Course Information

Course Name	Turkish	Bilgisayarla Görü
	English	Computer Vision
Course Code	YZV 416E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	3	-	-
Course Language		English
Course Coordinator		Gözde Ünal
Course Objectives		1. To learn main techniques in processing 2D images and analysis of 2D and 3D vision problems in extracting and understanding the visual structure in the scenes. 2. To study the 2D and 3D vision techniques in terms of both mathematical principles and computer realizations as well as applications
Course Description		This course introduces the foundations of 2D and 3D computer vision, emphasizing geometry, estimation, and modern learning-based perspectives. Advanced treatments of multi-view geometry, nonlinear optimization, and research-level 3D reconstruction are intentionally beyond scope and are reserved for graduate-level courses.
Course Outcomes		1. Know and discuss the main problems, application areas and techniques of computer vision 2. Design and implement various image transforms: point-wise transforms, neighborhood operation-based spatial filters, and geometric (coordinate) transforms over images 3. Define, construct, and apply segmentation, feature extraction, dimensionality reduction, and visual motion estimation algorithms to extract relevant information from 2D or higher dimensional images 4. Describe basic mathematical techniques required in 3D vision (linear algebra, algebra groups, projective geometry), define 3D-2D image formation process and camera parameters, express rigid-body and homography transformations using 3D transformations 5. Construct solutions to some 3D vision problems such as triangulation, epipolar geometry, and depth estimation 6. Construct least squares solutions to problems in computer vision 7. Implement computer realizations of vision algorithms in Python.
Pre-requisite(s)		Deep Learning (YZV302E or YZV303E), MAT281E or equivalent Linear Algebra, YZV231E or equivalent Probability Theory, BLG202E Numerical Methods or equivalent.
Required Facilities
Other
Textbook		R. Szeliski, Computer Vision. Algorithms and Applications. Springer, 2nd Ed. 2022.
Other References		D. Forsyth, J. Ponce. Computer Vision: A Modern Approach, Pearson, (2nd Ed.) 2012.

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