| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Robot Vision | BTM607 | Elective | Doctorate degree | 1 | Fall | 8 |
Name of Lecturer(s)
Associate Prof. Dr. Serdar SOLAK
Research Assistant Seda BALTA
Learning Outcomes of the Course Unit
1) Students know and apply image processing techniques.
2) Students know computer vision applications.
3) Students know the camera geometric model and icamera calibration.
4) Students can develop applications using an image processing library.
Program Competencies-Learning Outcomes Relation
| Program Competencies | ||||||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | ||
| Learning Outcomes | ||||||||||||||
| 1 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 2 | No relation | No relation | No relation | No relation | No relation | High | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 3 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 4 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Image Processing
Course Contents
Image and color space types, Binary image: Geometric and topological properties, Region and image segmentation, Image processing: Continuous images and discrete images, Edge and edge detection, Pattern classification, Computer vision, Camera coordinate frame, camera calibration, Position and orientation of objects identification.
Weekly Schedule
1) Course Description and introduction to image processing2) Imaging Systems: Camera model and Camera calibration, Binocular imaging systems
3) Image Processing and Feature Extraction:Image representations (continuous and discrete), Edge detection
4) Image Processing and Feature Extraction:Image representations (continuous and discrete), Edge detection
5) Motion Estimation:Regularization theory, Opticalcomputation, StereoVision, Motion estimation, Structure from motion
6) Motion Estimation:Regularization theory, Opticalcomputation, StereoVision, Motion estimation, Structure from motion
7) Shape Representation and Segmentation:Deformable curves and surfaces, Snakes and active contours, Level set representations, Fourier and wavelet descriptors, medial representations, Multiresolution analysis
8) Midterm Exam
9) Shape Representation and Segmentation:Deformable curves and surfaces, active contours, set representations, Fourier and wavelet descriptors, Medial representations,Multiresolution analysis
10) Object recognition:Hough transforms and other simple object recognition methods, Shape correspondence and shape matching, Principal Component analysis, Shape priors for recognition.
11) Object recognition:Hough transforms and other simple object recognition methods, Shape correspondence and shape matching, Principal Component analysis, Shape priors for recognition.
12) Object recognition:Hough transforms and other simple object recognition methods, Shape correspondence and shape matching, Principal Component analysis, Shape priors for recognition.
13) Computer Vision Application Examples
14) Presentation of the Computer Vision Projects
15) Presentation of the Computer Vision Projects
16) Final Exam
Recommended or Required Reading
1- Computer Vision - A modern approach, by D. Forsyth and J. Ponce, Prentice Hall Robot Vision, by B. K. P. Horn, McGraw-Hill.
2- Richard Szeliksy “Computer Vision: Algorithms and Applications” (http://szeliski.org/Book/)
3- G erardMedioni and Sing Bing Kang “Emerging topics in computer vision”, http://people.inf.ethz.ch/pomarc/pubs/KangMedioniBook.pdf
Planned Learning Activities and Teaching Methods
Assessment Methods and Criteria
Language of Instruction
Turkish
Work Placement(s)
Required