|COURSE UNIT TITLE||COURSE UNIT CODE||SEMESTER||THEORY + PRACTICE (Hour)||ECTS
||3 + 0
|TYPE OF COURSE UNIT||Elective Course
|LEVEL OF COURSE UNIT||Doctorate Of Science
|YEAR OF STUDY||-
|NUMBER OF ECTS CREDITS ALLOCATED||10
|NAME OF LECTURER(S)||-
|LEARNING OUTCOMES OF THE COURSE UNIT
||At the end of this course, the students;
1) Know the low- and mid-level image processing techniques such as filtering, edge detection, segmentation and clustering.
2) Know about the object and scene recognition.
3) Know the techniques of motion detection from video data.
4) Know about the object and people tracking.
5) Comprehend the human activity recognition and inference.
|MODE OF DELIVERY||Face to face
|PRE-REQUISITES OF THE COURSE||No
|RECOMMENDED OPTIONAL PROGRAMME COMPONENT||BIL 566 Digital Image Processing
|1st Week ||An introduction and basic concepts |
|2nd Week ||Low and mid level image processing:filtering|
|3rd Week ||Low and mid level image processing:filtering|
|4th Week ||Edge detection|
|5th Week ||Segmentation and clustering|
|6th Week ||Object and scene recognition|
|7th Week ||Object and scene recognition|
|8th Week ||Mid-term|
|9th Week ||Motion detection from video data |
|10th Week ||Motion detection from video data|
|11th Week ||Object and people tracking|
|12th Week ||Object and people tracking|
|13th Week ||Human activity recognition and inference|
|14th Week ||Human activity recognition and inference|
|RECOMENDED OR REQUIRED READING||1. Forsyth, D.A. & Ponce, J., "Computer Vision: A Modern Approach", 2nd edition, Prentice Hall, (2011).
2. Shapiro, L.G. & Stockman, G.C., "Computer Vision", Prentice Hall, (2001).
3. Parker, J.R., "Algorithms for Image Processing and Computer Vision", Wiley, (2010).
|PLANNED LEARNING ACTIVITIES AND TEACHING METHODS||Lecture,Questions/Answers,Practice,Problem Solving,Project,Report Preparation,Presentation
|ASSESSMENT METHODS AND CRITERIA||
|Contribution of In-term Studies to Overall Grade(%)||60|
|Contribution of Final Examination to Overall Grade(%)||40|
|LANGUAGE OF INSTRUCTION||Turkish
|KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)|
|K1|| X || X || X || X || X |
|K2|| X || || || X || |
|K3|| || || X || || X |
|K4|| X || X || || || |
|K5|| || || X || X || X |
|K6|| || || || X || X |
|K7|| || || || || |
|K8|| X || || X || || X |
|K9|| || X || || || |
|K10|| || || || X || X |
|K11|| || || X || X || X |
|K12|| || || X || X || X |