CS 554: Computer Vision

Spring 2021

• Instructor: Hamdi Dibeklioglu
• Office hours:  by appointment / online
• Class hours:
• Monday 13:30-15:20; Thursday 8:30-10:20.
• While every other week we will have 2+2 hours of lectures, other weeks there will be one 2-hours lecture. Please see the schedule below for the dates of the lectures.
• Class room:
• Online (EA-502)

UPDATES / NEWS:

• Earlier you were asked to submit your literature surveys by sending an email, however, the procedure has been changed. Please submit your survey report and presentation slides in a single zip archive via CS554 Moodle page.
• Earlier you were asked to submit your projects by sending an email, however, the procedure has been changed. Please submit your project report, codes/materials, and project presentation slides in a single zip archive via CS554 Moodle page.
  
• Please follow this link to access the online exam protocol. (Accessible only within Bilkent network. Use VPN to access from home.
• Midterm exam will be held on Monday, 19 April 2021, starting at 12:40.
• All important dates (including homework, project/project progress, and survey submission/presentation deadlines, and midterm date) have been announced.
• Homework details have been announced, please see the homework section below.
• Lectures start as of 28 January 2021.
• When you submit your reports for survey, homework, project progress, and project, please make sure that you use the required keyword in the subject line of the corresponding email. For the subject line keywords please see the Important Dates section below.

• R. Szeliski. Computer Vision: Algorithms and Applications, Springer Science & Business Media, 2010. [Available Online] 
• D.A. Forsyth and Jean Ponce. Computer Vision: A Modern Approach, Prentice Hall Professional Technical Reference, 2002.
• I. Goodfellow, Y. Bengio, A. Courville. Deep Learning, MIT Press, 2016. [Available Online]

Assessment Methods:

Any of the following will directly result in an F grade:

• not submitting a project or homework (including report),
• not presenting a survey on the pre-scheduled date,
• being absent in the midterm,
• being absent in a project presentation.

Prerequisites:

• Basic calculus and linear algebra.
• Basic probability theory and statistics.
• Good programming skills.

Passing Grade: No predetermined grade to pass the course.

Makeup Policy: Medical report holders will be entitled for the midterm make up. Makeup exam will be comprehensive.

Homework:
Please follow this link to access the homework details. Homework details/materials are accessible only within Bilkent network. Use VPN to access from home.

• Groups of two students will choose a topic related to computer vision, and prepare a short survey on it.
• Surveys should be based on about 10 papers (report: 5 pages max.).
• You will make a presentation on your survey in class. The presentation should be in parallel with your report. Duration of your presentation may be 10 minutes at most.
• Survey topics should be confirmed first. Very similar topics to others’ will not be allowed (priority: first come, first served).
• Your chosen survey topic and a few lines explanation (indicating group members) should be sent to dibeklioglu@cs.bilkent.edu.tr by 15 February 2021, 23.59 (Turkey time).

Project:

• By groups of two students.
• Projects related to your research topics are encouraged.
• Build a “real” computer vision application and test it on some data.
• You may re-use existing code, but indicate what you code you have re-used and what code you have developed yourself.
• Three stages:
• Proposal: one-page description of the project topic and the planning (indicating group members) for the project should be sent to dibeklioglu@cs.bilkent.edu.tr by 18 February 2021 (23:59 Turkey time)
• Progress report & presentation (report: 2 pages max.)
• Final report & presentation (report: 4 pages max.)
• Examples of projects:
• Performing face verification for automatic passport control
• Recognizing the identity or expression of faces
• Recognizing gestures for communication via sign language
• Recognizing or detecting objects in images (Pascal VOC / ImageNet)
• Segmenting parts in medical images
• Performing restoration of old, deteriorated photographs
• Performing automatic morphing of images
• Performing video stabilization using object tracking
• Identifying the writer of a piece of handwriting

Template for the Reports:
All reports (including homework report) must be prepared using the IEEE double-column transactions article template (i.e. "bare_jrnl.tex").

Important Dates:

Tentative Schedule & Lecture Notes:
Lecture notes below are downloadable only within Bilkent network. Use VPN to access from home.

Week	Topic	Dates	Lecture Notes
1	Introduction, human vision, overview of basics	28 January 2021 (08:30-10:20)
2	Feature point extraction, Feature point description and matching	01 February 2021 (13:30-15:20) 04 February 2021 (08:30-10:20)
3	Homography and image stitching, Camera geometry	08 February 2021 (13:30-15:20) 11 February 2021 (08:30-10:20)
4	Stereo vision and depth estimation	18 February 2021 (08:30-10:20)
5	Stereo vision and depth estimation, Motion, Face Processing	22 February 2021 (13:30-15:20) 25 February 2021 (08:30-10:20)
6	Face Processing, Shape, scene, and object recognition	04 March 2021 (08:30-10:20)
7	Shape, scene, and object recognition, Conditional and Markov random fields	08 March 2021 (13:30-15:20) 11 March 2021 (08:30-10:20)	>>
8	Spring Break	No Lecture
9	Visual Tracking	25 March 2021 (08:30-10:20)
10	Action recognition and motion magnification	29 March 2021 (13:30-15:20) 01 April 2021 (08:30-10:20)	>>
11	Action recognition and motion magnification, Deep learning	08 April 2021 (08:30-10:20)
12	Deep learning Project Progress Presentations	12 April 2021 (13:30-15:20) 15 April 2021 (09:00-10:20)	>>    .
13	Midterm	19 April 2021 (12:40)	.
14	Deep learning	26 April 2021 (13:30-15:20)	>>
15	Survey Presentations	06 May 2021 (08:30-10:20)	.
16	Project presentations	10 May 2021 (13:30-15:20)	.