department, Koç University
Office: Eng 139 Phone: (212) 338 1585 E-mail: yyemez@ku.edu.tr
Lectures: Tue & Th 13:00 - 14:15, SCI-103
Office Hours: Tue & Th 11:30 - 12:30
COMP 508 is a graduate course to introduce the fundamentals of computer vision theory and practice. With recent developments in computing, transmission and display technologies, 2D/3D visual data have become commonplace in scientific, industrial and commercial arenas. The digital visual data are mostly reflections from real world and contain useful information. The main goal of computer vision is to analyze sensed images for extracting this information, to construct scene descriptions and knowledge representations, to recognize objects and thereby to make useful decisions about physical objects and scenes.
The course is open to graduate and (highly motivated) undergraduate students who are willing to understand the vision technology in conjunction with real world applications and especially very well suited to those who are interested in doing research in computer vision. Good programming skills and knowledge of Matlab/C/C++ are necessary for the course project and homework assignments. Basic DSP knowledge will also be very helpful.
Syllabus (in pdf)
Textbooks: No required textbooks, but reading from
the following books will be helpful.
Honor Code
All code and documentation handed in exams, assignments and projects must be your own work. In programming assignments, you can exchange ideas, but you should not ever share your code, even partly.
Grading
Final grades will be composed of: (tentative)
|
Programming assignments |
30% |
|
Exam |
35% |
|
Project |
35% |
TA
Nusrah Hussain, Office: MVGL Lab, nhussain15@ku.edu.tr, Office hours: Wed 11:00-13:00
There
will be programming assignments posted here. I plan the first
assignment to be in OpenCV/C. The other assignments will probably be in
Matlab.
Assignment 1, due to 11 Oct, Thursday.
Assignment 2, due to 30 Oct, Tuesday.
Assignment 3, due to 22 Nov, Thursday.
By the first month of the semester, each student will have chosen a topic for her/his project. Projects can be either research oriented or applications programming oriented, addressing one of the computer vision problems/concepts/applications covered throughout the course. Depending on the chosen topic, students may be expected to do a literature survey on different techniques aiming at solving the specified problem and then to implement and test one of these techniques. A software implementation is mandatory, using OpenCV or Matlab.
Students are expected to submit a project proposal by Nov 5.
| Lecture | Topic | Reading (from suggested textbooks) |
| 18 Sep |
Intro |
Szeliski: Chapter 1 |
| 20 Sep |
Imaging |
Szeliski: Chapter 2, Sonka (3rd ed.): Ch. 1, 2, 3 |
| 25 Sep |
Filtering |
Szeliski: Ch. 3.1, 3.2 Sonka: Ch. 5.3 |
| 27 Sep - 2 Oct |
Frequency |
Szeliski Ch. 3.4, Sonka Ch. 3 |
| 4 Oct - 16 Oct |
Feature Detection |
Szeliski Ch. 4, Sonka Ch. 5.3 |
| 18 Oct |
RANSAC |
Szeliski Ch. 6.1.4, Ch. 9.1 |
| 23- 30 Oct, 1 Nov |
Recognition |
Szeliski Ch. 14, Sonka Ch 8,9,10 |
| 6-8 Nov |
PCA |
Szeliski Ch. 14.2.1 |
| 15, 20 Nov |
Segmentation |
Szeliski Ch. 5, Sonka Ch. 6 |
| 22 Nov - |
3D Vision |
Szeliski Ch 2.1, 6.3, 7, 11, 12 Sonka Ch 11,12 Also: Multiple View Geometry in Computer Vision, Hartley and Zisserman |
OpenCV Resources