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Language of Instruction
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English
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Level of Course Unit
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Bachelor's Degree
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Department / Program
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COMPUTER ENGINEERING
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Type of Program
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Formal Education
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Type of Course Unit
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Elective
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Course Delivery Method
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Face To Face
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Objectives of the Course
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Introducing basic basic image processing and computer vision techniques.
Discussing the foundations of image formation, measurement, analysis, object representations.
Explaining the theoretical knowledge and practical applications of common and the state of the art CV and approaches.
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Course Content
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This course introduces students to foundational methods, algorithms commonly used in computer vision field and discusses their applications. In relevant subjects, most popular deep learning based methods takes place. The topics include digital image processing basics such as histogram equalization, neighbourhood operations and filtering; feature detection, extraction and matching, SIFT, Hough transform, stereo and epipolar geometry, image to image projections, Homographies and mosaics, projective geometry, essential and fundamental matrix, camera calibration, object detection, recognition and segmentation using classical methods as well as more modern deep learning based approaches. The students will have hands on experience and ability to discuss of theoretical aspects of the methods.
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Course Methods and Techniques
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Prerequisites and co-requisities
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None
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Course Coordinator
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None
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Name of Lecturers
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Asist Prof.Dr. VEHBİ ÇAĞRI GÜNGÖR burcu.gungor@agu.edu.tr
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Assistants
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None
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Work Placement(s)
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No
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Recommended or Required Reading
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