TÜRKÇE
ENGLISH
Information
| Code | CENG712 |
| Name | Intelligent Computational Imagıng and Video |
| Semester | . Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Doktora Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Doç. Dr. MUSTAFA ORAL |
Course Goal
To introduce students the fundamentals of image formation; To introduce students the major ideas, methods, and techniques of computer vision and pattern recognition; To develop an appreciation for various issues in the design of computer vision and object recognition systems; and To provide the student with programming experience from implementing computer vision and object recognition applications
Course Content
introduction to course;An overview of the intelligent systems;An overview of image processing;Feature and corner detection;Feature descriptors and matching;High Dynamic Range imaging;Camera models;Stereo;Structure from motion; techniques for combining multiple images;Tone Reproduction for Realistic Images; Intelligent imaging applications
Course Precondition
None
Resources
GONZALEZ R.C., WOODS R.E., and ADDINS S.L., Digital Image Processing Using Matlab, Pearson Education Inc., New Jersey, 2004.
Notes
AWCOCK G.J. and THOMAS R., Applied Image Processing, McGrow-Hill, Inc., 1996. 4.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | identify basic concepts, terminology, theories, models and methods in the field of computer vision |
| LO02 | identify basic concepts, terminology, theories, models and methods in the field of artificial intelligence |
| LO03 | describe basic methods of computer vision related to multi-scale representation, edge detection and detection of other primitives, stereo, motion and object recognition |
| LO04 | develop and apply computer vision techniques for solving practical problems |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | On the basis of the competencies gained at the undergraduate level, it has an advanced level of knowledge and understanding that provides the basis for original studies in the field of Computer Engineering. | 4 |
| PLO02 | Bilgi - Kuramsal, Olgusal | By reaching scientific knowledge in the field of engineering, he/she reaches the knowledge in depth and depth, evaluates, interprets and applies the information. | 2 |
| PLO03 | Yetkinlikler - Öğrenme Yetkinliği | Being aware of the new and developing practices of his / her profession and examining and learning when necessary. | 3 |
| PLO04 | Yetkinlikler - Öğrenme Yetkinliği | Constructs engineering problems, develops methods to solve them and applies innovative methods in solutions. | 3 |
| PLO05 | Yetkinlikler - Öğrenme Yetkinliği | Designs and applies analytical, modeling and experimental based researches, analyzes and interprets complex situations encountered in this process. | |
| PLO06 | Yetkinlikler - Öğrenme Yetkinliği | Develops new and / or original ideas and methods, develops innovative solutions in system, part or process design. | 4 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Has the skills of learning. | 4 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Being aware of new and emerging applications of Computer Engineering examines and learns them if necessary. | 3 |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Transmits the processes and results of their studies in written or oral form in the national and international environments outside or outside the field of Computer Engineering. | 1 |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Has comprehensive knowledge about current techniques and methods and their limitations in Computer Engineering. | 4 |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Uses information and communication technologies at an advanced level interactively with computer software required by Computer Engineering. | 3 |
| PLO12 | Bilgi - Kuramsal, Olgusal | Observes social, scientific and ethical values in all professional activities. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | introduction to course | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 2 | An overview of the intelligent systems first part | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 3 | An overview of the intelligent systems 2nd part | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 4 | An overview of image processing first part | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 5 | An overview of image processing 2nd part | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 6 | Feature and corner detection | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 7 | Feature descriptors and matching | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 8 | Mid-Term Exam | Exam preparation | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | High Dynamic Range imaging | Reading course material | Öğretim Yöntemleri: Anlatım |
| 10 | Camera models | Reading course material | Öğretim Yöntemleri: Anlatım |
| 11 | Stereo | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 12 | Structure from motion | Reading course material | Öğretim Yöntemleri: Soru-Cevap, Anlatım, Tartışma |
| 13 | techniques for combining multiple images (basic methods) | Reading course material | Öğretim Yöntemleri: Anlatım |
| 14 | techniques for combining multiple images (advanced methods) | Reading course material | Öğretim Yöntemleri: Anlatım |
| 15 | Intelligent imaging applications | Reading course material | Öğretim Yöntemleri: Anlatım, Tartışma, Gösteri |
| 16 | Term Exams | Project Development and presentation | Ölçme Yöntemleri: Proje / Tasarım, Performans Değerlendirmesi |
| 17 | Term Exams | Project Development and presentation | Ölçme Yöntemleri: Proje / Tasarım, Performans Değerlendirmesi |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||