| School/Faculty/Institute |
Graduate School |
| Course Code |
ITC 532 |
| Course Title in English |
Computer Vision |
| Course Title in Turkish |
Computer Vision |
| Language of Instruction |
EN |
| Type of Course |
Flipped Classroom |
| Level of Course |
Intermediate |
| Semester |
Bahar |
| Contact Hours per Week |
| Lecture: 3 |
Recitation: 0 |
Lab: 0 |
Other: 0 |
|
| Estimated Student Workload |
188 hours per semester |
| Number of Credits |
7.5 ECTS |
| Grading Mode |
Standard Letter Grade
|
| Pre-requisites |
None |
| Expected Prior Knowledge |
None |
| Co-requisites |
None |
| Registration Restrictions |
Only Graduate Students |
| Overall Educational Objective |
To become familiar with the fundamental concepts of Computer Vision, such as image formation, camera parameters, preprocessing, convolution, segmentation, edge and corner detection, line and ellipse fitting, image understanding and object recognition. |
| Course Description |
This course provides a comprehensive introduction to some fundamental aspects of Computer Vision. The following topics are covered: Introduction, Image formation, camera parameters, preprocessing, convolution, segmentation, edge and corner detection, line and ellipse fitting, Object Tracking, image understanding and object recognition, deep Learning. |
| Course Description in Turkish |
Bu derste; bilgisayarla görünün temel kavramları şu konu başlıklar altında kapsamlı bir şekilde incelenmektedir: Giriş, görüntü oluşumu, kamera parametreleri, önişleme, evriştirme, bölütleme, kenar ve köşe bulma, doğru ve elips uydurma, görüntü analizi, nesne tanıma ve derin öğrenme. |
Course Learning Outcomes and Competences
Upon successful completion of the course, the learner is expected to be able to:
1) Görüntü oluşum sürecini, kamera parametrelerini ve projeksiyonlarını anlamak
2) Filtreleme ve ön işleme için evrişim uygulamak
3) Kenar ve köşe tespitini ve eğri uydurmayı kullanmak
4) Görüntü anlama ve nesne tanımayı kullanmak
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Relation to Program Outcomes and Competences
| N None |
S Supportive |
H Highly Related |
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Program Outcomes and Competences |
Level |
Assessed by |
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| Prepared by and Date |
, |
| Course Coordinator |
TUNA ÇAKAR |
| Semester |
Bahar |
| Name of Instructor |
Prof. Dr. MUHİTTİN GÖKMEN |
Course Contents
| Hafta |
Konu |
| 1) |
Bilgilendirme-Giriş |
| 2) |
Görüntü oluşumu
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| 3) |
Kamera parametreleri |
| 4) |
Ön işleme: Histogram değişiklikleri
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| 5) |
Evrişim ve gürültü azaltma
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| 6) |
Kenar ve köşe algılama
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| 7) |
Çizgi, daire ve elips uydurma |
| 8) |
RANSAC ve Homografi |
| 9) |
Binoküler Stereo
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| 10) |
Optik Akış ve Takip
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| 11) |
Görüntü Anlama
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| 12) |
Nesne Tanıma-PCA
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| 13) |
Nesne Tanıma-Derin Öğrenme |
| 14) |
Proje sunumları
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| 15) |
Proje/Sunum Dönemi |
| 16) |
Proje/Sunum Dönemi |
| Required/Recommended Readings | Computer Vision: Algorithms and Applications, Richard Szeliski, Springer Science & Business Media, 2010
Introductory Techniques for 3-D Computer Vision, by Emanuele Trucco, Alessandro Verri, Prentice-Hall, 1998
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| Teaching Methods | Lecturing and exercises in the classroom with computers. |
| Homework and Projects | In-class exercises, 3 Projects |
| Laboratory Work | Programming exercises |
| Computer Use | For Programming |
| Other Activities | None |
| Assessment Methods |
| Assessment Tools |
Count |
Weight |
| Küçük Sınavlar |
4 |
% 20 |
| Projeler |
2 |
% 40 |
| Final |
1 |
% 40 |
| TOTAL |
% 100 |
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| Course Administration |
gokmenm@mef.edu.tr
02123953600
Office: 5th Floor, #18
Rules for attendance: Minimum of 70% attendance required.
Missing a quiz: Provided that proper documents of excuse are presented, each missed quiz by the student will be given a grade which is equal to the average of all of the other quizzes. No make-up will be given.
Missing a midterm: Provided that proper documents of excuse are presented, each missed midterm by the student will be given the grade of the final exam. No make-up will be given.
A reminder of proper classroom behavior, code of student conduct: Academic dishonesty and plagiarism will be subject to Law on Higher Education Article 54.
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Bilgi Paketi / Ders Kataloğu